Kenya CCA 2001

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					THE UNITED NATIONS COMMON COUNTRY ASSESSMENT FOR KENYA




                                  2001




      OFFICE OF THE UN RESIDENT COORDINATOR IN KENYA
United Nations Office at Nairobi, Gigiri, P. O. Box 30218, Nairobi, Kenya.
                      Telephone: (254-2) 621234.
     Facsimile: (254-2) 624489/90. Internet: registry.ke@undp.org
ii
Table of Contents


INDEX OF TABLES .................................................................................................................................... iv

LIST OF ACRONYMS ................................................................................................................................. vi

LIST OF UNITED NATIONS AGENCIES IN KENYA ................................................................................ vii

ACKNOWLEDGEMENTS ......................................................................................................................... viii

EXECUTIVE SUMMARY ............................................................................................................................ ix

INTRODUCTION ......................................................................................................................................... 1
     (a)  The objective of the CCA ....................................................................................................... 1
     (b)  The rationale of the CCA ....................................................................................................... 1
     (c)  Methodology and analytical approach ................................................................................... 2
     (d)  The CCA consultation process .............................................................................................. 2

I.       KEY DEVELOPMENT ISSUES IN KENYA: THE POVERTY ISSUE ................................................ 4
         (a)  Defining the poor ................................................................................................................... 4
         (b)  The dimensions of poverty .................................................................................................... 4
         (c)  Macroeconomic trends .......................................................................................................... 5
         (d)  Demographic trends .............................................................................................................. 9
         (e)  Socio-cultural changes ........................................................................................................ 10
         (f)  Governance and structural transformations ....................................................................... 11

II.      POVERTY, HUMAN RIGHTS AND DEVELOPMENT ..................................................................... 12

III.     NATIONAL SITUATION IN RELATION TO GLOBAL CONFERENCES ......................................... 14

IV.      ISSUES OF PARTICULAR CONCERN ............................................................................................ 17
         (a)  Maternal and child health ................................................................................................... 17
         (b)  Disease patterns .................................................................................................................. 18
         (c)  Access to basic education ................................................................................................... 19
         (d)  HIV/AIDS ............................................................................................................................ 21
         (e)  Increasing frequency and severity of disasters .................................................................. 23
         (f)  Degradation of natural resources ........................................................................................ 23

V.       UNDERLYING PROBLEMS AND PRIORITY AREAS FOR ACTION ............................................. 26
         (a) Expanding opportunities ..................................................................................................... 26
         (b) Securing empowerment ....................................................................................................... 26
         (c) Guaranteeing security ......................................................................................................... 27

VI.      THE WAY FORWARD ..................................................................................................................... 28




                                                                                                                                                           iii
     Annexes



     I.       The CCA timetable and management structure ............................................................................. 29

     II.      Data collection: rationale, sources and limitations ....................................................................... 32

     III.     (a)      The CCA consultative process, list of participants and affiliation ..................................... 35
              (b)      List of participants in the CCA ........................................................................................... 38

     IV.      The CCA indicator list - status and trend ...................................................................................... 44

     V.       The CCA indicator list - references and notes ............................................................................... 50

     VI.      Kenya’s performance with respect to global conference goals ...................................................... 57

     VII.     Terms of reference ......................................................................................................................... 64

     VIII. Tables of disaggregated data ......................................................................................................... 66

     INDEX OF TABLES

              1.0      Rural absolute poverty by province ..................................................................................... 66
              1.1      Decomposition of urban poverty measures, 1997 ............................................................... 66
              1.2      Absolute poverty measures by rural region of residence, 1997 .......................................... 67
              1.3      Food poverty measures by rural region of residence, 1997 with new districts .................. 68
              1.4      Hard-core poverty measures by rural region of residence, 1997 ........................................ 69
              1.5      Population growth rate in Kenya - 1944-2010 .................................................................... 70
              1.6      Population projections for provinces and districts medium fertility decline ...................... 71
              1.7      Population projections for provinces and districts (‘000’) medium fertility
                       decline - males ..................................................................................................................... 72
              1.8      Population projections for provinces and districts (‘000’) medium fertility
                       decline - females .................................................................................................................. 73
              1.9      Nutritional stunting (moderate malnutrition) among children under five years
                       in Kenya (percentage stunted) ............................................................................................ 74

              2.0      Distribution of nutritional status indicators in 1992, 1994 and 1997 by district ............... 74
              2.1      Key education indicators for selected years ....................................................................... 75
              2.2      Key education indicators by gender, 1989 - 1999 ............................................................... 75
              2.3      Adult education enrolment by sex, 1989 - 1999 ................................................................. 75
              2.4      Percentage distribution of household members who never attended
                        school by region ................................................................................................................. 76
              2.5      Percentage distribution of household members by region and
                       level of education: secondary and above ............................................................................. 77
              2.6      Distribution of land per person by region............................................................................ 78
              2.7      Percentage distribution of the population aged six years and above
                       who never attended school .................................................................................................. 79
              2.8      Percentage distribution of the population aged six years and above by region and
                       level of education: secondary and above in 1997 ................................................................ 80



iv
2.9   Distribution of land per person by region in 1997 .............................................................. 81
3.0   Primary school enrolment by sex in 1995 ........................................................................... 82
3.1   Secondary school enrolment by sex in 1995 ....................................................................... 83
3.2   Wage employment by province, 1990 - 1999 ....................................................................... 84
3.3   Wage employment by sector, 1989 - 1999 ........................................................................... 85
3.4   Wage employment in the public sector, 1989 - 1999 .......................................................... 85
3.5   Estimated real wage earnings per employee, 1989 - 1999 ................................................. 85
3.6   Persons engaged, recorded total, 1990 - 1999 ................................................................... 86
3.7   Estimated production of selected agricultural commodities, 1995 - 1999 ......................... 86
3.8   Recorded marketed production at current prices, 1991 -1999 ........................................... 87
3.9   Sale of some of the major crops to marketing boards, 1990 - 1999 ................................... 88
4.0   Agricultural inputs purchased, 1990 - 1990 (K million) ..................................................... 88
4.1   Exports of fresh horticultural produce ................................................................................ 89
4.2   Tea production (‘000’ tons), 1989 - 1999 ............................................................................ 89
4.3   Coffee production (‘000’ tons), 1987 - 1999 ....................................................................... 89
4.4   Production and sale of livestock and dairy products, 1990 - 1999 ..................................... 89
4.5   Analysis of key fiscal trends, 1992/3 - 1999/00 ................................................................. 90
4.6   Total expenditure on roads, 1990/91 - 1999/00 .................................................................. 91
4.7   Development expenditure on water supplies and related services, 1990/1 - 1999/00 ....... 91
4.8   Balance of trade, 1990 - 1999 ............................................................................................. 91
4.9   Central government expenditure on main services, 1990/91 - 1999/00 ............................. 92




                                                                                                                                       v
     List of Acronyms


     AIDS     Acquired Immune Deficiency Syndrome
     CBS      Central Bureau of Statistics
     CCA      Common Country Assessment
     CEDAW    Convention on Eradication of All Forms of Discrimination Against Women
     EFA      Education for All
     HIV      Human immuno-deficiency virus
     IPRSP    Interim Poverty Strategy Paper
     IUCN     International Union for Conservation of Nature and Natural Resources
     KACA     Kenya Anti-Corruption Authority
     KEPI     Kenya Expanded Programme on Immunization
     NAAC     National Aids Consultative Council
     NASCOP   National Aids/STD Control Programme
     PRSP     Poverty Reduction Strategy Paper
     SD       Standard deviation
     STD      Sexually transmitted diseases
     UNCED    United Nations Conference on Environment and Development
     UNDAF    United Nations Development Assistance Framework




vi
List of United Nations Agencies in Kenya


Food and Agriculture Organization of the United Nations (FAO)
International Civil Aviation Organization (ICAO)
International Finance Corporation (IFC)
International Labour Organization (ILO)
International Monetary Fund (IMF)
Office for Coordination of Humanitarian Affairs (OCHA)
Joint United Nations HIV/AIDS Programme (UNAIDS)
United Nations Centre for Human Settlements (UNCHS)
United Nations Drug Control Programme (UNDCP)
United Nations Development Programme (UNDP)
United Nations Environment Programme (UNEP)
United Nations Educational, Scientific and Cultural Organization (UNESCO)
United Nations Fund for Population Activities (UNFPA)
United Nations High Commissioner for Refugees (UNHCR)
United Nations Information Centre (UNIC)
United Nations Children’s Fund (UNICEF)
United Nations Industrial Development Organization (UNIDO)
United Nations Fund for Women (UNIFEM)
United Nations Office at Nairobi (UNON)
United Nations Office for Project Services (UNOPS)
UNDP Office to Combat Desertification and Drought (UNSO)
World Bank (WB)
World Food Programme (WFP)
World Health Organization (WHO)




                                                                            vii
       Acknowledgements


       The preparation of the Common Country Assessment        theme groups for undertaking analysis in their re-
       (CCA) was a collaborative exercise involving the        spective areas of focus.
       United Nations Country Team, the Government of
       Kenya and other development partners. While heads       We acknowledge the role of individual representa-
       of United Nations agencies, referred to as the Kenya    tives and staff of agencies in the review of specific
       Country Committee (KCC), provided the core over-        aspects of the document.
       sight and strategic thinking reflected in this CCA,
       various other people made specific contributions that   Last but not least, we thank all our partners from
       we must acknowledge. Special thanks go to the CCA/      the Government and other development agencies for
       United Nations Development Assistance Framework         contributing to the preparation of the CCA through
       (UNDAF) Advisory Team who supported Kenya               provision of data, clarification of indicators and par-
       Country Committee by providing the technical guid-      ticipation in the assessment and analysis. It is our
       ance and backstopping, working closely with the         hope that the CCA will contribute to the elucidation
       secretariat of the Resident Coordinator as well as      of the development dialogue in the country as it re-
       external consultants. We are very grateful to the       lates to poverty reduction. As we prepare to incor-
       consultants, Messrs. Terrence Ryan and Boniface         porate the results of the CCA into a revised UNDAF,
       K’Oyugi, who assisted in data collection, assessment    we look forward to using that process to institu-
       and analysis. We are also grateful to the six UNDAF     tionalize collaboration and enhance partnerships.




viii
Executive Summary


(a)   Objectives and expected outcomes                   ducing poverty in order to achieve long-term and
                                                         sustainable development. In view of this context, it
This Common Country Assessment (CCA) for Kenya           is an opportune moment to revisit the CCA, to re-
is a joint exercise by the various United Nations        examine the indicators and their trends and to lay
funds, programmes and specialized agencies oper-         the groundwork for a continuous process of moni-
ating in Kenya (collectively referred to as organiza-    toring. Through this process, the United Nations
tions or agencies) to assess the development status      agencies, the Government and other development
of the country. The objective of the CCA is to iden-     partners can measure the progress of the poverty
tify gaps and priorities that deserve new or contin-     reduction strategies.
ued focus by the United Nations syö‰em under
UNDAF which is set for mid-term review in mid 2001.      (d)    Issues of particular concern
In carrying out the analysis, the CCA is guided by
national commitments as well as the endorsement          The five key issues identified that merit special con-
of the development goals of the various global con-      sideration include: maternal and child health; dis-
ferences and conventions to which Kenya is signa-        ease patterns; access to basic education; the high
tory.                                                    rate of HIV/AIDS; the increasing frequency and se-
                                                         verity of disasters; and degradation of natural re-
(b)   Lessons from the pilot CCA                         sources.

The original CCA, although helpful in bringing the       (i)    Maternal and child health
agencies together on a common footing, did not fully
incorporate input from the Government and civil           Poverty in Kenya has severely undermined the
society. Moreover, it did not have sufficient analyti-   health status of the people as evidenced by the lim-
cal content to assist United Nations agencies in iden-   ited resources available for health care. Children and
tifying a clear focus and priorities for channelling     women are particularly adversely affected judging
development assistance. The present CCA has ben-         from the deteriorating infant, under five and mater-
efited from a more in-depth analysis as well as an       nal mortality rates. The three mortality rates as re-
extensive consultative process involving the United      corded in 1998 are: maternal mortality rate (590-
Nations system, the Government, civil society and        650 per 100,000); under five mortality rate (105 per
bilateral and multilateral partners. It therefore re-    1,000) and infant mortality rate (71 per 1,000). All
flects a common analysis of trends and priorities        three show significant deterioration in comparison
that will serve as a basis for promoting collabora-      with the values recorded in the 1989 census.
tive programming.
                                                         (ii)   Access to basic education
(c)   Links with national priorities
                                                          The net enrolment rate deteriorated from 80 per
 The preparation of the CCA comes in the wake of         cent in 1990 to 76.5 per cent in 1997. Gross enrol-
ongoing major efforts by the Government of Kenya         ment rates in the rural areas have deteriorated while
to review its national planning framework, under         those in the urban areas have improved slightly.
the Poverty Reduction Strategy Paper (PRSP) proc-        Enrolment in primary schools is higher than in sec-
ess. It aims at ensuring that the Government’s pri-      ondary schools where the proportions of both males
orities and resource allocation are targeted at re-      and females progressing from Form 1 to Form 4 has




                                                                                                                  ix
    declined dramatically from around 95 per cent for         conflicts and industrial and transport accidents. The
    both sexes in 1996 to 75 per cent for boys and 78         range of these disasters may well extend beyond
    per cent for girls in 1999.                               the capacity of the current institutional framework
                                                              that has tended to concentrate on drought and food
    (iii)    High rate of HIV/AIDS                            insecurity. What is required is a long-term proactive
                                                              disaster mitigation strategy involving all the
    Data from the Sentinel Sites continue to show in a        stakeholders.
    very graphic way that the HIV/AIDS epidemic has
    been growing. The current adult prevalence rate ac-       (e)     Underlying problems and priority
    cording to the National AIDS/STD Control Pro-                     areas for action
    gramme is 13.5 per cent with Thika and Busia being
    the districts with the highest prevalence rate (33 per    In an analysis aimed at determining the underlying
    cent and 34 per cent respectively). Available data also   causes of the problems identified above, the CCA
    show that 80 to 90 per cent of infections are in the      discusses three key priority areas of attention. The
    15-49 years age group and that 5 to 10 per cent of        priority areas are expansion of opportunities, secur-
    the infections occur in children under 5 years of age.    ing of empowerment and guaranteeing of security.
    It is estimated that over 30,000 children are born
    with HIV annually, over 1.9 million Kenyans are in-       (i)      Expanding opportunities
    fected and approximately 850,000 children are cur-
    rently orphaned. These trends continue despite high       One recurring theme of international conferences is
    public awareness of the causes and consequences of        the right of access of all people to the basic necessi-
    HIV infection.                                            ties of life and the opportunity to advance their well-
                                                              being. This theme is common because of issues such
    (iv)      Degradation of natural resources                as declining access to education, health care and
                                                              other basic social services, often with a gender bias
    Kenya is endowed with a wealth of natural re-             against girls and women. Redressing this situation
    sources, part of which are legally protected as re-       would require improvement of the livelihood of the
    serves or parks for conservation of biodiversity,         people through access to markets, credit, informa-
    water and soil. Due to rapid population growth as         tion and production skills and generation of employ-
    well as industrialization, natural resources have in-     ment opportunities.
    creasingly been converted into cultivated and built-
    up areas. In addition, officially gazetted areas have     (ii)    Securing empowerment
    not been spared from conversion and many others
    have degenerated due to overexploitation for tim-         Institutions, particularly public ones, are unrespon-
    ber, charcoal burning, fuelwood, grazing, fishing,        sive to the concerns and demands of the poor. There
    hunting and minor products as well as encroach-           is a need for inclusive decentralization, gender eq-
    ment. All this has resulted in the depletion of the       uity and greater participation of women in a variety
    natural resource base, a key source of livelihood for     of social, political and economic processes. Similarly,
    a majority of Kenyans.                                    assisting the poor to advance their interests through
                                                              proper targeting of poverty reduction resources would
    (v)     Increasing frequency and severity of disasters    work in the long-term interest of empowerment of
                                                              communities.
    Kenya continues to be exposed to a variety of natu-
    ral and man-made disasters that undermine human           (iii)   Guaranteeing security
    development. Among the most significant natural
    disasters are droughts, wild fires, floods and land-       The various ways in which lack of security exposes
    slides. Although earthquakes and volcanic activity        a large proportion of Kenyans to devastating shocks
    have not occurred, they have the potential of doing       that diminish their chances of extricating themselves
    so. The most significant man-made disasters are civil     from poverty and that threaten the non-poor include



x
lack of security and the threat of conflicts in many
of the poorest regions of the country. Putting in place
an effective disaster prevention, preparedness and
response system and mobilizing a coordinated na-
tional strategy to deal with the critical problems of
the day such as HIV/AIDS and food security would
lead to improvements in security and well-being.

(f)   The way forward

 The CCA is meant to provide the United Nations
agencies with an analysis and appropriate data for
the design of the UNDAF, the development plan that
should involve all the agencies in the attainment of
common goals. It focuses attention on critical is-
sues that would appear to contribute significantly
to the attainment of specified broad goals, in this
case improving broadly defined welfare and poverty
reduction. The analysis done in the CCA indicates
ways in which the agencies, through the theme
groups, can prepare their contributions to the
UNDAF.




                                                          xi
Introduction


(a)    The objective of the CCA                                     ponents and policy objectives of this strategy are as
                                                                    follows:
For several years now, the United Nations agencies
in Kenya1 have been working together on a com-                      (i)   To facilitate sustained and rapid economic
mon United Nations response to the development                            growth;
challenges of Kenya. This effort is built around a                  (ii) To improve governance and security;
common planning framework, the UNDAF, designed                      (iii) To increase the ability of the poor to raise their
to ensure that the development operations of the                          incomes;
United Nations system in Kenya share a common                       (iv) To improve the quality of life of the poor; and
objective and common strategies for cooperation.                    (v) To improve equity and participation.
Kenya was one of the first pilot countries to formu-
late and implement an UNDAF, beginning in late                      The Government will use the strategy outlined in
1997 with the development of an initial CCA. The                    the PRSP as a national planning framework upon
CCA is a country-based process for reviewing and                    which detailed sectoral priorities, programmes and
analyzing the national development situation and                    allocations will be developed. The PRSP will also
identifying key issues. It is the basis for advocacy                outline the policies, reforms and programmes that
and policy dialogue and for the preparation of the                  the Government will undertake over the coming
UNDAF. The UNDAF, in turn, must be based on ar-                     three years to realize the stated objectives2 . The
eas of consensus with the Government that arise                     CCA and the resulting UNDAF support this approach
from the assessment process.                                        to address the issue of poverty but cast the concept
                                                                    in the broader context of human rights discussed
(b)    The rationale of the CCA                                     below. These rights have been at the heart of a se-
                                                                    ries of global conferences convened by the United
The CCA is closely linked with the objectives of pov-               Nations over the last decade. They have also helped
erty reduction. This focus is in line with the direc-               countries to focus on the most deprived and excluded
tion of the policy targets of the Government of Kenya.              of their populations.
In 1999, the Government published the National
Poverty Eradication Plan that was followed by a                     The philosophy of the PRSP and the approach of
short-term focused Poverty Reduction Strategy Pa-                   the CCA are similar. The CCA has drawn on a wide
per (PRSP) which was published at the time of the                   participation with emphasis on involving a variety
2000/01 budget. As stated in the PRSP, “the pri-                    of stakeholders. The underlying approach of both
mary development goal for Kenya is to achieve a                     the PRSP and CCA/UNDAF seeks to create an envi-
broad-based, sustainable improvement in the stand-                  ronment that will attract broad participation of all
ards of welfare of all Kenyans”. The five basic com-                members of the community so as to raise economic




1   There are over 24 United Nations agencies operating in Kenya working in close cooperation with the Government and in partner-
    ship with non-governmental organizations and bilateral and multilateral institutions
2   Government of Kenya: Poverty Reduction Strategy Paper for the Period 2000-03, Ministry of Finance and Planning, June 2000, p. 2



                                                                                                                                      1
    growth in a sustainable manner. This will increase                   and the estimated impact of HIV/AIDS at that time.
    the income of the poor and improve the quality of                    The lack of demographic data has also meant that
    their life where that quality concerns both material                 the problems of urbanization that constitute one of
    access to goods and services and the well-being that                 the target areas of analysis have not benefited from
    comes from empowerment in social and political                       the most recent insights. Second, different sources
    processes and reduced vulnerability.                                 of data often gave different values for the same vari-
                                                                         able. On several occasions, some data were found
    (c)      Methodology and analytical                                  to be seriously irrelevant. Third, although there were
             approach                                                    many suggestions for non-quantifiable indicators
                                                                         with respect to rights, it proved impossible to get
    Work on the CCA began in March 2000 following an                     up-to-date data on such things as gender and age-
    agreement by the United Nations Country Team to                      specific prison populations and those relating to
    prepare a new CCA on the basis of the lessons learnt                 cases before the courts. Data on crimes as a proxy
    from the pilot phase, uppermost of which was the                     for a deteriorating environment with respect to rights
    need to undertake a more in-depth analysis of the                    have been introduced. However, they lack precision.
    development situation.3 Following initial consulta-                  Annex V provides a complete list of CCA indicators
    tions and briefing to partners, and on the basis of                  and data.
    the CCA table of indicators4 , data were collected.
    The data collection process involved access to the                   Analysis in the CCA was undertaken by each of the
    various databases located in government depart-                      six UNDAF theme groups, working with partners in
    ments and among other partners and collection of                     the Government and civil society, based on the pri-
    materials or documents, electronically on disks or                   ority issues in their respective areas of focus using
    as hard copy, relevant to the CCA. Studies already                   the “problem tree” approach. The objective of the
    undertaken by some agencies and the ideas and ex-                    analysis was to understand the underlying causes
    periences of heads of agencies and key programme                     of the key problems identified which would assist in
    staff were also utilized. The data were compiled and                 the overall CCA analysis. This innovative consulta-
    relevant disaggregations (age, sex, spatial, etc) were               tive approach demonstrated the causal relationships
    computed according to the various parameters to                      between development problems. Sometimes, what
    show the status and the trend. Gender issues have                    appeared as a critical issue to one group was seen
    been incorporated as a cross-cutting theme through-                  as the intermediate or root cause of the issue by
    out the policy objectives and within all sections of                 another.
    the document. Annex II provides details on data
    collection, including sources and limitations, while                 (d)    The CCA consultation process
    annex IV contains a list of CCA indicators and
    sources of data.                                                     Apart from the United Nations Country Team that
                                                                         has assisted in shaping the thinking reflected in the
    There were three main limitations of data identified                 CCA, the exercise was inclusive, involving the ac-
    during the data collection exercise. First, there was                tive participation of the Government, non-govern-
    lack of demographic data as a result of the unavail-                 mental organizations and other development part-
    ability of the full results of the 1999 Population and               ners, particularly in the analysis. The close interac-
    Housing Census data. As a result, the estimated                      tion with partners during the process has helped to
    demographic data in the table of indicators are from                 improve the common understanding of the develop-
    the analytical volumes of the 1989 Population and                    ment situation in Kenya in a coherent and focused
    Housing Census using the medium fertility forecast                   manner. The consultative process also helped to




    3     See annex I for details on the CCA timetable and annex VII for the Terms of Reference
    4     The CCA Guidelines establish a set of indicators that are generally acceptable for comparative purposes.



2
build the capacity of senior technical personnel from   the PRSP. The Government has already requested
the Government in the analysis and in priority set-     the United Nations to share the outcome of the analy-
ting. As a result of this consultation process, there   sis as well as the data and the indicators contained
is now an opportunity to carry this forward into the    in the CCA. Annexes III (a) and (b) describe the proc-
UNDAF. Similarly, there is a possibility of forging     ess of collaboration and consultation that was
closer ties between the United Nations agencies, the    adopted for the CCA, including a list of the partici-
Government and other development partners around        pants.




                                                                                                                 3
    I.      Key Development Issues in Kenya:
            The Poverty Issue

    (a)   Defining the poor                                   cent work as subsistence farmers compared to 43
                                                              per cent of men. As the PRSP points out, “given
    The poor, defined as those who cannot afford basic        that subsistence farmers are among the very poor,
    food and non-food items, constitute slightly more         this relative dependence of women on subsistence
    than half the population of Kenya - 52 per cent ac-       farming explains the extreme vulnerability of
    cording to the 1997 Welfare Monitoring Survey. Both       women. These problems are most severe in the arid
    the number of absolutely poor people and the inci-        and semi-arid areas where women spend a great
    dence of poverty are increasing. The number of poor       portion of their time searching for water and fuel”
    people increased from 3.7 million in 1972-73 to 11.5      (p. 18). A drop in the productivity of those resources
    million in 1994, to 12.5 million in 1997 and is now       due to environmental degradation, for example, is
    estimated to have reached 15 million. According to        more likely to affect women than it will affect men.
    the 1997 Welfare Monitoring Survey, poverty               Female-headed households are particularly poor and
    reached 53 per cent of the rural population and 49        among the most vulnerable.
    per cent of the urban population. This contrasts with
    47 per cent rural poverty in 1994 and only 29 per         Finally, as the PRSP also points out, the distribution
    cent urban poverty in that year’s survey. Since the       of the benefits of development is very uneven and
    rural population is much larger than the urban popu-      Kenya ranks very high in terms of unequal income
    lation, most poor people in Kenya live in the rural       distribution. According to the PRSP, “estimates indi-
    areas. There are slightly more than five million          cate that a high proportion of wealth is concentrated
    households in Kenya. Of these, 1.8 million are poor.      in a very small proportion of the total population.
    Among the poor households, 87 per cent are rural          This income concentration is the highest amongst
    and 13 per cent are urban. Subsistence farmers ac-        the 22 poorest countries and is exceeded only by
    count for over 50 per cent of the total poor in Kenya.    Guatemala (per capita income US$1,340), South Af-
                                                              rica (US$ 3,160) and Brazil (US$3,640)” (p. 18).
    The bulk of the poor are located within the highly
    populated belt stretching from the South to the           (b) The dimensions of poverty
    South-East from Lake Victoria to the coast. The high-
    est incidence of poverty is found in the arid and semi-   These numbers indicate the depth and breadth of
    arid districts of Northern Kenya where the over-          poverty in Kenya and the seriousness of the chal-
    whelming majority of the people are poor in spite of      lenge not only to accelerate poverty reduction but
    the total population being relatively small. The ar-      also to reverse the existing trend of an increasing
    eas of high and medium agricultural potential con-        incidence of poverty. In addressing this challenge,
    tain the bulk of the rural population and, conse-         there is increasing agreement that poverty should
    quently, high concentrations of poor households.          be seen as the result of overlapping economic, po-
    Machakos and Kakamega together contain 10 per             litical and social processes that deprive people of
    cent of the country’s poor. With four other districts     fundamental freedoms. As the World Development
    (Makueni, Siaya, Kitui and Bungoma) they account          Report 2000/2001 puts it, “Poor people live without
    for 25 per cent of all poor households in Kenya. Sev-     fundamental freedoms of action and choice that the
    enteen rural districts account for 57 per cent of         better-off take for granted. They often lack adequate
    households living below the poverty line.                 food and shelter, education and health, deprivations
                                                              that keep them from leading the kind of life that
    Women are considerably more vulnerable to poverty         everyone values. They also face extreme vulnerabil-
    than men. Of the active female population, 69 per         ity to ill health, economic dislocation and natural dis-



4
asters. And they are often exposed to ill treatment        duplication. This causes a slowing down and ineffi-
by institutions of the State and society and are pow-      cient governance and management of development.
erless to influence key decisions affecting their lives.   Kenya’s potential to mobilize its social capital
These are all dimensions of poverty” (p. 1).               through the active participation of civil society is
                                                           diminished to the extent that dual or parallel ad-
Poverty has conventionally been treated as a lack          ministrative structures limit the capacity of local
of some material things. This approach has given           authorities to be managers of their development at
rise to a variety of measures, starting from an insuf-     the grassroots. Therefore, decentralization and devo-
ficiency of food to an insufficiency of other neces-       lution of power to lower levels based on the princi-
sary possessions such as shelter to an insufficiency       ple of subsidiarity can lead to good governance in
of income to acquire what is necessary. These meas-        both rural and urban environments. Consequently,
ures are all material but are subject to some criti-       the CCA and the resulting priorities for action must
cism. The concepts of “an adequate diet,” “an adult        address all the three dimensions.
equivalent” or even “basic needs” are not easily
transferable between communities with different            (c)     Macroeconomic trends
cultures and environments. Even the creation of a
national poverty line is bedevilled by the need to         (i)      Declining economic growth and instability
generalize – for ease of computation – the cost of
critical items across very heterogeneous rural mar-        As the PRSP puts it, “The fight against poverty, ig-
kets and environments. The international criterion         norance and disease has been a major goal of Gov-
of those living on less than US$1 per day is even          ernment since independence. However, growth in
more complex, involving as it does the appropriate-        terms of the gross domestic product (GDP) has not
ness of the exchange rate and the accuracy of the          improved over this period to provide a good basis to
measurement of national income and the population.         fight poverty” 5 . For instance, economic growth
The present CCA takes a broad approach to poverty          (GDP) in real terms averaged 8 per cent during the
covering income poverty, access to social and eco-         1963-72 decade following independence. The rate
nomic facilities and factors of production, or rela-       declined to 4.8 per cent for the period 1973-82, which
tional poverty (exclusion and isolation). The combi-       was still above average for low-income countries.
nation of these determines an individual’s or a            Annual growth from 1983 to 1994 declined to 3.5
group’s advantages within the social milieu and in         per cent and then to 2.3 per cent in 1997, 1.8 per
turn their access to information and prospects to          cent in 1998 and 1.4 per cent in 1999. The latest
make decisions and change their situations.                estimate for 2000 is just over one per cent. The con-
                                                           tinued slowdown in economic performance was re-
As mentioned above, the CCA attempts to focus on           flected in virtually all the key sectors of the economy
a broader concept of poverty. To reduce poverty, ac-       (see Table 1 below).
tions must be taken to increase opportunities for all
people to have access to an improved livelihood and              Table 1: Average sectoral shares of GDP - 1977-97
                                                                                    (per cent)
basic social services, to empower people to interact
in political, social and economic processes and to          SECTOR              1977-80   1981-85   1986-90   1991-97

enhance their security by reducing their vulnerabil-        Agriculture             34      33        31        29
ity to disasters and violence. All three relate directly    Manufacturing           12      13        13        10
                                                            Rest of industry         7       7         5         6
to the commitments made at the global conferences           Total services
and the basic human rights that these entail. A dis-          (private & public)    47      47        50        57
                                                            Public services         14      14        15        14
cussion of the progress made towards the achieve-
                                                            Total GDP              100     100       100       100
ment of these goals and commitments is outlined in
chapter II. Furthermore, the structure of the gov-          Source:     The Government of Kenya/UNICEF
                                                                        20:20 Initiative Report 2000
ernment and the administration can often result in


5   PRSP, p. 23



                                                                                                                        5
    It is therefore evident from the foregoing that ef-            Figures 1, 2 and 3 below show that there was con-
    forts to date have been inadequate and the growth              siderable instability in a variety of macroeconomic
    of poverty has not been reversed. Economic turmoil             indicators early in the decade. The catalyst would
    over the past decade has exacerbated the difficul-             appear to have been the massive increase in money
    ties. One of the consequences of this situation has            supply associated with the elections that took place
    been a reduction in real expenditure on basic social
    services (health and nutrition, education, water and
    sanitation) which essential for poverty reduction.                                      Figure 1
    Real expenditures in these services declined from
    approximately 20 per cent of the government budget
    in 1980 to about 12.4 per cent by 1997. On educa-
    tion, the decline in expenditure (as a proportion of
    the real government budget) dropped from 23 per
    cent in 1980 to 19 per cent in 1997. Furthermore,
    while recurrent expenditure on education over the
    1980-97 period averaged 96 per cent of the budget
    of the Ministry of Education, development expendi-
    ture averaged only 6 per cent. The burden of provid-
    ing education facilities was shifted to communities,
    resulting in differential access to education.

    Over the same period (1980-97), similar budgetary
    reductions were also experienced in health and nu-
    trition. As a proportion of the real government
    budget, real public expenditure on health declined
    from about 10 to 6 per cent. On nutrition, the real
    expenditure decreased from K£ 98,000 in 1980 to
    K£ 60,200 in 1997. Spending on reproductive health                                      Figure 2
    and family planning services also declined from K£
    3.3 million in 1980 to K£ 3 million in 1997 although
    this had peaked to K£ 5 million in 1991 and 1995.
    As a proportion of the ministry’s budget and real
    GDP, this sector suffered a drop from 5 to 2 per cent
    for reproductive health and 0.5 to 0.1 per cent for
    family planning services during the same period.
    With regard to water and sanitation, public expendi-
    ture in real terms on low cost water and sanitation
    services remained almost stagnant, only rising from
    about K£ 17 million in 1980 to K£ 18 million in 1997.
    As a proportion of government budget and GDP,
    water and sanitation services declined from 2.4 to
    0.6 per cent for water and 0.6 to 0.4 per cent for
    sanitation, over the same period.6 The expenditures
    reviewed above can be assumed to have had a nega-
    tive impact on the provision of the services con-
    cerned.


    6   These figures are drawn from the Government of Kenya/UNICEF 20:20 Initiative Report titled “Government Expenditures on
        Basic Social Services”, June 2000; p.19-23.



6
                                                        The increase in money supply and the resultant in-
                                                        flation (linked to the decline in real growth) might
                      Figure 3
                                                        have increased the inflationary pressure from the
                                                        money supply and led to major reforms in early 1993.
                                                        The inflation, together with the decline in investor
                                                        confidence, led to massive net outflows of foreign
                                                        exchange and an unsustainable balance of payments.
                                                        There were no resources for investment to allow
                                                        economic recovery and job creation. First, the tax
                                                        effort of the Government (Figure 8) moved from be-
                                                        low 22% of GDP to excessively high levels of over
                                                        27%. This was linked to a dramatic decline in the
                                                        propensity to save domestically (Figure 9) as peo-
                                                        ple became poorer (Figure 6).

                                                        (ii)   The restoration of growth and sustainability

                                                        The return to stability in 1994 saw a restoration of
                                                        growth and much more stable macroeconomic prices.
                                                        However, the domestic debt had more than doubled
                                                        by that time, causing a major diversion of budget-



at the end of 1992. The impact of this increased                              Figure 5
money supply on the price level and inflation can be
seen from Figure 1. Furthermore, the meeting of the
Consultative Group of the Group of Eight in Paris in
November 1991 had resulted in the freezing of quick-
disbursing aid and a major pressure for multiparty
elections. Figure 5 illustrates the dramatic drop in
the rate of growth between 1990 and 1993. This
decline was also linked to a contraction in the agri-
cultural sector, which dominates the economy, ac-
counting for about a quarter of Kenya’s GDP (Fig-
ure 4).


                      Figure 4
                                                                              Figure 6




                                                                                                               7
    ary resources to debt service. Consequently, the ca-
    pacity of the Government to provide appropriate                                  Figure 8
    support to the development of the infrastructure and
    similar development-oriented activities was severely
    curtailed. The depreciation of the Kenya shilling,
    which can be seen from Figure 2 above, presented
    yet a further cost to the budget in servicing the for-
    eign debt. Faced with this situation, the Government
    was exploring all sources of funding. These re-
    sources had to come from the domestic market since
    donors did not deem Kenya’s reform efforts cred-
    ible, often regarding them as unsustainable. It will
    be noted in Figure 9 that domestic savings declined
    drastically yet again and the revenue collection ef-
    forts of the Government severely cut into the earn-
    ings of the private sector (Figure 7). Although the
    magnitude of the cash deficit in the Treasury started                            Figure 9
    to decrease in 1995, the Government still had to
    borrow from the financial markets due to the need
    to service the foreign debt. It will be noted in Figure
    10 that there was an outflow of resources from the
    Kenyan economy to the world at large from 1994
    onwards. This outflow, which was financed by do-
    mestic borrowing, increased at a higher rate than
    the money supply. Such a situation was not sustain-
    able and Figure 5 illustrates the collapse of the short-
    lived recovery. Once again, growth fell below 2 per
    cent and income per capita declined (Figure 6).

    The foregoing analysis suggests that the Govern-
    ment of Kenya first tackled the instability question
    and successfully brought the macroeconomy under            ing. Although data on unemployment are not avail-
    control. The strategies pursued were not sustain-          able, a variety of proxies indicate a deeper depres-
    able and growth declined. With the decline in in-          sion. Among the indicators in the annex are the head-
    come per capita, it is not surprising that even though     count measure, the food poverty measure and the
    inflation levels are low, poverty has been increas-        poverty gap measure. All three measures provide
                                                               the same picture of serious deterioration between
                                                               1994 and 1997. It can only be assumed that since
                           Figure 7
                                                               growth has continued to decline since 1997, all the
                                                               three indicators will have worsened. A further indi-
                                                               cator which looks at the share of national consump-
                                                               tion taken by the poorest 20 per cent of the popula-
                                                               tion shows that a larger proportion of resources is
                                                               in fact going to the poor.

                                                               Ideally, the discussion of poverty should not be gen-
                                                               eralized; it should at least rather disaggregate be-
                                                               tween rural and urban residents and between males
                                                               and females. The nature of the data does not allow



8
                                                        These figures give inter-census enumerated popu-
                     Figure 10
                                                        lation growth rates of 3.4 and 2.9 per cent per an-
                                                        num during the 1979-89 and 1989-99 inter-census
                                                        periods, respectively. The highest growth rate of 9.5
                                                        per cent per annum during the 1989-99 inter-cen-
                                                        sus period was recorded in North-Eastern Province
                                                        followed by Nairobi with 4.8 per cent. Central Prov-
                                                        ince recorded the lowest growth rate of 1.7 per cent
                                                        followed by Eastern and Nyanza provinces whose
                                                        population grew at a rate of 2.1 per cent and 2.3 per
                                                        cent, respectively.

                                                        Given the fact that the above growth rates are aver-
                                                        age rates during the inter-census period, the census
disaggregation. However, it can be seen that both       year rates will be determined after the estimation
rural and urban poverty have worsened. Particularly     of key components of population change, namely,
noteworthy is the deepening of poverty in the urban     birth, death and migration rates. The basic demo-
areas where 29 per cent of the people were classi-      graphic indicators between the 1969 and 1989 cen-
fied as poor in 1994. This figure rose to 49 per cent   suses are given in table 2.
in 1997.
                                                         Table 2: Basic demographic indicators, Kenya 1969,1979
(d)   Demographic trends                                                   and 1989 censuses

                                                                                        Population census
Kenya is committed to pushing its agenda in the
                                                         Indicator                  1969a*        1979b*     1989c*
areas of population and development with the re-
                                                         Crude birth rate             50.0         54.0       49.0
cent adoption of the sessional paper on National
                                                         Crude death rate             17.0         14.0       11.0
Population Policy for Sustainable Development (May
2000). This will further help in the implementation      Growth rate                    3.3          3.8     3.4d*
                                                         Total fertility (number
of the goals of the International Conference on Popu-
                                                         of children per woman)         7.6          7.8       6.7
lation and Development up to the year 2010. Ac-          Infant mortality rate
cording to the recently released 1999 Kenya Popu-        per 1000 live births          119           88         66
lation and Housing Census results, the total popu-       Life expectancy
lation of Kenya increased from 15.3 million in 1979      at birth (years)               50           54         60

to 21.4million in 1989 and to 28.7 million in 1999.      Sources: a* Central Bureau of Statistics, 1970; b* Central
                                                         Bureau of Statistics, 1981; c* Central Bureau of Statistics,
                                                         1991; Central Bureau of Statistics, 1996; d* based on 1979-
                                                         89 inter-census period.
                                                         Generally, however, these figures are consistent with the
                     Figure 11                           declining fertility rates that have been reported in the
                                                         Kenya Demographic and Health Surveys carried out in 1989,
                                                         1993 and 1998, (Figure 11).



                                                        With regard to the structure of the population, 44
                                                        per cent of the people enumerated during the 1999
                                                        census were aged below 15 years, 52 per cent were
                                                        aged 15 to 64 years and 4 per cent were aged 65
                                                        years and above. However, it should be noted that
                                                        the fertility decline described above has been a ma-
                                                        jor contributing factor to the decline in the propor-
                                                        tion of the population aged below 15 years as com-



                                                                                                                        9
     pared to 49 per cent in 1989. Concern for the large
     proportion of the youth population has given rise to                             Figure 14
     the need for reproductive information and counsel-
     ling services to enable the youth to manage their
     sexuality. Despite the implementation of appropriate
     programmes, adolescents and youth continue to suf-
     fer from problems such as inadequate knowledge of
     sexuality, precocious sexual activity, early child-bear-
     ing, unsafe abortions and the risk of contracting sexu-
     ally transmitted infections (STIs) and HIV/AIDS.

     (e)   Socio-cultural changes

     Although gender disparity continues to be a major
     concern, there has been a marked improvement over
     the years in several sectors. In education, the gap        There is also an observable growth in the earnings
     between the enrolment of boys and girls at both pri-       of females employed in the formal sector (Figure 15
     mary and secondary levels is gradually narrowing           below). In 1969, women represented 14.9 per cent
     (Figure 12). In addition, even though there are still      of the total labour force in this sector, out of which
     two males for every female at the university level,        62.4 per cent earned less than100 Kenya shillings
     this is a major improvement in comparison with 24          per month. Ten years later, while they merely repre-
     years ago when the enrolment ratio was more than           sented 16.1 per cent, a negligible group was earn-
     4.6 to one (Figure13).                                     ing the minimum wage. By 1989, 20.7 per cent of
                                                                formal sector employees were women and by 1999
                                                                this had risen to 29.4 per cent. Although the avail-
                            Figure 12
                                                                able data do not allow for a clear comparison of earn-
                                                                ings, it can be seen that while only 55 women earned
                                                                more than 3,000 shillings per month in 1969, there
                                                                were 12,889 earning in excess of 30,000 Kenya shil-
                                                                lings per month in 1999. In other words, the socio-
                                                                economic status of women has undergone a posi-
                                                                tive transformation over the last two decades, largely
                                                                as a result of the spirited empowerment campaign
                                                                and the increased access of women to education and
                                                                training.



                                                                                      Figure 15
                            Figure 13




10
One of the long-term changes that have taken place       years later they held 4.1 per cent. In local authori-
is the massive increase in urbanization (figure 15).     ties, the participation rose from 2.4 per cent to 8.1
In 1969, there were only 47 towns with populations       per cent over the same period. However, this im-
in excess of 2,000 and only 9.7 per cent of the popu-    proved participation is far too slow to demonstrate
lation lived in them. By 1989, 17.5 per cent of the      real commitment to gender equality. The judicial
population inhabited 122 towns. By the 1999 Popu-        service, in which the participation of women is some-
lation and Housing Census, this number had in-           what higher, continued to move towards a more rep-
creased to 194. Urbanization has resulted in reduced     resentative ratio, being 25.9 per cent in 1994 and
pressure on the land as well as job openings for the     30.6 per cent in 1998.
growing educated elite. At the same time, however,
it has placed severe stress on the traditional insur-    From a long-term perspective, Kenya’s politics has
ance and welfare mechanisms and strained both the        undergone major positive transformations. While
administrative capacity and the financial resources      there was a de jure single party in 1983 and the re-
of local authorities. While increased urbanization       placement of the secret ballot with queue voting in
and the culture that goes with it may help to create     1988, the 1992 elections were contested by secret
a sense of national identity, it also creates tremen-    ballot with 10 parties competing. In those elections,
dous human stress in the form of street children,        only 58.9 per cent of registered voters voted but in
drug use and addiction to the television that many       1997, 65.7 per cent cast their ballot, with 22 con-
urban parents are grappling with.                        testing parties. It was also significant that one of
                                                         the presidential candidates was a woman. A related
(f)   Governance and structural                          transformation that is gradually taking root is the
      transformations                                    increased awareness of human rights. Despite the
                                                         lack of supportive data, it can be argued that there
With regard to governance, the most important event      has been an increased awareness of human rights.
was the restoration of multiparty democracy. Al-         In particular, the rights of women have received
though it may not have met all the expectations of       greater attention over the last fifteen years. The
the public in 1992, it has definitely led to far wider   rights of children are only just beginning to receive
consultation and involvement of the public. One of       the attention they deserve with draft legislation and
the most noteworthy aspects of this has been the         improvements in the approach of the courts to child
slow but steady increase in the participation of         abuse. The right to food and shelter has been an is-
women in the various national bodies. In 1988, they      sue for particular groups of the population rather than
held 1.5 per cent of the parliamentary seats and ten     a matter of general countrywide concern.




                                                                                                                   11
     II. Poverty, Human Rights and Development


     Poverty has conventionally been understood as lack            Enabling citizens to express their own opinions, to
     of some material possessions. In extreme cases,               assemble and to associate for common interests goes
     these possessions have been basic necessities. This           along way in creating mental well-being. In addi-
     approach has given rise to a variety of measures,             tion, freedom of speech, worship and access to the
     starting with insufficiency of food, insufficiency of         media are vital components of welfare. From the
     other necessary possessions such as shelter and               standpoint of physical well-being, the individual
     insufficiency of income to acquire what is necessary.         largely judges whether he or she is poor or not by
     The present CCA takes a broader view of the con-              looking at those things over which he or she has
     cept of poverty, looking at it as a denial of some-           control – not least of which is finance and access to
     thing that is necessary for the dignity of an indi-           credit. But in many ways the wealth of individuals
     vidual whereby that dignity, which is a right to all,         can be judged by their human capital in terms of
     is denied. While it therefore relates to the lack of          education, health and access to information. Their
     means to support material well being, it also refers          position in society, including those laws and con-
     to laws and customs that deny rights and increase             ventions which govern their behaviour, similarly
     insecurity, thus undermining mental well being. This          gives them a sense of security and of belonging, or,
     is a critical element of the dignity of a person (see         if they are absent, a sense of insecurity and inferior-
     the box below).                                               ity.




                                      Poverty, human rights and human development

          Poverty limits human freedoms and deprives a person of dignity. The Universal Declaration of Human Rights,
          the Declaration on the Right to Development and a large body of other human rights instruments make this
          clear. The Vienna Declaration and Programme of Action adopted at the 1993 World Conference on Human
          Rights affirms that “extreme poverty and social exclusion constitute a violation of human dignity”.


          Human Development Reports takes the view that poverty is broader than lack of income, that it is depriva-
          tion in various respects. If income is not the sum total of human lives, a lack of income cannot be the sum
          total of human deprivation. Indeed, Human Development Report 1997 defined it as deprivation in the valu-
          able things that a person can do or be. The term “human poverty” was coined to distinguish this broad
          deprivation from the narrower income poverty, a more conventional definition limited to deprivation in in-
          come or consumption.


          Human development focuses on expanding capabilities that are essential for all people, capabilities that
          are so basic that their lack forecloses other choices. Human poverty focuses on the lack of these capabilities
          – to live a long, healthy and creative life, to be knowledgeable, to enjoy a decent standard of living, dignity,
          self-respect and the respect of others.


          How does a person escape poverty? The links between different dimensions of poverty can be mutually
          reinforcing in a downward spiral of entrapment. But they can also be mobilized to create a vicious circle and
          an upward spiral of escape. Expanding human capabilities and securing human rights can thus empower
          poor people to escape poverty.


          Source: Human Development Report 2000, p.73




12
Over the last two decades, a number of key global                  makers is to build an enabling environment that
conferences have been convened at which treaties                   empowers people, particularly the poor, guarantees
and conventions relating to human rights have been                 them opportunities to fulfil their human rights and
signed7 . These conventions have helped to place the               supports them in this endeavour. Building the capa-
issue of rights at the centre of development strate-               bilities of the poor through the provision of basic
gies. They have also helped countries to focus on                  health care, nutrition and education is key to nur-
the most deprived and excluded of their populations,               turing and sustaining the rights approach to devel-
paying special attention to those deprivations that                opment.
have resulted from discrimination. This view of de-
velopment goes beyond the conventional yardstick                   The availability of these services in a way bridges
of market efficiency and incomes. It also broadens                 the gap between the mental and the physical welfare
the area of accountability so that those who have                  within society since even when they are not used,
authority perform their duties and respect the rights              they provide a kind of insurance that reduces the
of those without economic power. This group must                   uncertainty that results from the unpredictability of
be defended against any forms of discrimination                    crises. The presence and operation of decision mak-
since they are the least articulate and in many cases              ing processes that are transparent and open to dia-
have the poorest access to sources of remedy.                      logue, including the right to hold the government
                                                                   accountable for its actions, promotes good govern-
The challenge of development in Kenya is the crea-                 ance. The guarantee of an impartial hearing by an
tion of a society in which people have the right to                efficient judiciary is necessary if the laws in the stat-
participate in the social, economic and political de-              ute books are to make sense. The Government’s strat-
cisions that affect their lives, in other words a rights-          egies for strengthening institutions such as the Kenya
centred perspective. Enabling individuals to broaden               Anti-Corruption Authority (KACA) and the Standing
their choices, to lead a long and healthy life, to ac-             Committee on Human Rights for the control and eradi-
quire knowledge and gain access to the resources                   cation of corruption and respect of human rights
necessary for a decent living, is the hallmark of                  should provide benefits to the non-quantitative char-
rights-based development. These are as important                   acter of poverty reduction by ensuring that justice is
to mental well-being as the provision of education                 available to all. They should also ensure that the
and health services or better housing are to enhanc-               rights of the most vulnerable are not jeopardized but
ing physical well-being. A critical task for policy                are instead jealously guarded.




7   Notable among these are: the International Covenant on Civil and Political Rights (1966); the Convention on the Elimination of
    All Forms of Discrimination Against Women (1979); the Convention on the Rights of the Child (1989); the Convention Against
    Torture and other Cruel, Inhuman or Degrading Treatment or Punishment (1984); the Fourth International Conference on Women,
    Beijing, 1995).



                                                                                                                                     13
     III. National Situation in Relation to Global
          Conferences

     (a)      Key performance targets                                   goals of the World Summit for Children. The mater-
                                                                        nal mortality rate value is expressed as a range be-
     One of the key uses of the CCA is to facilitate coun-              cause Kenya has not managed to conduct a valid
     try-level follow-up to United Nations conferences and              survey of this variable. Nevertheless, curbing ma-
     declarations and support for their implementation.                 ternal mortality is crucial as it reflects not only
     Kenya has participated in major international con-                 women’s access to and use of essential health care
     ferences 8 and has made efforts to implement the                   services during pregnancy and childbirth but also
     declarations emanating from them. These confer-                    the broader underlying socio-economic factors in-
     ences, including the World Conference on Education                 cluding the general health and nutritional status of
     for All in 1990, have provided Kenya with an oppor-                women and access to reproductive health and care
     tunity to embark on a process of re-examining its                  services such as family planning. It also includes
     performance with regard to its obligations under the               access to resources and the educational, social and
     terms of the declarations and commitments of the                   economic status. The adverse trends for infant, child
     various summits and conferences. This relates, in-                 and maternal mortality rates, as can be discerned
     ter alia, to the provision of opportunities for sustain-           from the above statistics, as well as the declining
     able economic growth, creation of employment op-                   life expectancy in the last decade, present strong
     portunities for her citizens, reduction of inequali-               indications of a general deterioration in health care.
     ties in income distribution, tackling poverty and pro-             In addition, the HIV/AIDS epidemic will adversely
     moting good governance. Government action relat-                   affect the overall health status and mortality in the
     ing to these issues is articulated in various policy               coming years.
     statements and documents. However, the success
     with which the Government action has been able to                  (ii)     Reproductive health
     articulate the needs and values of its citizens in line
     with these obligations has been mitigated. Some                    Addressing the key strategies for improving the
     examples of areas of action are outlined in the para-              sexual and reproductive health of the population of
     graphs below to show the status and the trends.                    Kenya, with particular emphasis on the provision of
                                                                        quality and comprehensive reproductive health serv-
     (i)       Mortality and morbidity                                  ices to under-served rural communities, has been
                                                                        the primary objective of the Government and its
     The three mortality rates as recorded in 1998 are                  development partners. The promotion of family plan-
     as follows: maternal mortality rate (590-650 per                   ning, i.e., making decisions regarding the number
     100,000); under five mortality rate (105 per 1,000)                and timing of children, is a key outcome of the In-
     and infant mortality rate (71 per 1,000). All three                ternational Conference on Population and Develop-
     show significant deterioration in relation to the val-             ment. Underlying this is the notion that enabling
     ues recorded in the 1989 Population and Housing                    women to take decisions about reproduction is
     Census, which is the appropriate benchmark for the                 closely related to decision making in other aspects




     8     The key summits under review are the following: the World Summit for Children, New York 1990); the World Conference on
           Education for All (Jomtien, 1990); the United Nations Conference on Environment and Development (Rio de Janeiro, 1992); the
           International Conference on Population and Development (Cairo, 1994); the World Summit on Sustainable Development (Copen-
           hagen, 1995); the Fourth International Conference on Women (Beijing, 1995); the World Food Summit (Rome, 1996); the Second
           United Nations Conference on Human Settlements (HABITAT II, Istanbul, 1996).



14
of their lives and provides them with the prospect       year immunized against measles dropped from 83.8
of realistic alternatives to child-bearing as a means    per cent in 1993 to 76.3 per cent in 2000. Both ru-
of obtaining social status. Over the last nine years     ral and urban areas have suffered similar deterio-
(1989-1998), the prevalence of use of modern con-        rating trends.
traceptive methods has risen from 17.9 per cent to
31.5 per cent which, even if off the benchmark set       (iv)   Water and sanitation
by the International Conference on Population and
Development of “universal access to safe, reliable       With regard to the situation of drinking water and
contraceptive methods”, is nevertheless among the        sanitation as spelt out under the goals of the United
highest in sub-Saharan African countries. The re-        Nations Conference on Environment and Develop-
productive rights of women and the youth, however,       ment, there is a slight improvement in access to
continue to be hindered by tradition and poverty. In     drinking water and a slight deterioration in sanita-
particular, gender-based violence, including tradi-      tion between the 1990s and 2000. In 1989, 48.1 per
tional harmful practices such as female genital mu-      cent of the population had access to safe drinking
tilation, continues to be a major hindrance to the       water while 56.4 per cent had access in the year
empowerment of women.                                    2000. In 1992, 84.1 per cent had access to appro-
                                                         priate sanitary means of human waste disposal while
(iii)   Child health and nutritional status              in 2000, only 79.9 per cent had access. In many ru-
                                                         ral households, people spend the bigger part of the
The goal of the World Summit for Children to re-         day fetching water yet access to safe water is cru-
duce the malnutrition rates of under fives by half by    cial for lowering infant and child mortality. It is also
2000 can be divided into two parameters, one meas-       a good universal indicator of human development in
uring the extent and the other the intensity. In terms   areas such as education, health and nutrition.
of the extent, Kenya has made some progress but is       Viewed against the goals of the World Summit for
yet to achieve the goal. On the other hand, the in-      Children of universal access, Kenya is far from
tensity (as measured by 3 SD), has remained un-          achieving the goal. This calls to question the practi-
changed. In 1993, underweight prevalence (2 SD)          cality of the goals of the World Summit for Children
was 22.3 per cent and 3 SD was 5.7 per cent, stunt-      of universal access to drinking water and sanita-
ing prevalence (2 SD) was 32.7 per cent and 3 SD         tion.
was 12.2 per cent, wasting prevalence (2 SD) was
5.9 per cent and (3 SD) was 1.2 per cent. The 2000       (v)    Gender mainstreaming and empowerment of
values were respectively 17.5, 4.8, 29.3, 12.5, 6 and           women
1.3 per cent. Underlying these trends is the preva-
lence of malnutrition of children which is an indica-    With regard to the mainstreaming of women in de-
tor of rising poverty. Reduction of malnutrition is      cision making in accordance with the declarations
often an end in itself. The use of the underweight       of the Fourth World Congress of Women and the
and stunting prevalence serves primarily to indicate     Convention on Eradication of All Forms of Discrimi-
progress in improving child nutrition, especially        nation Against Women (CEDAW) declarations, there
among the poor who now constitute 53 per cent of         are insufficient data for assessing trends and per-
the population of Kenya.                                 formance. At the special session of the United Na-
                                                         tions General Assembly on Women: Gender Equal-
The goal of the World Summit for Children of attain-     ity, Development and Peace for the Twenty-first Cen-
ing at least 90 per cent immunization coverage for       tury and the International Conference on Popula-
children under one year by 2000 was too ambitious        tion and Development, significant attention was paid
for Kenya. The percentage national immunization          to harmful traditional practices as obstacles to the
coverage rose from 72.8 per cent in 1989 to 78.8         empowerment of women. Some progress has been
per cent in 1993 but by 2000, it had dropped to 53.9     made in Kenya. For example, the female share of
per cent. Even the proportion of children under one      paid non-agricultural employment has been on an




                                                                                                                    15
     upward trend (26.64 per cent in 1996 to 30.43 per        (vi)   Household food security
     cent in 1999). Similarly, the proportion of seats held
     by women in the National Assembly has showed             With regard to of the declaration of the Word Food
     some significant improvement from (1.5 per cent in       Summit on household food security, the trends have
     1992 to 4.1 per cent in 1998). Gains have also been      been largely negative. Food poverty both for the ur-
     made in changing discriminatory laws and policies.       ban and rural areas has been increasing (from 29
     The ratio of girls to boys in secondary education has    per cent in 1994 to 38 per cent in 1997 for the ur-
     shown a slight improvement from 0.88 in 1998 to          ban and 47 per cent to 50 per cent for the rural ar-
     0.89 in 1999. This shows, however, that efforts to       eas). Similarly, the proportion of the urban house-
     ensure equity in the opportunity for boys and girls      hold incomes spent on food among the poorest
     to participate in schooling, though improved, have       quintile increased from 75 per cent in 1994 to 80
     nevertheless not yielded the desired results. The        per cent in 1997. Annex VI provides details of con-
     overall situation still reflects male dominance in       crete follow-up actions by the Government of Kenya
     decision making.                                         for the different summits.




16
IV. Issues of Particular Concern


(a)    Maternal and child health                          rienced shortages of iron and of tetanus toxin vac-
                                                          cine during the six-month period before the survey.
Poverty in Kenya has severely undermined the health       In addition, many facilities also lack the equipment,
status of its people as evidenced by the limited re-      supplies and medicines for handling obstetric com-
sources available for health care. Children and           plications. Moreover, access to health facilities, par-
women are particularly adversely affected judging         ticularly by rural women, is hampered by poverty.
from the deteriorating infant, under five and mater-
nal mortality rates. The following section examines       The absence of skilled birth attendants (57.8 per
these rates in detail.                                    cent of births in 2000) aggravates the situation. In
                                                          the majority of districts in Kenya, more babies are
(i)    Maternal mortality                                 born at home than at health facilities, implying a
                                                          high risk for mothers and children if complications
 The significance of this indicator is that it reflects   occur during delivery. Visits to antenatal clinics are
not only women’s access to and use of essential           inadequate as the clinics are usually far from the
health care services during pregnancy and childbirth      homes of expectant mothers. To achieve sustainable
but also the broader underlying socio-economic fac-       maternal mortality levels it is proposed that the pro-
tors including women’s general health and nutri-          portion of professionally attended deliveries be in-
tional status, access to resources and the educa-         creased from the current 42 per cent to 90 per cent
tional, social and economic status. In Kenya, the         in the year 2010 in accordance with the goals of the
maternal mortality ratio is estimated at between 590      International Conference on Population and Devel-
and 650 but could be higher since no truly repre-         opment.
sentative survey has been conducted to capture the
correct value of this indicator.                          (ii)   Child health

Complications related to pregnancy and childbirth         The results of the 1998 Kenya Demographic and
are among the main contributors to the high mater-        Health Survey indicated that the health status of
nal mortality. Hospital-based studies indicate that       children in Kenya appears to have deteriorated some-
most of these deaths are due to obstetric complica-       what during the mid-1990s following a period of
tions including haemorrhage, sepsis, eclampsia, ob-       steady improvements during the 1980s and early
structed labour and unsafe abortion. Unsafe abor-         1990s. One sign of the deteriorating health status
tion is estimated to cause at least a third of all ma-    was a rise in child mortality levels. At the time of
ternal deaths. Anaemia is also among the most sig-        the 1998 demographic and health survey, the child
nificant causes of maternal deaths although HIV/          mortality rate in Kenya was 112 per 1000 and it
AIDS is increasingly becoming a common cause.             had reached 113 deaths per 1,000 live births in 2000,
                                                          indicating a continued worsening trend over the
According to the recently concluded 1999 Kenya            decade. At this rate, more than 1 in 9 children die
Service Provision Assessment, many facilities are         before reaching their fifth birthday. The worsening
equipped to provide routine antenatal care and man-       health status owing to increasing poverty is largely
age normal deliveries but shortages of basic sup-         responsible for this. Comparison of the 1998 results
plies and drugs limit their ability to provide effec-     with the 1993 survey suggests that mortality levels
tive services. For example, more than a fifth of the      among young children rose by 24 per cent over the
facilities delivering maternal health services expe-      same period.




                                                                                                                    17
     Although the goal of the World Summit for Children       (b)   Disease patterns
     to reduce the infant mortality rate by one third or by
     50 per cent between 1990 and 2000, the rate has          As stated in successive national development plans
     actually been rising. The infant mortality rates for     and government policy documents such as the Kenya
     1997, 1998 and 2000 were 55.4. 56.8 and 74 deaths        Health Policy Framework, the Government is com-
     per 1,000 live births respectively. The goal was to      mitted to improving the health of the population.
     reduce the under five mortality rate by one third or     These policies form the basis for planning and im-
     to 70 per cent between 1990 and 2000. Over the           plementation of health care services. The current
     decade, the under five mortality rate increased from     health policy revolves around two critical areas,
     90.9 deaths per 1,000 live births in 1989 to 105.2       namely the delivery of quality basic health services
     by 1998.                                                 and good nutrition to a growing population and the
                                                              financing and management of services in a way that
     Malnutrition is another factor that contributes to       guarantees their availability, accessibility and
     high child mortality. The Kenya Demographic and          affordability to the vulnerable groups. Since 1994,
     Health Survey found that around a third of children      the Government has embarked on far-reaching re-
     under age five in Kenya are stunted or too small for     forms in the health sector. These reforms empha-
     their age. Stunting reflects a chronic state of mal-     size prevention and treatment of common diseases
     nutrition that can leave children more vulnerable to     and involvement of non-governmental organizations
     life-threatening illnesses. Chronic malnutrition         and the private sector in health care delivery. In an
     among children under five years in Kenya is associ-      attempt to combat common illnesses, the Govern-
     ated with prolonged periods of consumption of in-        ment has also established specific programmes that
     adequate food or food of low nutritional value. Dur-     address conditions and diseases that greatly affect
     ing the last decade, the most vulnerable groups, in-     the health of Kenyans, particularly women and chil-
     cluding women and children, have not had adequate        dren. These programmes include Primary Health
     food with high nutritional value due to poor economic    Care, Maternal Child Health/Family Planning, the
     conditions and unreliable rainfall. The unpredictable    Control of Diarrhoeal Diseases Programme, the Na-
     climatic conditions during the last decade have not      tional Malaria Control Programme and the Expanded
     only seriously reduced the capacity of the people to     Programme on Immunization (KEPI). Diarrhoea has
     produce food but have also negatively affected their     also been identified as one of the most common ill-
     coping mechanisms in times of famine.                    nesses, particularly among children, and there are
                                                              significant efforts to control diarrhoeal diseases in
     In addition to malnutrition, there are other critical    Kenya. The annual incidence of diarrhoea is 3.5 to
     factors that have contributed to the worsening trends    4.6 episodes per child and it is among the top child
     in both infant and under five mortality rates. These     killers. The Control of Diarrhoeal Diseases Pro-
     include the HIV/AIDS epidemic, limited access to         gramme is implemented countrywide and aims at
     basic health services, which include clinics and         reducing mortality and morbidity through improved
     drugs, poor care-providing knowledge of mothers          management. Deaths from diarrhoea have decreased
     and deterioration in the percentage of children cov-     from 14 per cent to 9 per cent. Oral rehydration
     ered by immunization. It should also be noted that       therapy has particularly been emphasized in treat-
     limited access to clean water and adequate sanita-       ing diarrhoeal diseases.
     tion contributed to an increase in both infant and
     child mortality rates. The health of a child relates     National immunization trends demonstrate a severe
     to social hygiene arising from access to clean water     deterioration as shown in chapter III. A comprehen-
     as well as refuse and sewage disposal. Where clean       sive review of KEPI, funded by the United Nations
     water is lacking and disposal of human waste is poor,    Children’s Fund and the World Health Organization
     contagious diseases are common. Child mortality in       (WHO), was conducted in early 1999. Programme
     such a situation tends to rise.                          management, vaccines and cold chain, logistics, in-




18
jection safety, health communication, training, serv-    (c) Access to basic education
ice delivery and programme planning, monitoring
and evaluation were examined. The review revealed        The available data on education suggest that enrol-
that immunization services were being offered to the     ment in basic education has been declining since
majority of children seeking the service. Weaknesses     1990. Gross enrolment rates in the rural areas have
were identified in the areas of cold chain mainte-       deteriorated while those in the urban areas have
nance and vaccine management and supervision. The        improved. The net school enrolment rate deterio-
use of data for planning and setting targets was non-    rated from 80 per cent in 1990 to 76 per cent in
existent at all levels. New KEPI policies had not        1997. This general decline in school enrolment has
been implemented as no training, apart from train-       been shown to be higher in secondary schools than
ing on polio eradication, had taken place over the       in primary schools. The proportion of both boys and
last five years. The findings of the review were used    girls progressing from Form I to Form IV declined
to formulate a new five-year KEPI strategic plan and     spectacularly from around 95 per cent for both in
formed part of the background information for the        1996 to 75 per cent for girls and 78 per cent for
country’s application for the support of the Global      boys in 1999. Analysis of data shows that the fig-
Alliance for Vaccines and Immunization. The appli-       ures dropped from 95 per cent in 1996 to 76 per
cation was approved this year and Kenya will ex-         cent in 1999 for secondary schools. Deterioration
pand KEPI with the introduction of hepatitis B and       in school enrolment rates is also shown to be higher
haemophilus influenza type B vaccines by the end         in the rural areas while urban areas have recorded
of year 2001.                                            a slight improvement. This trend, if continued, will
                                                         undermine efforts to reach the goal of provision of
In general, Kenya has performed poorly in the pro-       basic education for all by the year 2015. The follow-
vision of health services. As a result, the incidence    ing tables show the trends in enrolment and transi-
of common diseases has increased, with malaria           tion rates for boys and girls over the1988-1998 pe-
being one of the most common killers in the country      riod.
because of its high incidence and resistance to some
drugs. The National Malaria Control Programme has        The goal of education for all can be meaningful only
aimed at reducing death and illness from malaria         if quality assurance and quality control are achieved
through effective case management, personal pro-         in the implementation of basic education. It is inter-
tection and vector control. For children, the strat-     esting to note that the ratio of girls to boys in both
egy that is currently being used for this programme      primary and secondary schools has been improving
is the Integrated Management of Childhood Illnesses      despite the low enrolment and retention rates re-
for which health workers are being trained with a        corded between 1990 and 1999. However, the ratio
view to improving implementation. Although the           of girls to boys in secondary schools is still below
Government and non-governmental organ-izations           parity. There are several reasons for the decline in
have collaborated in combating malaria through the       the numbers of both boys and girls in both primary
provision of impregnated mosquito nets and treat-        and secondary schools. One of the major constraints
ment using non-resistant drugs, malaria continues        to education is its high cost. The absence of a clear
to be a major concern. One of the reasons why both       policy to improve enrolment, together with additional
malaria and diarrhoea are difficult to eradicate or      prohibitive costs of education, have contributed to a
control is that both are related to access to adequate   downward trend in the enrolment, retention and
safe drinking water, sanitary disposal of human          completion rates of basic education. Although pri-
waste and environmental hygiene. The high inci-          mary education in Kenya is supposed to be free, there
dence of common diseases can also be explained by        are many costs that parents must meet such as those
other factors that include the poor performance of       of uniforms, books and several levies.
the health system, the cost-sharing policy that has
raised the cost of health care services in an envi-      As a result of the cost-sharing policy, the Govern-
ronment of worsening poverty and the deterioration       ment has reduced subsidies to primary schools. In
of the HIV/AIDS epidemic.                                secondary schools, government subsidies are virtu-



                                                                                                                  19
                                      Table 3: Gross admission rate in primary schools, 1989-1998

                   1989        1990        1991           1992        1993           1994           1995        1996          1997    1998

       Boys        138.4      135.4       129.7           127.1       122.0          123.4          120.5       117.8         117.1   112.0
       Girls       132.1      128.7       122.9           121.2       116.3          117.8          113.9       112.1         111.0   106.6
       Total       135.2      132.1       126.3           124.2       119.2          120.6          117.2       115.0         114.0   109.3

       Source: Economic Survey, various issues; Ministry of Education, Science and Technology, 1999




                                      Table 4: Gross enrolment rate in primary schools, 1989-1998

                   1989       1990         1991           1992        1993           1994           1995        1996          1997    1998

      Boys         107.6      104.0        93.4           92.0        88.9           89.1           87.4            87.3      88.7    89.3
      Girls        103.2       99.6        89.5           90.0        86.7           87.8           86.3            85.5      86.6    88.2
      Total        105.4      101.8        91.4           91.0        87.8           88.5           86.8            86.4      87.7    88.8

      Source: Ministry of Education, Science and Technology, 1999




                                         Table 5: Primary school completion rates, 1988-1998

                   1988       1989        1990          1991      1992        1993      1994          1995           1996     1997    1998

      Boys         47.4       47.9        45.7          46.6      44.7        44.5      44.6          45.0           45.1     46.3    46.4
      Girls        39.6       43.2        40.5          41.6      48.2        42.2      43.0          42.1           43.5     45.8    48.1
      Total        43.6       45.6        43.2          44.1      46.4        43.4      43.4          42.6           44.3     46.1    47.2

      Source: Ministry of Education, Science and Technology, 1999




                                        Table 6: Primary to secondary transition rates 1990-1998

                   1990         1991             1992          1993           1994           1995            1996           1997      1998

      Boys         42.9          45.4            46.9          41.8           43.2           45.4            46.0           47.3      46.4
      Girls        39.4          43.7            45.0          35.0           42.1           43.9            44.3           44.5      43.1
      Total        41.3          44.6            46.0          38.4           42.7           44.7            45.2           44.9      44.8

      Source: Ministry of Education, Science and Technology, 1999




     ally non-existent and parents have to bear most of                      burden of the cost of education. In the face of com-
     the costs of running the schools. The very limited                      peting priorities, the top priority of the families is to
     places at tertiary institutions have made it impera-                    stay alive rather than send their children to school.
     tive for parents to spend money to secure good pri-                     The overall poverty in both rural and urban areas
     mary and secondary education for their children. It                     has rendered education inaccessible to a large pro-
     is important to note that the policies of the Govern-                   portion of the population. This is a major cause of
     ment are supportive of education for all. However,                      under-enrolment or non-enrolment. This, coupled
     provision of adequate resources, which should be                        with the impact of the HIV/AIDS epidemic through-
     commensurate with policy implementation, is lack-                       out the country has aggravated the situation. Juve-
     ing. Large numbers of children are out of school ei-                    niles have been called upon to supplement family
     ther because they have never enrolled or because                        income and in cases where parents are invalid or
     they have dropped out. Households in arid districts,                    dead, they have become heads of households and
     where 80 per cent of the population depends on re-                      sole breadwinners. This has generally led to low
     lief food as a result of drought, famine and cattle                     retention rates in areas with a high HIV/AIDS preva-
     rustling, find it extremely difficult to cope with the                  lence.



20
Internal displacement can directly disrupt education      enrolment has declined even in areas close to Nai-
through homelessness. Insecurity in some parts of         robi and other industrial towns.
the country such as the North-Eastern and Rift Val-
ley provinces has forced parents to withdraw chil-        (d)     HIV/AIDS
dren from school. In the recent past, more than
400,000 Kenyans have been dislocated. This has            In response to the growing epidemic, the Kenya Gov-
rendered them insecure and landless and robbed            ernment in 1999 declared HIV/AIDS a national dis-
them of their livelihood. The need for family labour      aster and set up the National HIV/AIDS Control
is another factor that has affected the education of      Council (NACC) to develop strategies for control-
children. The data analyzed shows that there is an        ling the spread of HIV/AIDS. Earlier, in 1997, the
increase in child labour as poor families struggle to     Government had adopted Sessional Paper no. 4 that
raise their incomes. Degradation of natural re-           had made recommendations for advocacy and policy
sources such as forests and water resources forces        formulation and implementation. The 1999 esti-
families to spend longer periods looking for fuelwood     mates of HIV/AIDS prevalence in Kenya provided
and water, hence the increased need for child la-         by the Joint United Nations HIV/AIDS Programme
bour. Annexed to the present CCA are maps illus-          2000 report show that 2.1million adults and chil-
trating the above phenomenon.                             dren were HIV positive and that 70 per cent of this
                                                          population was aged between 14 and 25 years. The
Several socio-cultural factors underlie the status of     1997 and 1999 estimates disaggregated by gender
school enrolment. Factors that are more specific to       and age are presented in the table below:
the enrolment of girls include teenage pregnancies,
early marriage, female genital mutilation, distance
from school and household chores. Stereotypes, for          Table 7: Estimates of HIV infection by gender and age,
                                                                                    1997-99
example that girls cannot perform well in science
subjects, have tended to bar girls from getting into       Year/       Adults     Women         Orphans      Estimated
                                                           Category    (14-49)    (14-49)     (cumulative)    deaths
competitive careers which would enable them to
improve their lives and those of their families. The       1997       1,600,000     780,000      440,000     140,000
                                                           1999       2,000,000   1,100,000      730,000     180,000
burden of the costs of education on parents places
girls at a greater disadvantage. If faced with finan-      Source: 1999: Global Epidemics: Joint United Nations HIV/
                                                           AIDS Programme updated report.
cial constraints, parents often opt not to send girls
to school.

Current statistics demonstrate a strong negative          The 2000 NACC Strategic Plan estimates that there
correlation between population density and illiteracy     are 78,000 HIV positive children aged between 0
(see maps). It appears that as land becomes scarcer       and 14 years. The number of AIDS orphans has been
as a consequence of population growth and the sub-        on the increase especially in areas where the epi-
sequent subdivision, families seek to invest in al-       demic is mature and the prevalence rate is high. This
ternative economic activities and this leads to mi-       has led to an increase in child-headed households
gration to urban centres. The growing population in       and, inevitably, an increase in child labour. The phe-
the big urban centres deepens poverty. In Nairobi,        nomenon of child-headed households has resulted
for example, 60 per cent of the population occupies       in an increase in the number of street children and
only 5 per cent of its total residential land. One con-   child prostitution. The AIDS epidemic undermines
sequence of this congestion is the reduction of the       the welfare of the nation by increasing youth and
likelihood of children succeeding in schooling. In        infant mortality, adult mortality and morbidity. Ear-
addition, the deteriorating economic performance          lier, we addressed the issue of the increase in infant
and the subsequent unemployment in the country            and under five mortality but there is also a signifi-
obviously have a negative impact on education. The        cant number of children who are dying in their teens
reduced possibility of getting a well-paid job after      and this constitutes a double loss. On the one hand,
schooling may be one of the reasons why school            there is a decline in the potential workforce, while



                                                                                                                         21
     on the other there is wastage of the scarce savings       ingly being abused in urban areas, notably in Nai-
     that have been invested in the education of those         robi and Mombasa. The use of injectable drugs re-
     who die prior to securing employment.                     mains limited in the country and is not yet consid-
                                                               ered to contribute much to the spread of HIV/AIDS.
     One of the reasons for the large number of HIV in-        Of particular concern as a leading cause of HIV trans-
     fections, particularly among the youth, is the chang-     mission is risky sexual behaviour under the influ-
     ing social environment. The media, part-icularly tel-     ence of drugs or alcohol. Alcohol and drugs make it
     evision, are believed to contribute to early sexual       more difficult for people to negotiate safe sex. In
     activity. However, no data are available to support       this context, efforts to curb drug trafficking need to
     such an assertion. School dropout resulting in child      be complemented by preventive measures targeting
     prostitution is associated with HIV transmission          the youth in particular.
     among youth by increasing the number of infected
     persons and thus starting a vicious circle of HIV         HIV/AIDS causes serious economic stresses. The
     transmission. This, coupled with inadequate infor-        costs of treatment of HIV/AIDS and related illnesses
     mation and lack of appropriate youth friendly re-         are too high in a developing country. On the one hand,
     productive health services and information dissemi-       a big proportion of hospital beds is occupied by HIV/
     nation, undermines efforts to control the spread of       AIDS sufferers while on the other, children are in
     the epidemic.                                             some cases required to stay at home to care for suf-
                                                               ferers who are not hospitalized but are already to
     With regard to adults, high HIV infection is increas-     weak to take care of themselves. As a result of the
     ingly being associated with various cultural prac-        AIDS epidemic, the life expectancy of both males
     tices such as wife inheritance, rape and domestic         and females has been greatly reduced. In 1989, the
     violence which inhibit women from having control          life expectancy of males was 57.7 years. By 1997, it
     over their sexuality. In particular, because many         had fallen to 51. The life expectancy of females in
     cultures give women relatively few rights, the threat     1989 was 69.42years; it had fallen to 53 years by
     of domestic violence easily undermines the capac-         1997. Because of the infectious nature of HIV/AIDS,
     ity of women to utilize knowledge that they have on       the traditional practice of wife inheritance has given
     ways of controlling the spread of AIDS. In some           rise to even greater adult mortality in cases where
     cases, women have the knowledge but are con-              infected husbands have died.
     strained either by cultural, socio-economic or gen-
     der discriminatory practices to lose control over their   It should be noted here that the available data on
     sexual choices, thus exposing them to infection.          HIV/AIDS come from the Sentinel Sites which are
     Many infected mothers inevitably transmit the vi-         located in the high population density areas of west-
     rus to their unborn babies.                               ern and central Kenya. Although the data are not
                                                               necessarily a valid measure of infections at the na-
     Another major issue related to the HIV/AIDS epi-          tional level, they graphically illustrate that the epi-
     demic and which is a major concern is the wide-           demic has been growing. It is particularly worth not-
     spread drug and alcohol abuse in the country. Sub-        ing that both rural and urban infection rates have
     stance abuse appears to have increased in the last        risen over the last five years. However, the actual
     few years, with a wider array of substances being         prevalence rates in arid and semi-arid areas are not
     used by an increasingly younger population. Alco-         known. The paucity of data to provide a good time-
     hol has always been used as an intoxicant, with the       based statement on adult and child infection or sepa-
     worrying appearance in recent years of highly dan-        rate male and female infection constitutes a critical
     gerous, cheap and illegal brews having devastating        gap that needs to be addressed if effective program-
     consequences for health. Drug abuse concerns              ming and planning are to be undertaken. Meanwhile,
     mainly cannabis, khat, glue (consumed particularly        up-to-date surveys have shown that the countrywide
     by street children), psychotropic substances, par-        awareness campaign appears to be successful but
     ticularly mandrax (methaqualone) and ampheta-             there has been no corresponding behavioural change.
     mines. However, heroin and cocaine are also increas-      Many people seem to be conscious of the possibili-



22
ties of sexual transmission of HIV and have fewer         cilities. For example, the landslides caused by the
misconceptions regarding the modes of transmission        1997-98 floods in Nairobi washed away a section of
of AIDS and knowledge of the likely consequences          the main water transmission pipeline to the city resi-
of contracting the disease has been enhanced.             dents, depriving a large section of the city popula-
                                                          tion of drinking water for many days. The landslides
(e)   Increasing frequency and severity of                also silted dams, destroyed power transmission lines
      disasters                                           and parts of the Mombasa Road.

Kenya continues to be exposed to a variety of natu-       c.      Earthquakes and volcanic activity
ral and man-made disasters that pose a threat to          The risks of major earth tremors are not frequent or
human development. Among the most significant             significant disaster concerns in many parts of Kenya.
natural disasters are droughts, wild fires, floods and    However, they occasionally do occur at low seismic
landslides. Earthquakes and volcanic activity are         scales in some areas. Areas that require monitoring
potential risks. The most significant man-made dis-       for seismic activity include the Rift Valley between
asters are civil conflicts and industrial and trans-      Nakuru and Northern Tanzania, the North-East of
port accidents.                                           Mt. Kilimanjaro and Nyanza.

(i)     Natural disasters                                 (ii)   Man-made disasters

a. Drought                                                a. Civil conflicts
Kenya is prone to recurring droughts whose effects        Civil conflicts continue to pose threats in some parts
on food security have become very pronounced in           of the country. Clashes in rural areas and unrest in
recent years. The 1991-92 drought was the worst           towns and cities are caused by ethnic conflicts and
since independence while the 1997-2000 has been           competition for resources such as land and water.
recognized as the worst in the past 40 years. The         An example of this is banditry and cattle rustling,
1997-2000 drought affected the North-Eastern, East-       particularly in the North-Eastern Province.
ern, Rift Valley, Coast and Central provinces. In the
pastoral and agro-pastoral areas, the communities         b. Industrial and transport accidents
suffered livestock losses of between 40 and 60%           Kenya’s modernization and industrialization efforts
and in some cases up to 80%. Wildfires also occur         have led to a variety of disasters such as the in-
during droughts.                                          creasing number of road and rail accidents and the
                                                          discharge of toxic wastes or poor disposal of haz-
b. Floods and landslides                                  ardous wastes.
 Apart from drought, floods are the second most fre-
quent natural disaster in Kenya. Coastal settlements,     c. Technological safety failure
river flood plains and areas around Lake Victoria         Many manufacturing activities and processes in
are particularly vulnerable to floods. Although the       Kenya such as the production of textiles, food
communities in these areas have to some extent            processing, leather tanning and the production of
adapted to the frequency and intensity of flooding,       pharmaceutical and chemical products constitute
they remain immensely vulnerable to the dangers it        potential hazards due to the discharge of industrial
poses. Landslides, closely associated with flooding,      wastes.
also occur frequently in some areas of the country.
Although no data are available to demonstrate the         (f)    Degradation of natural resources
economic damage caused by landslides, it is esti-
mated that communities in the landslide-prone ar-         Kenya is endowed with a wealth of natural resources
eas suffer significant losses from the destruction of     parts of which are legally protected as reserves or
homes, human life and livestock. Landslides also          parks for biodiversity, water and soil conservation.
destroy road and rail infrastructure, electricity power   Due to population growth and industrialization, land
transmission lines, water supply and irrigation fa-       rich in natural resources has increasingly been con-



                                                                                                                   23
     verted for cultivation and construction. Officially              ple live within 5 km of the edge of a forest, i.e. about
     gazetted forests have not been spared from conver-               10 per cent of the total population.
     sion and many others have degenerated due to
     overexploitation9 . The increasing population density            Increased poverty is leading to increasing degrada-
     in fragile environments such as Baringo and                      tion of land and biodiversity in rural areas. At the
     Marsabit districts has resulted in serious                       United Nations Conference on Environment and
     desertification. For example, with a rate of loss of             Development in 1992, Kenya signed the Convention
     vegetation cover of 1,626 hectares per year in                   on Biological Diversity. This convention states in
     Baringo, the annual desertification rate is 0.6%. In             Article 6(b), that “each contracting Party shall, in
     Marsabit, the annual desertification rate is 1.3%.               accordance with its particular conditions and capa-
                                                                      bilities, integrate, as far as possible and as appro-
     Forests and woodlands are important sources of                   priate, the conservation and sustainable use of bio-
     economic, social and environmental benefits to the               logical diversity into relevant sectoral or cross-
     country, particularly for local communities. The in-             sectoral plans, programmes and policies”. Although
     crease in farming and grazing, fuelwood collection               the National Environment Action Plan has been for-
     and timber harvesting is leading to the irretrievable            mulated, its implementation is hampered by the lack
     loss of indigenous forests in the country. The indig-            of data on trends and appropriate mitigation meas-
     enous closed-canopy forests cover some 1.2 million               ures. Consequently, it is not possible at present to
     hectares and are a critical habitat for wildlife. The            estimate the potential impact of population increase
     forests have an important tourist potential that is              and various socio-economic activities on the natu-
     threatened by the continuing encroachment into                   ral resources of the country11 . In short, the rural
     these areas. The majority of the rural poor depend               poor depend on natural resources for their livelihood
     on the availability of natural resources for their live-         while at the same time they deplete the resources,
     lihood. According to the PRSP, 80 per cent of the                thus undermining their own source of livelihood.
     rural poor depend on agriculture for their livelihood,           Other actors in the process of degradation are pri-
     mostly as subsistence farmers. The latter are largely            vate developers and the Government itself as it al-
     excluded from the national economy due to low in-                locates land to create settlements, housing, offices,
     come levels and lack of legally-owned assets (houses             industries, etc. The urban poor are highly depend-
     and land) that can be used as collateral for bank                ent on their cash income but this income normally
     credit. Subsistence farmers also tend to pay in kind             does not allow economic improvement and since
     (with agricultural produce or livestock) for commu-              many are squatters, their insecure economic situa-
     nal activities or school fees. Those who do not have             tion reduces investment opportunities. Conse-
     long-term security for their agricultural or grazing             quently, they rely on cheap products such as char-
     land do not have any incentive for planting trees                coal for survival.
     and consequently rely on communal or government-
     owned natural resources for satisfying their subsist-            Links with national priorities under the PRSP
     ence needs. In times of hardship (drought, floods,
     wildlife menace and fires), the rural poor will rely             The objective of the CCA was to assess the develop-
     even more on the surrounding natural resources for               ment situation of Kenya in order to identify gaps
     their survival, increasing the pressure to unsustain-            and priorities that deserve new or continued focus
     able levels. Wass10 estimated that 2.9 million peo-              by the United Nations system under the UNDAF. A



     9 Njuguna, P., Mbegera, M., Mbithi D., 1999. Reconnaissance survey of forest blocks in the West and East of the Rift Valley.
       Permanent Presidential Commission on Soil Conservation and Afforestation (PPCSCA) and Matiru, M., 2000 (rev.), Forest cover
       and forest reserves in Kenya: Policy and practice. IUCN Eastern Africa Programme, Forest and Social Perspectives in Conserva-
       tion, Working Paper No. 5.
     10 Wass, P. 1995 (Ed.). Kenya’s Indigenous Forests: Status, Management and Conservation. IUCN Forest Conservation Programme.
     11 Government of Kenya, 1997. National Land Degradation Assessment and Mapping of Kenya. Government of Kenya / Govern-
        ment of the Netherlands / United Nations Environment Programme, Nairobi.



24
close examination of the priorities identified by the          pation and guaranteeing security relates to the broad
CCA in relation to those identified under the PRSP             priority areas of PRSP in the areas of public admin-
reveals a great deal of similarity. There is consider-         istration and public safety, law and order.
able convergence between the PRSP priorities and
the CCA areas of concern. Issues of maternal and               The CCA provides the platform for the United Na-
child health, disease patterns, access to education            tions system to work with the Government and other
and HIV/AIDS relate to the priorities identified by            development partners to ensure that its efforts con-
the PRSP with regard to human resources develop-               tribute to the continuous monitoring and analysis
ment. Similarly, the issues of degradation of natu-            of progress in reducing poverty and in meeting the
ral resources and disaster management are embed-               medium-term targets set by Government in the PRSP
ded in the agriculture and rural development sector            and the long-term targets agreed at global confer-
(see table below). This similarity points to the need          ences. Given this convergence, it would mean that
for adopting common approaches and strategies for              the United Nations must continue to work to
addressing the development problems of Kenya. The              strengthen data collection and fill gaps in critical
discussion on entry points for action in the CCA,              areas whenever they are identified.
namely securing empowerment, broadening partici-




                                Table 8: Links with the national priorities under the PRSP


  PRSP priorities                                        Corresponding CCA issues of particular concern


  Agriculture and rural development                      Degradation of natural resources
                                                         Increasing frequency and severity of disasters


  Human resource development                             Maternal and child health
                                                         Disease patterns
                                                         Access to Basic Education
                                                         HIV/AIDS
  Infrastructure development                             –
  Tourism, trade and industry                            –
  Public safety and law                                  –
  Public administration                                  –
  Information and communication technology               –




                                                                                                                       25
     V. Underlying Problems and Priority Areas for
        Action

     The reasons for the high and increasing incidence          was often noted. The themes also included declin-
     of poverty in Kenya are complex and inter-related.         ing opportunities for improving the livelihood of the
     First, they relate to the lack of opportunities for the    people through access to credit, information and pro-
     poor to improve their livelihoods and have access to       duction skills. These in turn relate to the declining
     basic social services, with special emphasis on the        economic growth due to reduced investor confidence,
     unequal distribution of opportunities to women and         poor governance and the deteriorating infrastruc-
     marginalized groups. Second, they relate to the lack       ture. Increasing opportunities for the poor requires
     of participation and empowerment in decisions that         building up and safeguarding the assets of the poor.
     affect the lives of the people in a variety of political   These assets include human, financial and social
     and social processes. Third, they relate to the ex-        capital and the natural resource base. This will re-
     treme vulnerability of a large proportion of the Ken-      quire the mobilization of savings and investment for
     yan population to the severe disruptions caused by         income growth and ensuring equitable access to
     natural disasters (particularly drought), physical         schools, health care and sanitation, all of which will
     insecurity and the threat and impact of HIV/AIDS.          remain key priorities for many years.
     This was well demonstrated by the outcome of the
     analysis undertaken by each of the six UNDAF theme         (b)   Securing empowerment
     groups, working with partners in the Government
     and in civil society, in their respective areas of fo-     Poverty and inequality disempower people and of-
     cus. Based on the “problem trees” approach, the            ten expose them to discrimination in many aspects
     groups generated themes12 that were closely related.       of life and to additional violations of their rights.
     The themes pointed to similarities in the underly-         The need for empowerment highlights the way that
     ing causes of different problems. While the themes         institutions, particularly State institutions, are un-
     were generally seen as the critical issue, they were       responsive to the concerns of the poor. This sug-
     at times seen as the intermediate causes or the root       gests the need for inclusive decentralization, gen-
     causes of those issues. These problems, however,           der equity and greater participation of women in all
     all relate to the earlier discussion of the dimensions     social, political and economic processes. Lack of ap-
     of poverty and the need for action on at least three       propriate information or knowledge was often cited
     fronts: increased opportunity; securing empower-           as a cause of the analyzed problems. In some in-
     ment; and guaranteeing security. Each of these is-         stances, the problems were aggravated by the fail-
     sues is discussed briefly below.                           ure to consult and involve those with appropriate
                                                                knowledge. Failure to consult or involve particular
     (a)    Expanding opportunities                             communities caused a variety of problems. Partici-
                                                                pation in the diagnosis, design and implementation
     The right of all to the basic necessities of life and      of intervention measures was considered critical.
     the opportunity to advance their well-being is a key       The solution to this problem will require an improved
     theme of global conferences. The lack of opportuni-        political and legal basis for the operations of trans-
     ties for the poor came up many times in the discus-        parent public institutions, the empowerment of com-
     sions by the theme groups. Specific topics included        munities so that they have greater influence over
     declining access to education, health care and other       public resources and services and greater gender
     basic social services. The existence of gender bias        equity. An excellent example of progress in this re-



     12 See annex III(a)



26
gard has been the community management approach                 sponse system, with particular emphasis on deal-
to the targeting and distribution of emergency food             ing with recurring drought. The country has made
aid. The lessons learnt with regard to the benefits             significant progress in initiating a drought manage-
of this approach to both the Government and the                 ment system but a great deal remains to be done.
beneficiaries should be applied to all other long-term          Drought will remain a recurring problem but long-
programmes.                                                     term solutions are required that can reduce the vul-
                                                                nerability of the population living in the arid and
(c)      Guaranteeing security                                  semi-arid areas. Of particular concern in this regard
                                                                are the pastoralists and the need for specific pro-
Security issues also came to the fore in a variety of           grammes to increase the resilience of their sources
ways in the various theme groups. There are a                   of livelihood. Linked to this is the phenomenon of
number of ways in which lack of security exposes a              cross-border refugees that since the 1990s has added
large proportion of Kenyans to devastating shocks               to this vulnerability and thus had a negative impact
that diminish their prospects of extricating them-              on poverty, particularly for women and children who
selves from poverty. Three main areas stand out.                constitute the majority (60-80 per cent). The third
First, lack of security and the threat of conflict in           major cause is the threat and impact of HIV/AIDS,
many of the poorest regions of the country. Second,             one of the most important sources of insecurity for
internal displacements of people resulting from eth-            a growing number of households throughout the
nic clashes, land disputes and forced evictions that            country with devastating consequences for the com-
have affected thousands of Kenyans in recent years              munities and the country at large. HIV/AIDS places
have increased poverty through loss of means of live-           enormous strain on the coping capacity of house-
lihood. Third, the loss of assets and the resulting             holds, communities and public services. Similarly,
inability to reinvest are very serious obstacles to             people with HIV/AIDS face serious threats to their
poverty reduction.                                              human rights (see box below). Reducing the vulner-
                                                                ability of poor households to this type of severe shock
The second area highlighted is the need for an ef-              is a key priority in addressing poverty in the coun-
fective disaster prevention, preparedness and re-               try.




                        Box 2: Respect for human rights - crucial in dealing with HIV/AIDS

      The protection and fulfilment of human rights are essential for an effective response to HIV/AIDS. Respect for
      human rights helps to reduce vulnerability to HIV/AIDS, to ensure that those living with or affected by HIV/AIDS
      live a life of dignity without discrimination and to alleviate the personal and societal impact of HIV infection.
      Conversely, violations of human rights are primary forces in the spread of HIV/AIDS, poverty and deprivation.
      Where people lack access to information about the risks of HIV/AIDS and are denied adequate education,
      prevention efforts are bound to fail and the epidemic will spread more quickly.

      Marginalization and disempowerment of women make them more vulnerable to infection and exacerbate
      the effects of the epidemic. Discrimination against people affected by HIV/AIDS leads to shame, silence and
      denial, fuelling the epidemic. Disrespect for civil and political rights makes society-wide mobilization against
      HIV/AIDs and open dialogue about prevention impossible.

      Source: Human Development Report 2000




                                                                                                                          27
     VI. The Way Forward


     The CCA is intended to provide the United Nations         coming publication of data from the 1999 Popula-
     agencies with analysis and appropriate data for the       tion and Housing Census, it would be appropriate to
     design of the UNDAF. This latter document is the          generate the required tables for future indicators.
     development plan that should involve all the agen-        The lack of sex-disaggregated data is another issue
     cies in the attainment of common goals. The objec-        that is on the agenda of the gender, population and
     tive of the CCA is not to provide that development        development theme group.
     plan or indeed to specifically identify the issues to
     be addressed in a hierarchical order. Nevertheless,       The HIV/AIDS epidemic is a matter of major con-
     it provides a document that focuses attention on          cern. Nevertheless, the dependence on the Sentinel
     critical issues that would appear to make a signifi-      Sites for data is subject to serious statistical defi-
     cant contribution to the attainment of the specified      ciencies and therefore not easily generalizable. It is
     broad goals, in this case, improving broadly defined      necessary to capture age and gender-specific rates
     welfare and poverty reduction. This CCA has ben-          of infection together with results on spatial distri-
     efited from an intensive consultative process to nar-     bution. More important than the gaps in the data
     row down to cross-cutting themes that have given          for the CCA is the need to work with the Govern-
     rise to a selection of issues for deeper analysis. That   ment and development partners to ensure that the
     analysis has indicated ways in which the agencies,        initial work of the CCA contributes to the continu-
     through the theme groups, can now prepare their           ous monitoring and analysis of progress in reducing
     contributions to the UNDAF.                               poverty and in meeting the medium-term targets set
                                                               by the Government in the PRSP and the long-term
     Data gaps were noticed in critical areas and they         targets agreed at the global conferences. Discus-
     should be remedied. Of particular importance was          sions between the Economic and Social Council and
     maternal mortality for which a very large sample is       the United Nations agencies have already been ini-
     required to make it possible to obtain a valid statis-    tiated in this regard.
     tic. A further problem related to data was observed
     with regard to access to primary health care. The         Finally, the CCA and the outcome of the PRSP
     Vulnerability Assessment and Monitoring Unit of the       consultations must be analyzed carefully to ensure
     World Food Programme clearly has the capacity to          their harmonization as the UNDAF theme groups
     provide excellent spatial data and would appear to        review their priorities for action. As in the case of
     be the appropriate focus for generating data since        the original CCA, the work done so far by most of
     the indicator is defined with respect to distance from    the UNDAF theme groups has concentrated on de-
     facilities or public transport. Net school enrolment      veloping closer collaboration among the United Na-
     rates require accurate age data that are often not        tions agencies with relatively little direct interac-
     available. Furthermore, the denominator of these          tion with the Government or other partners. The new
     rates is the eligible population and this has up to       CCA and its harmonization with the PRSP process
     now been generated from assumed rates of growth           should provide the basis for greater interaction in
     from the 1989 population census. With the forth-          this regard.




28
Annex I:          The CCA timetable and management
                  structure

A. THE CCA TIMETABLE

October 1999:   The Kenya Country Committee (KCC) holds a retreat in Mombasa, discusses and agrees
                to revise the CCA for Kenya as a priority activity in the work plan of the Resident
                Coordinator for 2000 building on the lessons learnt from the pilot phase; the CCA/
                UNDAF Advisory Team is requested to prepare a work plan and budget for the activ-
                ity; the team is also asked to prepare the terms of reference for the various players to
                be involved in the process.
January 2000:   A special Kenya Country Committee meeting is convened to discusses the draft work
                plan for the revision of the CCA; a number of recommendations are made for the way
                forward including the management structure, the lead agency formula, consultations
                with the Government, the World Bank and other partners; agreement is reached to
                have CCA become a standing agenda in all subsequent Kenya Country Committee
                meetings; the Advisory Team is further requested to come up with proposals on a
                suitable management structure and funding options for the CCA for review by the
                Kenya Country Committee.
March 2000:     The Kenya Country Committee agrees on the management structure for the CCA in-
                cluding the hiring of a qualified technical consultant to assist in data verification,
                analysis and drafting; the Advisory Team is asked to steer the process in order to
                ensure quality and timely production of results; the Resident Coordinator’s secre-
                tariat is requested to take responsibility for overall coordination.
March 2000:     Meetings are held with the Government and the World Bank to explain the objectives
                and the expected outcome of the CCA and the need for harmony with Government
                strategies and plans, particularly the Poverty Reduction Strategy Paper (PRSP) and
                the Comprehensive Development Framework (CDF). Similar policy level meetings are
                held with key non-governmental organizations and donors; a planned high-level meet-
                ing on CCA involving Permanent Secretaries is postponed as it coincides with a key
                PRSP consultative meeting.
April 2000:     A number of potential partners are contacted with a view to discussing CCA data
                requirements as well as mechanisms of engagement in subsequent CCA consulta-
                tions. A brief aide- mémoire on CCA, including its terms of reference and consultative
                framework is circulated for this purpose.
May 2000:       A senior Kenyan consultant, Mr. Terrence Ryan, is recruited to assist in data verifica-
                tion and analysis; a government letter endorsing the exercise is secured and subse-
                quently shared with all partners; discussions are held with technical staff drawn from
                United Nations agencies as well as the theme groups to explain the indicators and
                assist in providing data or suggestions on their location; these discussions help to
                bring them on board and ensure ultimate ownership of the process and use of the CCA;
                on the recommendation of the Advisory Team, the Kenya Country Committee approves
                the recruitment of a short-term consultant to assist in data collection
June 2000:      The major activity is the collection of quantitative and qualitative data from both United
                Nations and non-United Nations sources, using the global list of indicators as the
                starting point; consultations with agencies and theme groups is finalized; as a result



                                                                                                             29
                       of these consultations, data and indicators relating to poverty are clarified and key
                       data sources such as the Kenya Demographic and Health Survey ; the Human Devel-
                       opment Report; the Welfare Monitoring Survey; the Participatory Poverty Assess-
                       ments and economic surveys, are identified as key data sources.
     July 2000:        A presentation covering the analytical model for the CCA is made to the Kenya Coun-
                       try Committee; the poverty relief focus of the CCA is outlined; the need for the CCA to
                       address both the follow-up to international conventions and summits and the real
                       world’s concern for poverty reduction is discussed and agreed on; the need for the
                       CCA to come up with a set of core measurable indicators that will assist the Govern-
                       ment to track progress and the impact of interventions focused on poverty relief is
                       reiterated.
     July 2000:        A one-day Kenya Country Committee retreat held in Nairobi discusses in detail the
                       outcome of data collection for the CCA and the methodology of the analysis; emerging
                       data gaps and ways of bridging them are also discussed; agreement is reached on the
                       need to involve the theme groups and Inter-Agency Task Forces in the analysis; the
                       Advisory Team is requested to take a lead in this exercise by developing guidelines to
                       assist theme groups in this exercise; it is agreed that the results of the analysis will be
                       input in the overall analysis to be undertaken with the assistance of the consultant.
     August 2000:      Analysis in the CCA using the “problem-tree” approach is undertaken by the theme
                       groups and the Inter-Agency Task Forces mainly in the form of one-day retreats; part-
                       ners drawn from the Government, donors non-governmental organizations and civil
                       society take part in the analysis in respective theme groups; this process ensures
                       broad-based consultations and consensus on the identification of priority issues for
                       attention; facilitation is provided by the Advisory Team and other identified experts;
                       the results of the analysis, largely ‘problem-trees’ with some explanatory notes, are
                       forwarded to the consultant for final analysis.
     September 2000:   Analysis on the basis of the various thematic areas is finalized and final analysis
                       commenced with the help of the Advisory Team and the consultant; an assessment of
                       the analysis exercise is presented to the Kenya Country Committee, including some
                       difficulties encountered and recommendations for the future; the Kenya Country Com-
                       mittee expresses satisfaction with the work done so far.
     October 2000:     A presentation covering the preliminary results of the analysis exercise, including a
                       set of priority areas of attention, is made to the Kenya Country Committee; an overall
                       structure of the CCA is also presented, including types of illustrations to be used
                       (maps, pie charts, graphs, etc); an update on the data sets is also given; it is indicated
                       that some year 2000 observations may be possible from the Multi-Indicator Cluster
                       Survey as well as the preliminary census results if completed by the Central Bureau of
                       Statistics.
     November 2000:    A ‘zero’ draft CCA is circulated, initially to the Advisory Team and subsequently to the
                       Kenya Country Committee for their review and comments; a presentation on the inter-
                       face between the PRSP and the CCA is made to United Nations agencies.
     December 2000:    A Kenya Country Committee retreat reviews the first draft of the CCA and makes
                       recommendations on revision; a substantial input is made by the Food and Agriculture
                       Organization of the United Nations (FAO) and a further draft is produced; agencies are
                       requested to submit their comments prior to the final review by the Advisory Team
                       and approval by the Kenya Country Committee.
     January 2001:     A one-day retreat of the Advisory Team makes a final review of the CCA draft which is
                       presented to the Kenya Country Committee for final review and adoption.




30
February 2001:       A Kenya Country Committee meeting formally adopts the CCA and agrees on a strat-
                     egy for disseminating the CCA to the Government and the International Monetary
                     Fund and the World Bank; the Advisory Team and the secretariat of the Resident
                     Coordinator is requested to follow up on this.
June 2001:           The Kenya Country Committee agrees to publish the CCA prior to a formal launch with
                     partners.

B.   THE MANAGEMENT STRUCTURE OF THE CCA

(a) The role of the Country Team

The Kenya Country Committee, under the leadership of the Resident Coordinator, provided overall guidance
and oversight in the preparation of the CCA, with the responsibility for the day-to-day management del-
egated to the Advisory Team. The latter provided regular (monthly) progress reports to the Kenya Country
Committee. Given that the exercise was carried out in consultation with the Government of Kenya and with
the involvement of other development partners, the Kenya Country Committee provided guidance on this by
discussing and agreeing on suitable mechanisms of involvement and participation. The Kenya Country
Committee discussed and agreed on the funding arrangements for the exercise and approved the nature,
the level and the extent of external assistance in the exercise.

(ii) The role of the Advisory Team and the secretariat
The Advisory Team played an advisory, quality control and oversight role for the exercise, working through
and with the theme groups and the secretariat of the Resident Coordinator; the latter took care of the day-
to-day practical management and logistical affairs also served as a secretariat for assistance with the
documentation. The Advisory Team also drafted the terms of reference for the exercise that specified the
rationale, the objectives, the scope and the roles and responsibilities of the various players involved in the
process. In addition, the team assisted the theme groups in the consultation process by developing guide-
lines to facilitate analysis. More importantly, the Advisory Team was in regular consultation with the con-
sultants to ensure quality of service, adherence to the work plan and timely production of the required
outputs. In addition, they reviewed the CCA draft document to ensure its quality prior to submission to the
Kenya Country Committee for further review




                                                                                                                 31
     Annex II:                      Data collection: rationale, sources and
                                    limitations

     (a)   The rationale                                                tion for measles, etc. were also sought to pro-
                                                                        vide further insights;
     As poverty relief provided the conceptual founda-            (f)   Data on research into health and nutrition
     tion for the CCA, data and indicators that premise                 matters that have yet to be disseminated. This
     on this were sought. Poverty, defined as denial of                 would be important since crop yields and vul-
     something vital to one’s human dignity, in either                  nerability to human, livestock or plant diseases
     absolute or relative terms, provided the basis for                 affect the security of the poor;
     identification of appropriate quantitative and quali-        (g)   In all the above, any studies, either at case
     tative data. The following were some of the key cat-               study level or sample surveys, since January
     egories formulated to assist in data collection:                   1994, were thought useful, particularly since
     (a) Status of the dimensions of poverty, be they spa-              it would be important to have at least a few
           tial, e.g., the arid and semi-arid areas, urban,             observations on particular variables so as to
           coastal; gender or age-group specific, e.g., women           understand the dynamics and trends. The main
           and children, etc; or characteristic-specific, e.g.,         aim was to collect qualitative, quantitative and
           physically or mentally handi-capped, etc.;                   time-series data and case studies, preferably
     (b) The dimensions of poverty could not be re-                     those easily amenable to causal analysis.
           stricted to income or nutrition. It was thought
           that they should also include such things as           (b) The data collection process
           shelter, access to education, water, health,
           energy; seasonal characteristics of a commu-           Following initial consultations and briefing to part-
           nity with respect to water or fuelwood, etc. In        ners, a short consultancy was commissioned to as-
           shelter, access to toilets and sewage was              sist in data collection. This involved visits to the
           thought be a good example;                             various offices of the partners (the Government,
     (c) Any studies on those communities that appear             donors, non-governmental organizations and re-
           to be poor. Many of these communities have             search institutions) and collection of data relevant
           maintained their cultural cohesion because             to the CCA. It also involved seeking access to the
           they provide security to their members. These          various databases run by the partners and collec-
           communities may be highly of vulnerable due            tion of materials or documents, electronically on
           to the pressures related to the cost of modern         disks or in hard copy, relevant to the CCA. Where
           medicines and veterinary services;                     data gaps were reported, this was carefully docu-
     (d) Studies relating to people who have grown up             mented for follow-up.
           in the urban centres without any rural base; it
           was expected that these could have different           Once collected, the data was compiled using simple
           poverty experiences to those who are recent            computer-based applications, thus generating the re-
           or first-generation migrants. The question of          quired correlation and cross-tabulations. Similarly,
           street children and AIDS-related orphans was           a list of focal points from each organization or gov-
           thought to be important;                               ernment department from which data had been col-
     (e) Data on short-term and long-term health as-              lected was compiled. At the end of the data collec-
           sist in understanding the extent to which dis-         tion exercise, relevant disaggregations (age, sex,
           eases such as malaria and tuberculosis, etc.           spatial, etc) were computed according to the vari-
           have become more lethal with the spread of             ous parameters to show the status and the trends.
           HIV/AIDS. Weight for age and height for age            This was vital in the analysis exercise that then fol-
           parameters as well as information on inocula-          lowed.



32
(c) Data sources and limitations                        wide variety of international institutions. The CCA
                                                        Guidelines suggest, however, that country-specific
The 1998 CCA provided an indicator table and a set      indicators can be included where appropriate.
of statistics. The present CCA benefited from that
information. In addition, data were drawn from the      The sources of data, which are dealt with in annex
1997 Welfare Monitoring Survey and the 1998 De-         IV, also limit the numbers actually available. With
mographic and Health Survey. The Multi-Indicator        regard to some parameters such as net educational
Cluster Survey (MICS) conducted in late 2000 also       enrolment, the data are of a poorer quality than those
provided a number of up-to-date observations and,       on gross educational enrolment and both are there-
where possible, the preliminary results of the 1999     fore shown. Similarly, access to primary health care
Population and Housing Census. As the results of        is shown without certainty that this number truly
the 1999 census were not expected by end of the         represents the required indicator. Although data
CCA exercise, the estimated population data in the      exist on access to health facilities, they are more
indicator table are from the analytical volumes of      broadly defined than those required for primary
the 1989 Population and Housing Census. The esti-       health care.
mates have been made using the medium fertility
forecast and the estimated impact of HIV/AIDS at        The quality of the data is a major concern, particu-
that time. The lack of population data has also meant   larly where disaggregations are involved. While fe-
that the problems of urbanization that are one of       male/male disaggregations do not pose particular
the target areas of analysis have not benefited from    problems, those between rural and urban
the most recent insights.                               populations pose problems of interpretation. Urban
                                                        centres in Kenya are those permanent settlements
The table on indicators appears as annex V of the       that have more than 2,000 people. This definition
present CCA. Where different sources gave differ-       has significant limitations since town boundaries are
ent values for the same indicator variable, personal    not contiguous with settlement boundaries and many
judgement has been used to record the one that con-     legally defined urban areas are surrounded by dense
sidered as the more valid number. The first meas-       peri-urban settlements. Enumerators are not always
ure of the validity was the way in which the variable   consistent across different sample surveys in their
was generated - National Census, large and sample       treatment of these areas.
survey, small sample survey, large non-randomized
survey, etc. The second criterion was whether the       The World Bank and the African Development Bank
observation conformed to the hypothesized trend         both issue annual publications which have indica-
relative to earlier and valid numbers.                  tors covering many of the listed variables. Although
                                                        they indicate in broad outline where their data come
Although there were many suggestions for non-quan-      from, the numbers cannot, in fact, be traced back to
tifiable indicators with respect to rights, it proved   the original source since the references are usually
impossible to get up-to-date data on such things as     to a complete publication. Nevertheless, where num-
gender and age-specific prison populations and cases    bers are missing from the other reliable sources but
before the courts. Data on crimes as a proxy for a      available in the World Bank of African Development
deteriorating environment with respect to rights has    Bank, these have been used. In some cases, those
been introduced. However, it lacks precision.           values indicate a significant discontinuity from one
                                                        year to another. Sometimes, these sources also fail
(d) Establishing the CCA set of indicators              to give a specific year of reference; they give a cer-
                                                        tain range of years or an unspecified “most recent
The CCA Guidelines establish a set of indicators that   year”. This makes it very difficult to use such num-
are generally acceptable for comparative purposes       bers for establishing a rate of change over a period
at the global level. These have been agreed on by a     of time .




                                                                                                                 33
     Many United Nations agencies publish annual or pe-       nel data, which are already from a non-representa-
     riodic documents that contain a large set of indica-     tive sample, must be treated with care. The Geneva-
     tors specific to their area of interest. Good examples   based United Nations Office of the High Commis-
     include the World Health Organization, the United        sioner for Human Rights was consulted in the quest
     Nations Children’s Fund or UNEP. Only those indica-      for possible indicators to reflect the status and trends
     tors specifically needed are recorded in the present     in the areas of governance and human rights. A use-
     CCA. In the particular case of HIV/AIDS, the Senti-      ful response nevertheless failed to generate indica-
     nel data have been used. In view of the important        tors that could be used in the CCA. For the complete
     discovery that only 8 per cent of the population have    status and trend table for Kenya’s CCA indicators,
     in fact been tested for AIDS (MICS 2000), the Senti-     reference should be to the indicator table provided.




34
Annex III (a):                          The CCA consultative process, list of
                                        participants and affiliation

(a)    Consultations with the Government                           (ii)      Consultations at the level of United Nations
       and other partners                                                    agencies and theme groups13

As part of the launch of the CCA exercise in Kenya,                On the part of the United Nations, the various agen-
the United Nations Resident Coordinator met with                   cies participated actively in the implement-ation of
the Head of the Public Service and Secretary to the                the CCA in accordance with the CCA Guidelines that
Cabinet to brief him on the objectives and expected                provided a theoretical basis for the process. Con-
outcomes of the CCA. At that meeting, the Resident                 sultations took place at the level of the UNDAF
Coordinator solicited the Government’s support to                  theme groups and individual agencies. The United
and participation in the CCA exercise. Government                  Nations agencies and theme groups provided a syn-
support would lend authority to the process and the                thesis of the most important developments and the
product. The response of the Government was posi-                  key future priorities in their areas of expertise. The
tive. Subsequent discussions held with the Ministry                CCA technical consultant working with the CCA/
of Finance helped to further establish a link between              UNDAF Advisory Team provided the overall frame-
the CCA and the poverty reduction strategies being                 work within which the consultations were conducted
pursued by the Government. The latter would pro-                   in a concise and thorough manner. In addition, these
vide the former with a set of measurable indicators                discussions provided the way forward for the types
to assist in measuring the impact of poverty relief                of data available, their location and modalities for
interventions.                                                     collecting it. This ensured that data relevant to the
                                                                   United Nations conferences and conventions were
In addition, the Government demonstrated its sup-                  collected, collated and analyzed.
port to the exercise by sending out a memorandum,
signed by the Permanent Secretary, Ministry of Fi-                 (iii)     Consultations at the analysis level
nance and Planning, to its key departments. He re-
quested them not only to participate in the exercise                Following the conclusion of the data collection and
by providing data on indicators, but also to desig-                the preliminary analysis, a one-day retreat of the
nate relevant focal points. This memorandum was                    United Nations heads of agencies was held where
also copied to donors, non-governmental organiza-                  key problems and data gaps were highlighted. It was
tions and civil society organizations with a similar               agreed that a careful process of analysis be under-
mission. This facilitated the subsequent data col-                 taken to understand the underlying causes of the
lection as it was easy to access data from key                     key problems identified which would assist in the
sources in the Government such as the Central Bu-                  preparation of the final CCA analysis. The Kenya
reau of Statistics (CBS) and from donors, research                 Country Committee decided that the theme groups
institutions and non-governmental organizations.                   would undertake analysis in their respective areas




13 A list of theme group and agency participants in given as annex III (b)



                                                                                                                            35
     in support of the analytical work of the CCA con-                        disaggregated data where they were available.
     sultant. Based on the experience from the pilot phase                    As an input to the analysis, the Advisory Team
     that had demonstrated weaknesses in the areas of                         made a presentation on CCA assessment and
     consultation, analysis and priority setting, an inno-                    analysis15 . The CCA consultant gave made in-
     vative approach was adopted which proceeded as                           troductory remarks on the data collected in the
     follows:                                                                 various areas;
                                                                        (c)   In deciding which problems to analyze, the
     (a)   The theme groups co-opted relevant partners                        theme groups looked for “red flags” in the data
           (the Government, non-governmental organiza-                        - where the indicator was either below the glo-
           tions, donors, the Bretton Woods Institutions                      bal objective or showed a disturbing trend. As
           etc14 .) to assist in the analysis of the priority                 it was not possible to analyze all the problems
           problems in their area of competence. A                            identified, prioritization was crucial. This in-
           sectoral/thematic criterion was used in the                        volved the selection of a limited number of pri-
           selection of the partners in addition to the ex-                   ority issues as a basis for identifying key is-
           isting partnership arrangements. In order to                       sues for the UNDAF. A number of groups used
           ensure a manageable process, the number of                         additional data drawn from other sources;
           partners involved was mostly limited though                  (d)   Following the analysis, the theme groups pre-
           care was taken to ensure a fair balance of ex-                     sented completed “problem trees” demonstrat-
           pertise and gender. Theme Chairs of the groups                     ing immediate, underlying and basis or struc-
           ensured a full quorum of their respective theme                    tural causes of problems. In many cases, the
           groups as well as consultation with partners                       “problem trees” were accompanied with brief
           for the analysis;                                                  explanatory notes and a summary showing the
     (b)   Based on the data available and the assess-                        analysis process and a list of all partners
           ment undertaken by the CCA consultant, the                         (United Nations and non-United Nations) in-
           theme groups identified a limited number of                        volved. The list of the participants is given as
           priority issues in their respective areas and                      Annex III (b);
           analyzed them to bring out the underlying                    (e)   A total of 29 priority problems were identified
           causes, using the “problem tree” approach as                       in this analysis. Although many of the prob-
           suggested in the CCA Guidelines. To assist in                      lems can fit into more than one category, they
           this work, the theme groups were provided                          have been grouped as follows to give an idea
           with a CCA indicator table for Kenya and                           of the nature of the underlying reasons why
                                                                              many of the indicators are deteriorating:




     14 This presentation is provided by the United Nations Staff College and is part of a standardized toolkit for CCA/UNDAF Resource
        Persons for field level training.
     15 Theme groups not only reflect the current work of the United Nations system in Kenya, but also the key areas where assistance
        by the United Nations system can make an impact



36
Problems of opportunity        Problems of empowerment                  Problems of security


Increasing poverty             Non-performing governance institutions   Rising HIV/AIDS prevalence


Increasing poverty             Lack of domestication of international   Increase in orphans
                               legal instruments

Increasing food poverty        Inadequate participation of              Inadequate institutional capacity
                               citizens in decision making              for disaster management



Low enrolment of girls in      Inadequate community empowerment         Lack of resources for disaster
education                                                               response

Increase in school dropouts                                             Lack of information on disasters


Deteriorating maternal and                                              Severe and deteriorating resource
child health indicators                                                 constraints for dealing with
                                                                        disasters


Inadequate access to
adequate sanitation


Poor access to basic health


Increase in infant and
under 5 mortality


Gender inequality


Low and declining foreign
direct investment


Declining per capita GDP


Decreasing share of exports
in GDP


Poor integration between
development and conservation


Unsustainable use of natural
resources




                                                                                                            37
38
     Annex III (b): List of participants in the CCA
     I.     United Nations agencies and theme groups

     Agency/theme group      Date/form of consultation     Persons involved                                 Notes on input/outcome

     UNICEF                 10 May 2000 (Meeting)        Mr. M. Gotink ; Ms. H. Eversole; Mr. A. Mugenda;   Clarification on health/nutrition indicators;
                                                         Mr. Fred Donde; Mr. J. Muita; Mr. T. Ryan;         documents (e.g DHS) and advise on sources
                                                         Mr. C. Torori; Mr. M. Bagayoko;Mr. T. Ryan;        of relevant data including of relevant Government of
                                                         Mr. B. K’Oyugi                                      Kenya contacts

     UNDP                   11 May 2000 (Meeting)        Mr. M. Nyirongo; Mr. C. Gakahu;                    Discussion on relevant indicators/data sources and
                                                         Ms. E. Oduor-Noah; Ms. G. Okonji;                  links to baseline surveys
                                                         Ms. H. Ibrahim;Mr. T. Ryan; Mr. C. Torori

     WHO                    29 May 2000                  Mr. S. Muziki; Mr. D. Mutie                        Government of Kenya/Ministry of Health contacts;
                                                         Mr. W. Ndegwa; Ms. E. Namai                        sources of relevant data and clarification on
                                                         Mr. C. Torori; Mr. Ryan; Mr. B. K’Oyugi            indicators and logic of the CCA

     UNFPA                  25 May 2000
                            (round-table meeting)        Mr. F. Zama Chi; Mr. I. Sambuli;                   Discussion on relevant indicators and data and
                                                         Mr. A. Mugenda; Mr. C. Torori;                     advise on relevant sources; no prospects for 1999
                                                         Mr. T. Ryan; Mr. B. K’Oyugi                        census data

     UNIFEM                 2 June 2000
                            (round-table meeting)        Mr. L. Dirasse; Dr. J. Kabeberi-Macharia;          Clarification on dissagregation of data (along
                                                         Ms. M. Garling; Mr. C. Torori;                     gender & space); list of relevant documents and
                                                         Mr. T. Ryan; Dr. B. K’Oyugi                        sources of data (non-governmental organizations, Gov-
                                                                                                            ernment of Kenya, etc);

     UNESCO                 5-7 June 2000                Mr. R. Hoft; Mr. A. Aznar; Mr. T. Sankey;          Clarification on indicators; data sources and issues
                            (written memoranda)          Mr. T. Schlueter; Ms. A. Ochanda                   for consideration during analysis
      Agency/theme group    Date/form of consultation       Persons involved                                   Notes on input/outcome

     WFP                   21 June meeting               Mr. R. Wheeler; Mr. C. Torori; Mr. T. Ryan           Discussion on food security and vulnerability analysis;
                                                                                                              possibility of using Vulnerability Assessment Models soft-
                                                                                                              ware for illustrations (maps, charts, etc)

     UNDCP                 28 June (written response)    Mr. John Gathecha                                    List of sources of information and data relating to drug
                                                                                                              abuse and crime prevention

     World Bank            Written Comments              Mr. Lucas Ojiambo                                    Comments and suggested clarifications on the contextual
                                                                                                              and poverty indicators and pointers to data sources

     ILO                   3 July (written response)     Mr. B. Oduor-Otieno                                  Data relating to indicators as per list submitted.

     OHCHR (Geneva)        30 May 2000 (meeting)         Mr. Brian Burdekin (Special Adviser to               Discussion on indicators and data on human rights
                                                         the High Commission for Human Rights                 and good governance; experiences with other
                                                         on National Institutions and Regional                countries; relevant materials sent later
                                                         Arrangements; Ms. E. Oduor-Noah (UNDP);
                                                         Mr. C. Torori (Resident Coordinator’s secretariat)

     Water and             25 May 2000                   Mr. W. Ndegwa (WHO); Mr. F. Donde (UNICEF);          Discussion on indicators and data on water quality
     Environmental                                       Mr. J. Mbuvi (WB); Mr. Kinge (UNHCR)                 and environmental sanitation
     Sanitation Task
     Force(under
     Basic Social
     Services Theme
     Group)

     Rural                 31 May 2000 (first meeting)   Mr. Dan Gustafson (FAO); Ms. Kari Blindheim          Clarification on environmental indicators and
     Development           7 June 2000                   (UNSO); Ms. H. Korsgaard (UNDP);                     sources of relevant information and data; relevant
     and Natural           (follow-up)                   Mr. C. Gakahu (UNDP); A. Abate (FAO);                 documents shared
     ResourcesTheme                                      S. Lacroux (UNCHS); Ms. V. Nyagah (UNSO);
     Group                                               Mr. H. Dal (FAO Consultant)

                                                         Mr. Dan Gustafson (FAO); Ms. Kari Blindheim
                                                         (UNSO); Mr. C. Gakahu (UNDP);




39
40
     Agency/theme group        Date/form of consultation         Persons involved                               Notes on input/outcome

                                                               Ms. J. Kabeberi-Macharia (UNIFEM);
                                                               Mr. Frederick Lyons (RR/RC); Mr. T. Ryan,
                                                               Mr. B. K’Oyugi (Consultants); Mr.;
                                                               C. Torori (Resident Coordinator’s secretariat)

     Governance, Livelihoods   26 June 2000                    Mr. M. Nyirongo (UNDP); Mr. G. Mariki (UNIDO);   Briefing on the CCA and extent of incorporation of
     and Poverty Reduction                                     Mr. B. Oduor-Otieno (ILO/JFA);                   poverty data; discussion on analysis methods
                                                               Ms. E. Oduor-Noah (UNDP);
                                                               Mr. S. Njagi (UNDP); Mr. C. Torori (Resident
                                                               Coordinator’s secretariat);
                                                               Mr. D. Kithakye (UNCHS);
                                                               Mr. J. Mutero (Consultant);
                                                               Mr. J. Gathecha (UNDCP)

     II. Government of Kenya   Form of consultation            Persons involved                                 Input/outputs

     Ministry of Planning      Discussions on objectives       Ms. Monica Aoko; Mr. Obidha                      Advise and relevant contacts given relating to
                               and expected outcomes                                                            departments under the Ministry

     Poverty Eradication       Discussions on objectives and   Mr. P. B. Ondieki                                Discussion on poverty indicators and useful leads
     Unit (Office of the       expected outcomes                                                                given for access to poverty data
     President)

     Office of the Vice        Discussions on gender-          Mrs. J.M Muriuki                                 Information relating to studies on
     President, Ministry       based indicators                Ms. C. Mbaka; Mr J.K Waithaka                    gender; written comments on additional
     of Home Affairs,                                                                                            gender-based indicators
     Heritage and Sports

     Central Bureau of         Written comments by Director    Mr. J. Mani; Ms. Rose Mungai;                    Vital statistics drawn from Eco.Survey 2000, WMS II
     Statistics                                                Mr. Monyoncho; Mr. John Kekovole                 and III; PPAs, etc shared; support throughout the
                                                                                                                exercise; status of the 1999 population census data.

     National Council for      Written comments by the         Mr. S. Bullut                                    Data on population trends (reported that
     Population and            Director; further discussions   Mr. S.M. Thumbi                                  1999 Population Census data
     Agency/theme group       Date/form of consultation           Persons involved                    Notes on input/outcome




     Development             by technical staff                                                       not analyzed yet).

     Ministry of Education   Written comments by discussions    Mr. Titus Katembo; Ms. Julia Nzomo;   Access to vital ands up-to-date statistics relating to
                                                                Elizabeth Wafula                      key education indicators including gender/spatial
                                                                                                      dissagregated enrolment rates, drop-outs, etc

     Ministry of Labour      Written comments from the          Mr. S. M Machuka                      Statistics covering employment/unemployment;
     and Human Resources     Permanent Secretary; follow-up                                           informal sector employment; child labour; urban/
     Development             discussions with technical staff                                         rural force, etc




     Ministry of Health      Written comments from the          Mr. E. Kabuu; Mr. G.M Baltazar;       Data on immunization, malnutrition, contraception
                             Permanent Secretary; discussion    Mr. J.M Kariiuki                      accessed; functioning of the HIF revealed, including
                             about the health information                                              available data
                             system follow-up discussions
                             with technical staff

     Ministry of Home        Written response from              Mrs. J.M Muriuki                      Detailed additional indicators provided covering
     Affairs, Heritage       Commissioner of Social             J.K Waithaka                          women empowerment; social welfare provided; no
     and Sports              Services; follow-up                Ms. Cecilia Mbaka                     relevant data provided, however.
                             discussions with
                             technical staff

     Ministry of Tourism,    Discussions on industry data       Ms. Esther Kinama,                    Knowledge about the objectives and expected
     Trade and Industry                                         Deputy Chief Economist                outcomes of CCA

     Ministry of Energy      Discussions on fuelwood            Mr. Patrick Nyoike;                   Some data relating to fuel consumption
                             consumption, etc                   Mr. John Mecheo




41
42
     Agency/theme group    Date/form of consultation       Persons involved                      Notes on input/outcome




     Ministry of          Discussions on data relating   Mr. Bwonbuna;                           Leads to, and indications of locations relevant
     Agriculture and      to food security,              Ms. Owuor                               data sources
     Rural Development    storage practices

     Ministry of          Written comments from          Mr. G.J Anyango;                        Detailed suggestions provided to consider during
     Environment and      the Permanent Secretary;       Mr. Omwenga;                            analysis; information regarding water quality and
     Natural Resources    follow-up discussions          Mr. J. Ong’uti                          pollution; relevant data accessed through sister
                          with technical personnel                                               departments

     Department of        Roundtable meeting             Mr. H. M. Ali Gula;                     Data on relevant indicators submitted, e.g., forest
     Resource Surveys                                    Mr. Njuguna; Mr. Hesbon                 coverage; biodiversity
     and Remote                                          Mwendwa; Mr. Akotsi
     Sensing (DRSRS)

     Kenya Police         discussions                    Mr. Francis Wachira                     Key indicators shared and relevant data promised but not
                                                                                                 provided

     III. Donors             Form of consultations          Persons involved/key contacts        Input/output

     United Kingdom          Written response from          Ms. Trisha Bebbington;               Clarification on the objectives of CCA and links to
     of Great Britain        Country Programme              Dr. Jason Lane;                      PRSP; discussion on indicators and data; advise on
     and Northern            Manager and                    Mr. Richard Hogg;                    data sources; materials and documents provided;
     Ireland/                designation of                 Mr. T. Ryan; Mr. B. K’Oyugi;         draft paper on analysis of poverty data
     Department for          contact persons                 Mr. C. Torori
     International
     Development

     Sida                    Meeting at Sida                Mr. Tom Anyonge, Programme Officer   Suggestions on location of data relating to water and natu-
                                                                                                 ral resources, etc
     Agency/theme group      Date/form of consultation         Persons involved                 Notes on input/outcome



     Non-governmental          Form of consultations            Persons involved/key contacts   Input/output
     organizations/
     Research Institutions

     KARI                      Written comments from            Mr. C.G Nderitu                 Useful leads, suggestions on sources of relevant data
                               the Director and                                                 and (some generated internally)
                               designation of contact person

     ICIPE                     Written comments on              Mr. J.P.R. Ochieng-Odero        Suggestions on sources of relevant data including
                               the CCA                                                          contact persons

     ILRI                      Written comments                 Mr. Ralph von Kaufmann;         Advise on types and sources of relevant data available
                               from Director and                Mr. P. Kristjanson              and submission of document on planned work on
                               designation of relevant                                          “Poverty Mapping for East Africa”
                               contact person

     AMREF                     Written response                 Mr. Mary Amuyunzu-Nyamongo;     Case studies with useful data and information on
                               followed by meetings             Ms. Anne W. Gichohi;            water and environmental health issues.
                                                                Mr. Gerald K. Rukunga

     Kenya Institute           Meeting between the              Mr. Mwangi Kimenyi              Promise of support in the analysis of data and review
     of Policy Research        Resident Coordinator and                                         of drafts.
     and Analysis              Executive Director,
                               Kenya Institute of
                               Policy Research and
                               Analysis Kenya Institute
                               of Policy Research and
                               Analysis on objectives
                               and expected outcome
                               of the CCA and need
                               for broad-based
                               consultations




43
44
     Annex IV:                              The CCA indicator list - status and trend

         No. Indicator                                                         Year     Value   Year       Value   Year      Value   Year       Value   Year    Value

         A:   Socio-Economic Indicators

              Income-Poverty

     1        Poverty headcount (% of population                                                 1992      50.20   1994      26.5
              < $1/day) (adult equivalent - AE)

     2        Poverty headcount (% of population                                                 1992      44.78   1994      40.25    1997      52.32
              < national poverty line) (AE)

     3        Population in absolute poverty: rural (%) (AE)                                     1992      47.89   1994      46.75    1997      52.93

     3a       Hardcore poverty: rural                                         1980/81    35      1992      37.4                       1997      34.82

     4        Population in absolute poverty: urban (%) (AE)                                     1992      29.29   1994      28.95    1997      49.2

     5        Poverty gap ratio (%) (AE)                                                         1992      19.00   1994      14.93    1997      18.74
                          Rural (AE)                                                             1992      18.37   1994      18.01    1997      19.33
                          Urban (AE)                                                                               1994      9.69     1997      15.67

     6        Poorest fifth’s share of national consumption (%)                                  1992      3.4     1994      5        1997      6.1
                            Income share Lowest 40%                                              1992      10.1    1994      14.7
                            Highest 20%                                                          1992      62.1    1994      50.4
     6a       Gini coefficient (%)                                                               1980/81   50      1992      57.5     1994      44.5

              Food Security and Nutrition                                                                                                                        rural   urban
     7        % of children under 5 suffering from mild underweight (2SD)     1993       22.3    1997      22.3    1998      22.1     2000      22.5     1997    23.5    14.3
              % of children under 5 suffering from severe underweight (3SD)   1993       5.7     1997      4.6     1998      4.8      2000      6.5      1997    4.9     2.3

     8        % of children under 5 suffering from mild stunting (2SD)        1993       32.7    1997      36.9    1998      33.0     2000      36.9
     8a                    Rural (%)                                          1993       34      1997      38.0    1998      34.7     2000      39.8
     8b                    Urban (%)                                          1993       22      1997      29.5    1998      24.7     2000      27.0
              % of children under 5 suffering from severe stunting (3SD)      1993       12.2    1997      17.3    1998      12.7     2000      17.5     1997    18      12.5

     9        % of children under 5 suffering from mild wasting (2SD)         1993       5.9     1997      6.5     1998      6.1      2000      6.0      1997    6.7     4.6
              % of children under 5 suffering from severe wasting (3SD)       1993       1.2     1997      1.6     1998      1.4      2000      1.3      1997    1.6     1.1

     10       % of urban household income spent on food for the
                          Poorest quintile                                                       1992      70.17   1994      74.99    1997      80.51

     11       % of undernourished in total population
                          (No. of undernourished in Kenya 1996-98: 12.2m)                        1979-81   26      1990-92   47       1996-98   43
      No. Indicator                                                       Year   Value   Year      Value     Year   Value     Year   Value     Year       Value



     12   Food poverty: rural (%)                                                        1980/81   66        1992   71.78     1994   47.19     1997        50.65
                     Urban (%)                                                           1992      42.58     1994   29.23     1997   38.29

          Health and Mortality
     13   % of population with access to primary health care services                    1994      9.9                        1998   13.9      1999        42        facility
                                                                                                                                                                     <4km

     14   Estimated HIV adult prevalence rate                                            1994      9.9       1996   11.9      1998   13.9      1997     (WB) adult   11.6
                      Rural                                                              1994      8.9       1996   11.0      1998   13.0       child      0.52
                      Urban                                                              1994      14.5      1996   16.3      1998   18.1
     15   HIV prevalence in pregnant women under 25 who receive
          Antenatal care in cities/major urban areas

     16   Infant mortality rate (per 1000 live births)                                   1989      58.6      1993   62.5      1998   70.7
                       Rural                                                             1989      58.9      1993   64.9      1998   73.8
                       Urban                                                             1989      56.8      1993   45.5      1998   55.4
                       Male                                                              1989      63.0      1993   66.4      1998   74.5
                       Female                                                            1989      54.3      1993   58.6      1998   66.8

     17   Under 5 mortality rate (per 1000 live births)                                  1989      90.9      1993   93.2      1998   105.2
                      Rural                                                              1989      91.2      1993   95.6      1998   108.6
                      Urban                                                              1989      89.0      1993   75.4      1998   88.3
                      Male                                                               1989      96.1      1993   97.1      1998   107.8
                      Female                                                             1989      85.7      1993   89.3      1998   102.6

          Reproductive Health

     18   Maternal mortality ratio (per 100,000)                                         1993      150-300   1994   365-489   1998   590-650

     19   % of births attended by skilled health personnel              1993      45     1997      47.23     1998   44.3      2000   42.4      1989        50
                        Rural                                                            1997      41.87                      2000   34.1
                        Urban                                                            1997      80.82                      2000   63.5

     20   Contraceptive prevalence rate (Modern methods use %)                           1989      17.9      1993   27.30     1998   31.50

          Child Health and Welfare

     21   % of 1 year old children immunized against measles            1993      84     1997      81.36     1998   79.2      2000   76.3      1989        78.0
                       Urban                                                             1997      80.1                       2000   74.0
                       Rural                                                             1997      88.3                       2000   83.8
                       - National Complete immunization coverage (%)                     1989      72.8      1993   78.7      1998   65.4
                       Urban                                                             1989      82.1      1993   80.9      1998   70.5
                       Rural                                                             1989      71.5      1993   78.3      1998   64.2




45
46
      No. Indicator                                                     Year     Value   Year          Value   Year         Value    Year    Value        Year      Value



     22    % of children <age 15 who are working                                          1989         30                            1998    40

           Education
     23    Attendance ratio in primary schools (Boys/Girls)                               1995         1.02    1997          1.03    1999    1.04
           Net enrolment in primary schools                            1990        80     1993         78      1997          76.51   2000    83            1997      2000
                      Urban                                                               1992         71.71   1997          78      2000    83.2          male      75.5   82.7
                      Rural                                                               1992         74.40   1997          76.27   2000    82.9          female    77.4   83.3
                      Gross enrolment in primary schools               1980        91     1990         95      1993          91      1997    94.47
                      Urban                                                               1992         82.03                         1997    89.34
                      Male                                                                1992         82.61                         1997    89.23
                      Female                                                              1992         81.49                         1997    89.25
                      Rural                                                               1992         95.39                         1997    95
                      Male                                                                1992         96.51                         1997    96.02
                      Female                                                              1992         94.25                         1997    93.98

     24a   % of pupils starting std 1 who reach std 5                                                                                                                       1999   73.14
                         Male                                                             1980         60      1997          70.2    1999    70.88
                         Female                                                           1980         62      1997          75.01   1999    75.56

     24b   % Form I students reaching Form IV
                        Male                                                                           1996    95.78         1998    85.75   1999          77.97
                        Female                                                                         1996    94.94         1998    83.07   1999          75.09

     25    Adult (reading) literacy rate (%) (6+)
                        Total                                          1980/81     47     1988 (10+)   54.3    1994 (self report)    74.8    2000 (15+)    79.7
                        Male                                           1980/81     61     1988 (10+)   64.2    1994 (self report)    82.8    2000 (15+)    84.2
                         Female                                        1980/81     38     1988 (10+)   47.2    1994 (self report)    67.4    2000 (15+)    75.9

     26    Literacy rate of 15-25 year olds (%)                                           1988         82.4                          2000    86.2

           Gender Equality and Women’s Empowerment
     27    Ratio of girls to boys in secondary education                                  1996         0.87    1998          0.88    1999    0.89

     28    Female share (%) of paid employment - non agricultural                         1995         26.64   1997          29.65   1999    30.43

     29    % of seats held by women in national government
                        Including parliament
                        National Assembly                                                 1988         1.5     1992          3.5     1998    4.1
                        Local Authorities                                                 1988         2.4     1992          2.7     1998    8.1
                        Diplomatic/Administrative services                                1992         21.1    1994          22.1    1998    24.6
                        Sen.Asst.Sec and above incl. Ambassadoresses                      1992         13.6    1994          15.9    1998    18.3
                        Judicial services                                                 1994         25.9    1996          26.9    1998    30.6
     No. Indicator                                               Year   Value    Year    Value    Year   Value    Year   Value    Year    Value



          Environment

     30   Carbon dioxide emissions (mt per capita)                                1990    0.2                     1996    0.2

     31   Biodiversity: Land area protected (%)                                   1996    6.1     1999    8

     32   GDP per unit of formal sector energy use (US$/kg)                       1995    0.47    1997    0.46    1999    0.48

     33   Arable land per capita (Ha)                                             1995    0.41    1997    0.38    1999    0.36

     34   % change in sq Km of forest land in past 10 years
                      - Forest plantation area (‘000 Ha)                          1995    160     1997    152.6   1999    141.9

     35   % of population relying on traditional energy use
                      - Firewood and charcoal                                     1994    85.4    1997    81.57
                      Rural                                                       1994    97.3    1997    95.76
                      Urban                                                       1994    39.2    1997    25.88

          Employment and Sustainable Livelihood

     36   Employment to population of working age (%)

     37   Urban unemployment rate (one week reference period)                     1986    16.2
                    Male                                                          1986    11.7
                    Female                                                        1986    24.1

     38   Informal sector employment as % of total employment                     1997    63.58   1998    65.97   1999    68.26

     39   Income share of poorest 40% of population (%)
                                                                                                                  1992    10.1     1994     14.7

     40   Average urban formal wage (K£ annually per head)                        1997    5,629   1998    6,869   1999    7,872

     41   % urban labour force in informal sector
                      Male                                                        1999    53.3
                      Female                                                      1999    46.7

          Housing and Basic Household Amenities

     42   No of persons per room                                1989       4.9                    1994    5.2

     43   % of population with (sustainable) access
          to drinking water (dry season)                        1989       48     1994    43.3    1997    49.7    2000    56.4
           Rural                                                1989       38     1994    30.5    1997    38.47   2000    45.9
           Urban                                                1989       95     1994    93.2    1997    85.67   2000    88.0




47
48
          No. Indicator                                                    Year   Value      Year   Value     Year   Value     Year   Value   Year   Value


     44       % of population with access to adequate sanitation         1992      84        1994   80.4      1997   83.31     2000   79.9
              Rural                                                      1992      81        1994   75.9      1997   81.02     2000   75.5
              Urban                                                      1992      97        1994   97.1      1997   92.36     2000   93.0

              Drug Control and Crime Prevention

     45       No of crimes

              Penal Code Cases per 100,000 population                    1993      338       1995   370       1997   399
              Criminal cases filed in Resident Magistrate’s Court        1991      376,752   1994   428,136   1997   479,520
              Criminal cases filed in High Court                         1991      5,502     1994   17,961    1997   30,420

     46       Area under illegal cultivation of coca, opium, poppy
              And cannabis

     47       Seizures of illicit drugs cannabis (‘000 kg)               1992      3.7       1993   2.7
                              heron (kg)                                 1992      12.7      1993   12.8
                              cocaine (kg)                               1992      0.04      1993   0.03
                              mandrax (‘000 tablets)                     1992      648.7     1993   73.0

     48       Prevalence of drug abuse

     B:       Governance and civil and political rights Indicators
              International Legal Commitments For Human Rights

     49       Status of ratification of, reservations to and reporting
              Obligations under international human rights instruments

     50       Status of follow-up to concluding observations
              of UN Human rights treaty bodies

              Democracy and Participation

     51       Periodicity of free and fair elections                     1988                1992             1997

     52       No. of political parties in elections                      1988      1         1992   10        1997   22

     53       % of registered voters who vote                            1988      queuing   1992   58.9      1997   65.7
                                                                                             &70%

     54       Recognition in law of the right to freedom of

              Expression, association and assembly

     55       No of civil society organizations per 100,000
                            - Women’s groups (per 100,000 women)         1997      558.5     1998   652.5     1999   701.1
      No. Indicator                                                        Year   Value   Year      Value    Year      Value    Year      Value    Year   Value



     56   No. of newspapers per 1,000 people                             1995       30    1997      34       1999      31
     57   No. of radios per 1,000                                        1991       86    1996      108      1997      104
              - No. of radios per 1,000 (new licenced radios sold)       1995       5     1997      6        1999      3

          Administration of Justice

     58   Recognition in law guarantees for independence
          And impartial judiciary and fair trial

     59   Recognition in law of the right to seek judicial Remedies
          against state agencies/officials

          Security of Persons

     60   Recognition in law of the prohibition of gross Violations of
          human rights affecting the security Of person

     C:   Contextual Indicators (economy and demography)

          Economy

     61   GNP per capita (US$)                                                            1993      174.6    1996      330.54   1999      331.87

     62   Decadal growth rate of GNP per capita (US$)                                     1983/93   -40.99   1986/96   -1.72    1989/99   0.89

     63   Share of exports in GDP (%)                                                     1993      41.00    1996      35.3     1999      30.5

     64   Share of FDI inflows in GDP                                                     1995      0.45     1996      0.16     1997      0.22

     65   External debt as % of GNP                                                       1993      87.93    1996      45.65    1998      42.07

     66   Domestic debt as % of GNP                                                       1993      34.28    1996      18.65    1998      23.32

     67   Gross domestic savings as % of GDP                                              1993      12.64    1996      14.76    1999      12.53

     68   % of public expenditure on social services                                      1994      16.80    1995      24.2     1997      29.6

     69   Share of direct poverty reduction
          Government spending

           Total public spending

     70   Incidence of benefits of public expenditure by
          income group, gender and region




49
50
      No. Indicator                                  Year   Value   Year    Value   Year   Value   Year   Value   Year   Value



           Demographics

     71    Total Fertility Rate                                      1989   6.7     1993   5.4     1998   4.7
                           Rural                                     1989   7.1     1993   5.8     1998   5.2
                           Urban                                     1989   4.5     1993   3.4     1998   3.1

     72a   Annual population growth (estimate) (%)                   1993   3.02    1996   2.72    1999   2.44

     73    Estimated Population size (in million)                    1993   26      1996   28.27   1999   30.47

     74    Life expectancy (years) - Males                           1979   52      1989   57.5    1997   51
                       - Females                                     1979   55.1    1989   61.4    1997   53
Annex V:                    The CCA indicator list: references and
                            notes

A:   Socio-economic indicators

Income poverty indicators

No.1
Source:                     World Bank data set
Disaggregated data:         Not available

Nos. 2 – 5
Sources:                    Economic Survey 2000 Tables 15.9 and 15.10
                            Poverty in Kenya (First Report Vol. I and Vol. II) 1998
Disaggregated data:         Provincial level - Table 15.9 Economic Survey 2000
                            District level – 1992 data: Annex Table 3 Poverty in Kenya (First Report Vol.1)
                            1994 data: Annex Table 5 Poverty in Kenya (First Report Vol.1)
                            1997 data: Tables 15.12, 15.14 and Figure 15.1 Economic Survey 2000

No. 6
Source:                     World Bank data set
Disaggregated data:         Not available

Food security and nutrition indicators

Nos. 7 – 9
Sources:                    Kenya Demographic and Health Survey 1993 - Table 9.5
                            Kenya Demographic and Health Survey 1998 - Table 9.5
                            Welfare Monitoring Survey III 1997 unpublished data - Sheet 8
Disaggregated data:         Provided in the Kenya Demographic and Health Survey data sets by sex, rural-
                            urban, region (province), and selected socio-economic variables
                            Provided in the WMS III data set by region (province and district)

No. 10
Source:                     World Bank data set
Disaggregated data:         Not available

No. 11
Sources:                    Economic Survey 2000 Tables 15.8
                            Poverty in Kenya (First Report Vol. I and Vol. II) 1998
Disaggregated data:         Provincial level - Table 15.8 Economic Survey 2000
                            District level – 1994 data: Annex Table 4 Poverty in Kenya (First Report Vol.1)
                            1997 data: Tables 15.11, 15.14 Economic Survey 2000




                                                                                                              51
     Health and mortality indicators

     No. 12
     Data gap

     No. 13
     Sources:                    Economic Survey 2000 Table 3.12
                                 Aids in Kenya Background Projections Impact Interventions Policy (Fifth Edi-
                                 tion) NASCOP 1999 – Appendix Table
     Disaggregated data:         Provided in the NASCOP publication by sentinel sites, rural-urban, children and
                                 total population – Page 7 and Appendix Table.

     No. 14
     Data gap

     Nos. 15 – 16
     Sources:                    Kenya Demographic and Health Survey 1989 - Table
                                 Kenya Demographic and Health Survey 1993 - Table 7.2
                                 Kenya Demographic and Health Survey 1998 - Table 7.2
     Disaggregated data:         Provided in the Kenya Demographic and Health Survey data sets by rural-ur-
                                 ban, region (province), and selected socio-economic variables

     No. 17
     Sources:                    PSRI/UNICEF Maternal Mortality Baseline Survey 1994 (Unpublished Report)
                                 Kenya Demographic and Health Survey 1998 - Table 11.3
     Disaggregated data:         Not available

     No. 18 – 19
     Sources:                    Kenya Demographic and Health Survey 1989 - Tables
                                 Kenya Demographic and Health Survey 1993 - Tables 4.8, 4.9 and 8.5
                                 Kenya Demographic and Health Survey 1998 - Tables 4.6, 4.7 and 8.5
     Disaggregated data:         Provided in the Kenya Demographic and Health Survey DHS data sets by rural-
                                 urban, region (province), and selected socio-economic variables

     Child health and welfare indicators

     No. 20
     Sources:                    Kenya Demographic and Health Survey 1989 - Table
                                 Kenya Demographic and Health Survey 1993 - Table 8.8
                                 Kenya Demographic and Health Survey 1998 - Table 8.8
     Disaggregated data:         Provided in the Kenya Demographic and Health Survey data sets by sex, rural-
                                 urban, region (province), and selected socio-economic variables

     No. 21
     Source:                     World Bank data set
     Disaggregated data:         Not available




52
Education indicators

Nos. 22 – 23
Sources:                  Education statistics – Ministry of Education (Raw data sets for the years 1993
                          to 1998)
                          Economic surveys for the years 1993 to 2000
Disaggregated data:       Available in raw computer data files by class/form, region (district and prov-
                          ince), and gender

No. 24
Sources:                  Welfare Monitoring Survey II (1994) Basic Report 1996 – Table 4.3
                          Fifth Nutrition Survey (1994) Report 1996 – Table 4.6
Disaggregated data:       Available for the year 1994 by gender and region (district and province)

No. 25
Data gap

Gender equality and women’s empowerment indicators

No. 26
Sources:                  Education statistics – Ministry of Education (Raw data sets for the years 1993
                          to 1998)
                          Economic Survey 2000 – Tables 3.5 and 3.6
Disaggregated data:       Available in raw computer data files by class/form and region (district and prov-
                          ince)

No. 27
Source:                   Economic Survey 2000 – Table 4.6
Disaggregated data:       Available only in industry

No. 28
Source:                   Women and Men in Kenya: Facts and Figures 2000 (Draft Report) – Tables 6.2,
                          6.5, 6.6 and 6.7
Disaggregated data:       Available for piplomatic/administrative services by grade

Environment indicators

Nos. 29 – 30
Source:                   World Bank data set
Disaggregated data:       Not available

No. 31
Source:                   Economic Survey 2000 – Table 10.10; and Population projections in Kenya Popu-
                          lation Census 1989 Analytical Report Volume VII
Disaggregated data:       Not available

No. 32
Sources:                  Raw data from DRSRS
                          Statistical Abstract for 1995 and 1998



                                                                                                              53
                                Population projections in Kenya Population Census 1989 Analytical Report Vol-
                                ume VII for the years 1995, 1997 and 1999.
     Disaggregated data:        Only regional (province and district) estimates can be computed from the above
                                sources

     No. 33
     Source:                    Economic Survey 2000 – Table 9.5
     Disaggregated data:        Not available

     No. 34
     Sources:                   Welfare Monitoring Survey II (1994) Basic Report 1996 – Table 8.14
     Disaggregated data:        Available for the year 1994 region (district and province)

     Employment and sustainable livelihood indicators

     Nos. 35 – 36
     Data gap

     No. 37
     Source:                    Economic Survey 2000 – Tables 4.4 and 4.13
     Disaggregated data:        Available only at regional (province) level

     No. 38
     Source:                    World Bank data set
     Disaggregated data:        Not available

     No. 39
     Source:                    Economic Survey 2000 – Tables 4.7 and 4.9
     Disaggregated data:        Not available

     No. 40
     Source:                    National Micro and Small Enterprise Baseline Survey 1999 – Table 4.1 Execu-
                                tive Summary
     Disaggregated data:        Scanty

     Housing and basic household amenities indicators

     No. 41
     Sources:                   Kenya Population Census 1989 Analytical Volume X - Table 3.4
                                Welfare Monitoring Survey II (1994) Basic Report 1996 – Table 8.1
     Disaggregated data:        Available only for the years 1989 and 1994 by region (district and province) and
                                rural-urban

     No 42
     Sources:                   Welfare Monitoring Survey II (1994) Basic Report 1996 – Table 8.4
                                World Bank data set
     Disaggregated data:        Available only for the year 1994 by region (district and province) and rural-
                                urban




54
No. 43
Source:                     Welfare Monitoring Survey II (1994) Basic Report 1996 – Table 8.20
Disaggregated data:         Available only for the year 1994 by region (district and province) and rural-
                            urban

Drug control and crime prevention indicators

No. 44
Source:                     Statistical Abstract 1998 – Tables 227 and 228
Disaggregated data:         Not available

Nos. 45 – 47
Data gap

B.   Governance and Civil and Political Rights Indicators

International legal commitments for human rights indicators
Nos. 48 – 49
Data gap

Democracy and participation Indicators

Nos. 50 – 52
Source:                     1997 Election Report
Disaggregated data:         Scanty

No. 53
Data gap

Nos. 54 - 56
Source:                     Economic Survey 2000 – Tables 3.18, 14.11, 14.12 and Projected Population
                            data
Disaggregated data:         Not available

Administration of justice indicators

Nos. 57 – 58
Data gap

Security of persons indicators

No. 59
Data gap




                                                                                                            55
     C.   Contextual Indicators (Economy and Demography)

     Economy indicators

     Nos. 60 – 66
     Source:                  Ministry of Finance and Planning – unpublished data sets
     Disaggregated data:      Not available

     No. 67
     Source:                  Nganda and Ong’olo 1998 study page 45

     Nos. 68 – 69
     Data gap

     Demographic indicators

     No. 70
     Sources:                 Kenya Demographic and Health Survey 1993 – Tables 3.2, 3.3 and 3.4
                              Kenya Demographic and Health Survey 1998 – Tables 3.2, 3.3 and 3.4
     Disaggregated data:      Provided in the Kenya Demographic and Health Survey data sets by rural-ur-
                              ban, region (province), and selected socio-economic variables

     No. 71
     Source:                  Kenya Population Census 1989 Analytical Report Volume VII on Population
                              Projections – Table 4.3
     Disaggregated data:      Available by region (province and district) and gender

     No. 72
     Sources:                 Kenya population censuses 1979 and 1989
                              World Bank data set for 1997 estimate
     Disaggregated data:      Not available by region for the year1997




56
     Annex VI:                     Kenya’s performance with respect to global conference goals
     Conference Goal               Target                           Indicators and follow-up action by the Government of Kenya
     Income poverty

     Reduced poverty levels        Proportion in extreme poverty    Status: 37.4 per cent of adult equivalent (AE)
                                   in 1990 reduced by 1/2 by 2015   in 1992 were below the absolute hard-core poverty
                                   (World Summit on Sustainable     line. In 1997, 34.8 per cent of AE were below the line.
                                   Development)
                                                                    Actions:
                                                                    •    Formulation and publication of a National Poverty Eradication Plan (NPEP) in 1999 and subsequently the creation of the Poverty
                                                                         Eradication Commission;
                                                                    •    Formulation and publication of a Poverty Reduction Strategy Paper (PRSP) and Mid-Term Expenditure Framework (MTEF) outlining
                                                                         policies, reforms and programmes of the Government to tackle poverty
                                                                    •    Improvement of governance and consultation/stakeholder involvement.
     Food security and nutrition
     Improved child nutrition      Halve severe/moderate            Status: Children under 5 who were severely:
                                   malnutrition among children      5.7% (1993), 6.5% (2000); and mildly underweight:
                                   under 5 of 1990 level by 2000    22.3% (1993), 22.5% (2000).
                                   (World Summit on Sustainable     Actions:
                                   Development/Fourth World         •    Formulation of the Kenya Health Policy Framework Paper (1994);
                                   Conference on Women/World        •    Development of the National Health Sector Strategic Plan (1999-2004);
                                   Summit for Children/World        •    Shift away from curative to preventive/promotional/rural health services;
                                   Food Summit)                     •    Development of home-based care centres;
                                                                    •    Implementation of child care and medical hygiene programmes;
                                                                    •    Improvement of parents’ knowledge and investment in social activities

     Increased food security       Reduce number of chronically     Status: currently over 3million Kenyans characterized as food insecure and requiring food relief; severely stunted
                                   under-nourished by half by       under-five-year-olds: 12.2% (1993), 12.7% (1998).
                                   2015 (World Food Summit)         Actions:
                                                                    •    Creation of a National Emergency Coordinating Unit;
                                                                    •    Development of a sessional paper on national food policy; provision of food a priority of the Government;
                                                                    •    Coordination of efforts: United Nations Disaster Management Team and the Kenya Food Security Group to review situation and make
                                                                         interventions;
                                                                    •    Operation of non-governmental organizations working on food security
                                                                    •    Review of various laws such as those governing agriculture and land control;
                                                                    •    Provision of food embedded in the current National Development Plan (1997-01).




57
58
     Conference Goal                   Target                               Indicators and follow-up action by the Government of Kenya
     Income poverty



     Health and mortality
     Improved health care              Universal accessibility of           Status: no data on proportion of population with access to public health care services
                                       primary health care (International   Actions:
                                       Conference on Population and         •    Expansion of community health services;
                                       Development/World Summit on          •    Provision of effective diagnostic, therapeutic and rehabilitation services;
                                       Sustainable Development/             •    Formulation of a National Reproductive Health Strategy (1996);
                                       Fourth World Conference on           •    Intensification of research and development to identify more efficient and cost-effective methods for service delivery;
                                       Women)                               •    Provision of ante-natal care and nutritional education for mothers;
                                                                            •    Intensification of family planning services;
                                                                            •    Law enforcement on food and drug abuse.

     Reduction in levels of HIV/AIDS   Universal access to reproductive     Status: Adult HIV prevalence rate: 9.9% (1994), 13.9% (1998) worrying.
                                       health services and information      Actions:
                                       by 2015 (International Conference    •    Formulation of a national five-year strategy to combat HIV/AIDS (1999);
                                       on Population and Development)       •    Creation of a National Aids Consultative Council (NAAC);
                                                                            •    Declaration of HIV/AIDS a national disaster;
                                                                            •    Promotion of community-based distribution centres for contraceptives (condoms, etc);
                                                                            •    Strengthening of information, education and communication activities particularly focusing the youth;
                                                                            •    Promotion of safe blood, HIV infection in control in health services and building capacity in AIDS management;
                                                                            •    Establishment of community-based HIV/AIDS committees;
                                                                            •    Promotion of home-based care for AIDS patients.

     Reduced infant mortality          Reduction of the infant              Status: Infant mortality rate: 58.6/1,000 live births (1989), 70.7/1,000 live births (1998).
                                       mortality rate by 1/3 of 1990        Actions:
                                       level and below 35 per 1,000         •    Intensification of maternal care during pregnancy
                                       by 2015 (International               •    Promotion of programmes on child spacing;
                                       Conference on Population and         •    Promotion of programmes focusing on educating the girl-child;
                                       Development/World Summit             •    Training programmes for care providers (skilled birth attendants).
                                       on Sustainable Development/
                                       World Conference on Women/
                                       World Food Summit)

     Reduced child mortality           Under five mortality rate            Status:Under five mortality rate: 90.9/1,000 live births (1989), 105.2/1,000 live births (1998).
                                       reduced by 2/3 of 1990 level         Actions:
                                       by 2015 (International               •    Maternal ante-natal and post-natal care;
                                       Conference on Population             •    Development of programmes on child spacing;
                                       and Development/World                •    Intensification of education for the girl-child.
                                       Summit for Children)
     Conference Goal                  Target                            Indicators and follow-up action by the Government of Kenya
     Income poverty


     Reproductive health
     Improved maternal health         Reduction by 1/2 of 1990 levels   Status: Maternal mortality rate: all data suspect due to very big errors on estimates. The trend can therefore not be established.
     and reduced maternal mortality    by year 2000 and a further 1/2   Actions:
                                      by 2015 (International            •    Promotion of safe motherhood;
                                      Conference on Population          •    Emphasis on skilled birth attendants;
                                      and Development/World             •    Increased funding for rural health care service delivery;
                                      Summit on Sustainable             •    Review of policy on cost-sharing to include waivers for vulnerable groups;
                                      Development/Fourth World          •    Emphasis on transparency in the collection and use of cost-shared funds.
                                      Conference on Women/World
                                      Summit for Children)



     Improved access to               Universal access to safe/         Status: Contraceptive use has risen from 17.9 per cent in 1989 to 31 per cent in 1998
     family planning                  reliable contraceptive            Actions:
                                      methods (International            •    Family planning intensified;
                                      Conference on Population          •    Strengthening reproductive health education and maternal services;
                                      and Development)                  •    Formulation of a National Reproductive Health Strategy (1996);
                                                                        •    National Health Sector Reform Programme formulated.

     Child health and welfare         Universal immunization            Status: 78.0 per cent of one-year olds immunized against measles (1989), 76.3 per cent (2000); national immunization coverage:
     Improved child health            against measles (World            72.8 per cent (1989), 65.4 per cent (1998).
                                      Summit for Children)              Actions:
                                                                        •    Increase in funding to KEPI as the key programme in preventive health;
                                                                        •    Intensification of education programmes targeting rural communities aimed at easing resistance;
                                                                        •    Increase in health care services with particular emphasis on women and children <5;
                                                                        •    Increased coverage for measles vaccinations;
                                                                        •    Encouragement of non-governmental organizations interested in providing health care services and funding;
                                                                        •    Programmes to prevent and control HIV/AIDS and sexually transmitted diseases;

     Reduced child labour             Elimination of child labour       Status: Child labour, measured by children under 15 working in Kenya on an upward trend, from 30% in 1989 to 40% in 1998.
                                      (World Summit on Sustainable      Actions:
                                      Development/ WHO)                 •    Kenya ratified ILO Convention 138 on Minimum Age for Admission to Employment in 1979;
                                                                        •    Draft Children’s Bill (1998) restricts employment of children;
                                                                        •    Existence of a Gazetted National Steering Committee on Child Labour (Government of Kenya, Confederation of Trade Unions, Federation
                                                                             of Kenya Employers);
                                                                        •    Intensification of campaigns against exploitation of the girl-child in all spheres including child labour;
                                                                        •    Directory of non-governmental organizations working to combat child labour created by the Children’s Department; existence of a coali-
                                                                             tion of non-governmental organizations, donors, United Nations, etc. with intensified action against child labour.
     Education




59
60
     Conference Goal                  Target                           Indicators and follow-up action by the Government of Kenya
     Income poverty


     Increased access                  Universal access and            Status: 76 per cent enrolment rate in 1997; reversal of enrolment at all levels of education characterized
     to basic education                completion of primary           by non-enrolment, high dropout rate, low level of completion rates and poor transition from one level to another.
                                       education by 2015 (World        Actions:
                                       Conference on Education         •    Development of Early Child Development Centres;
                                       for All/World Conference        •    School feeding programmes in arid and semi-arid areas; abolition of tuition fees; provision of bursaries;
                                       on Women/World Summit           •    Review of the curriculum to ensure suitability;
                                       on Women/International          •    Deployment of inspectors at zonal levels;
                                       Conference on Population and    •    Policy shift from tertiary to basic education;
                                       Development)                    •    Launch of a national policy on textbook production, increase in guidance and counseling;
                                                                       •    Establishment of vocational rehabilitation training centres.

     Increased literacy                Adult illiteracy reduced by     Status: some progress: 1988, 82.4%; 2000, 86.2% literate
                                       half of 1990 level by 2000      Actions:
                                       (World Conference on            •    Intensification of adult literacy programmes;
                                       Education for All/World         •    Distribution of literacy books to learners;
                                       Summit on Sustainable           •    Introduction of mobile library networks in the rural areas.
                                       Development/World
                                       Conference on Women)

     Gender equality and women’s empowerment
     Gender equality
     in education                     Eliminate disparity in           Status: low disparity in primary but a deterioration in 1999; gender disparity in secondary improving slightly; boys per girl in
                                      primary and secondary            primary and secondary education respectively - 1996: 1.032, 1.156; 1999: 1.041, 1.120.
                                      education by 2005 (ICPD/         Action:
                                      WSSD/FWCW)                       •    Promotion of education programmes for girls and women;
                                                                       •    Support to institutions which promote the interest of girls;
                                                                       •    Social campaigns which deal not only with access but also on retention and quantitative aspects of schooling;

     Gender equality in                Eliminate discriminatory        Status: Increase in female share of formal sector employment (from 23% in 1993 to 29.5% in 1999)
     employment                        practices in employment         Action:
                                       (FWCW)                          •    Dismantling intrusive, restrictive and outdated laws and regulations to allow women participate in paid employment;
                                                                       •    Promotion of rural non-farm employment to enable increased women participation;
                                                                       •    Vocational training with preferential treatment for women.

     Women’s political                 Equitable access to political   Status: women’s participation in key decision-making organs of government increased but remains dismal on the whole.
     empowerment                       institutions (FWCW)             Actions:
                                                                       •    Report on task force reviewing legislation pertaining to women’s standing before the law presented to the Government; as a result:-
                                                                       •    Affirmative Action Bill, the Family Protection Bill and the Equality Bill, all published to increase women’s participation in decision
                                                                            making and protect their rights;
                                                                       •    National gender policy formulated to mainstream gender issues in all areas of development;
     Conference Goal                   Target                            Indicators and follow-up action by the Government of Kenya
     Income poverty

                                                                          •    Creation of a Land Commission to, among other things, review laws and customary practices relating to ownership;
                                                                          •    Existence of non-governmental organizations championing the cause of women empowerment.
      Employment and sustainable livelihood
      Creation of full                  Universal access to paid          Status: No up-to-date data on unemployment but with the recession and downsizing of the public sector, it is thought to be
      employment                        employment (WSSD)                  high and increasing; informal sector employment rising
                                                                          Actions:
                                                                          •    Publication of Sessional Paper on Small Enterprise and Jua Kali Development (1992);
                                                                          •    Publication of Sessional Paper No. 2 (1996) on Industrial Transformation;
                                                                          •    Employment policy statements in the National Development Plan 1997-2001

      Housing and basic household amenities and facilities
      Adequate shelter for all          Provision of sufficient           Status: Objective of providing sufficient housing is far from being met; the current situation is characterized by a housing
                                        living space and avoidance        deficit, growing annually; 60 per cent of the total population of the city of Nairobi occupy 5 per cent of its total residential area.
                                        of overcrowding (HABITAT II)      Action:
                                                                          •    Improvement in urban governance through the Kenya Local Government Reform Programme;
                                                                          •    Gradual progress towards local participation;
                                                                          •    Sessional paper to enable growth of the informal sector; enhancing the provision of credit;

      Improved access to                 Universal access to safe         Status: Rural areas (dry season) 38.2 per cent had access to sustainable safe drinking water in 1989; 45.9 per cent had access in
      safe drinking water                drinking water; full coverage    2000. In urban areas, 95.4 per cent had access in 1989 and 88.0 per cent in 2000.
                                         of drinking water supply by      Action:
                                         2025 (World Conference on        •    Review of the national water policy and legislation;
                                         Women/World Summit on            •    Promotion of increased community management of water resources;
                                         Sustainable Development/         •    Privatization of water undertaking.
                                         UNCED)

      Improved access to                 Universal sanitary waste         Status: In 1992, 80.9 per cent of those in rural areas had access to adequate sanitary waste disposal, in 2000, 75.5 per cent. In
      safe sanitation                    disposal (World Conference        urban areas, in 1992, 96.8 per cent and 93.0 per cent in 2000.
                                         on Women/World Summit            Action:
                                         for Children/World Summit        •    Sanitation programmes and beautification projects
                                         on Sustainable Development/      •    Review of by-laws at the city level;
                                         UNCED)                           •    Communal participation in cleaning ;
                                                                          •    Involvement of other stakeholders, e.g., the private sector in urban environmental management;
                                                                          •    Privatization of refuse collection in urban areas.
      Environment
      Improved environment               Clean and healthy                Status: Forest plantation area decreased from 160,000 ha (1995) to 141,900 ha (1999) but there was a slight increase in land area
                                         environment and reversal          protected: 6.1% (1996), 8.0% (1999).
                                         of current trends in loss        Action:
                                         of environmental resources       •    Kenya is a signatory to the Vienna Convention on the Protection of the Ozone Layer;
                                         (UNCED)                          •    National Environmental Action Plan prepared and adopted (1994);
                                                                          •    Sessional Paper No. 6 (1999) on Environment and Development giving guidelines on environmental management approved;




61
62
     Conference Goal                     Target                           Indicators and follow-up action by the Government of Kenya
     Income poverty



                                                                          •   Environment Management and Coordination Act No. 8 (1999) enacted establishing a National Environmental Council, National Environ-
                                                                              ment Management Authority and technical committees;
                                                                          •   Review and harmonization of laws (at the subregional level) relating to environmental standards, environmental impact assessment,
                                                                              forestry, wildlife management, management of Lake Victoria, chemical wastes, etc.;
                                                                          •   Ratification of the Convention on Biological Diversit6y (1994); development of a Biodiversity Strategy and Action Plan and a Biodiversity
                                                                              Management Data Base;
                                                                          •   Ratification of the United Nations Framework Convention on Climate Change (1994);
                                                                          •   Creation of a land commission to examine systems for sustainable use and management;

     Drug control and crime prevention
     Improved drug control               Measurable results in            Status: upward trend in the abuse of drugs; only limited reliable data to show extent of cultivation, manufacture, trafficking
                                         reducing cultivation,            and abuse of illicit drugs;
                                         manufacture, trafficking         Action:
                                         and abuse of illicit drugs       •    Establishment of an Anti-Narcotics Unit within the Criminal Investigation Department;
                                         by 2008 (UNDCP)                  •    Repeat rapid assessment study on drug abuse;
                                                                          •    Intensification of demand reduction activities particularly targeting the youth and using information, education and communication
                                                                               materials;
                                                                          •    Establishment of treatment and rehabilitation centres;
                                                                          •    Intensification of supply reduction activities through increased surveillance and monitoring;
                                                                          •    Strengthening of law enforcement.

     Improved crime prevention           Eliminate/significantly          Status: penal code cases per 100,000 people: 338 (1993), 399 (1997).
                                         reduce violence and crime        Action:
                                         (United Nations Congress         •    Creation of community policing
                                         on the Prevention of Crime
                                         and Treatment of Offenders)

     Universal legal commitments for human rights
     Universal ratification            Acceding to all international      Status: Kenya has ratified all but one of the six international human rights instruments;
     of international human            human rights instruments and       Efforts to adopt legislation towards the enjoyment of the rights enshrined under the conventions has been slow and there has
     rights instruments                avoiding resort to reservations,   been no consistent record of follow-up action;
                                       as far as possible

     Democracy and participation
     Strengthened democratic             Free and fair elections and      Status: Kenya has held elections consistently since 1963 with noteworthy improvements from non-secret ballot and single party
     institutions and popular            democratic government             (1988) to multiparty, secret ballot in 1992 and 1997.
     participation                       (World Conference on Human       Action:
                                         Rights)                          •    Creation of an Electoral Commission to manage and supervise elections;
                                                                          •    Setting up of a Parliamentary Service Commission to ensure the autonomy of Parliament;
                                                                          •    Review of laws relating to elections under the Inter-Parties Parliamentary Group;
     Conference Goal             Target                             Indicators and follow-up action by the Government of Kenya
     Income poverty


                                                                    •   Increased participation of women organizations and women decision makers;
                                                                    •   Creation of the Constitutional Review Commission to review the Constitution of Kenya.
     Administration of justice

     Fair administration         Effective legislative framework,   Status: some recent improvements in the administration of justice.
     of justice                  law enforcement, prosecutions,     Action:
                                 the legal profession and           •    Implementation of the Kwach Report on reform of the judiciary and improvement of the administration of justice;
                                 fair trials in conformity with     •    Institutional reform in the Attorney-General’s Office, ministries and legal education institutions;
                                 international standards            •    Review of the Penal Code and the Criminal Procedures Code;
                                 (World Conference on               •    Enactment of a Community Service Order for a community service punishment regime;
                                 Human Rights)                      •    Existence of a strengthened office of the Controller and Auditor-General
                                                                    •    Creation of the Judicial Service Commission
                                                                    •    Reform in the commercial law process by the creation of the Commercial Court;
                                                                    •    Introduction of alternative dispute resolution mechanisms and creation of a small claims court;
                                                                    •    Establishment of the Kenya Anti-Corruption Authority (KACA); drafting and publication of an Anti-Corruption and Economics Crimes
                                                                         Bill to give greater autonomy to KACA to deal with corruption;
                                                                    •    Formulation of a code of ethics for public servants.

     Improved framework          Existence of legal remedies        Action:
     of remedies                 in conformity with international   •    Establishment of KACA
                                 standards                          •    Recognition in law of the right to representation.
     Security of persons
     Liberty and                 Elimination of gross               Status: record not good for Kenya
     security of persons         violations of human                Action:
                                 rights affecting the               •    Establishment of an independent human rights body: the Standing Committee on Human Rights;
                                 security of persons,               •    Existence of independent human rights organizations and watch-dogs;
                                 including torture and cruel,
                                 inhuman or degrading
                                 treatment or punishment;
                                 summary and arbitrary
                                 execution; disappearances
                                 and slavery (World
                                 Conference on
                                 Human Rights)




63
     Annex VII:                    Terms of reference


     1.    Definition                                               which is described in the UNDAF. At the same
                                                                    time, the teamwork promoted by the CCA is
     The Common Country Assessment (CCA) is a coun-                 indispensable for uniting the United Nations
     try-based process that reviews and analyzes key                system around the subsequent UNDAF and for
     development challenges and identifies issues as a              building alliances with key development ac-
     basis for advocacy, policy dialogue and preparation            tors;
     of the UNDAF. The findings that emerge from this         (b)   Facilitation of country-level follow-up to United
     exercise are described in a CCA document.                      Nations conferences and support for the im-
                                                                    plementation of United Nations conventions
     2.    Partners                                                 and declarations;
                                                              (c)   Advocacy: The CCA provides a forum for advo-
     The CCA is undertaken by the United Nations sys-               cacy and dialogue among the Government, the
     tem with the national government and key develop-              United Nations system and the wider develop-
     ment partners.                                                 ment community. The CCA is an ongoing proc-
                                                                    ess. There is a continuous dialogue on issues
     3.    Objective                                                when it becomes difficult to reach consensus.
                                                                    Thus the CCA provides an objective basis for
     To gain a deeper understanding of the main devel-              resolving policy-level issues between the Gov-
     opment challenges facing Kenya, based on a com-                ernment and the United Nations system;
     mon analysis and understanding of the development        (d)   Promoting partnerships and alliances: The
     situation. The assessment also identifies priorities           participatory discussions of the assessment
     for future assistance by the United Nations system.            provide an opportunity for building alliances
                                                                    and partnerships in support of national priori-
     4.    Use of the CCA                                           ties and needs and internationally agreed
                                                                    goals, for instance, with civil society;
     The CCA can be used, inter alia, for the following:      (e)   Programming: The CCA is the basis for the
                                                                    preparation of the UNDAF which indicates the
     (a)   Preparation of the United Nations Development            objectives and strategies of United Nations as-
           Assistance Framework (UNDAF): General As-                sistance and guides the subsequent country pro-
           sembly resolution 53/192, paragraph 22, notes            grammes. The quantitative data of the CCA
           “the role that the United Nations Development            should be used as baseline information in all
           Assistance Framework should play to facili-              programme documents; and
           tate, inter alia, the contribution of the United   (f)   Monitoring: The CCA Indicator Framework
           Nations to the coordinated follow-up to the              may be used to monitor trends in national de-
           major United Nations conferences at the field            velopment over time.
           level and the importance of the common coun-
           try assessment for the effective formulation of    6. Expected output
           the Framework”. It generates a common un-
           derstanding within the United Nations system       A CCA document that provides an overview of key
           of the causes of development problems as well      development issues facing the country and
           as the needs and priorities of a country. This     prioritizes action for the United Nations system. The
           helps to define the purpose and strategy of        document will also contain a list of common indica-
           United Nations system support to a country,        tors with disaggregated data, wherever possible.



64
7.   Scope of work                                                (b)    Poverty audit: The revised CCA draft will then
                                                                         undergo a poverty reduction audit to ensure
The preparatory process                                                  that issues with the highest impact on poverty
                                                                         are evident;
The United Nations Country Team, in consultation                  (c)    Facilitation: Under the oversight of the Resi-
with the Government and its development partners,                        dent Coordinator and with the day-to-day su-
will launch the CCA exercise and agree on a frame-                       pervision by the CCA Advisory Team, together
work for preparing it. Discussions will be held within                   with the technical input by the CCA consult-
theme groups16 to identify and select a core list of                     ant, the Programme Analyst in the office of
indicators and data reflecting the key issues of con-                    the Resident Coordinator will be responsible
cern to the groups. This will be passed on to the                        for convening theme groups, drafting discus-
CCA consultant for collation and analysis. Theme                         sion papers where necessary, compiling a list
groups will participate in the analysis. Similar dis-                    of common indicators and data and organizing
cussions will also be held with the Government and                       consultations on the CCA. The CCA consult-
other partners. The discussions will be followed by                      ant will assist in drafting the CCA document;
the following activities:                                         (d)    Final review: The final draft will be circulated
(a) Drafting of chapters and consultations: The                          to members of the United Nations Country
      groups will identify an individual or individu-                    Team, chairs of theme groups, a selected group
      als to work with the Advisory Team and the                         of peer reviewers, and those United Nations
      CCA consultant in identifying and selecting a                      agencies not represented in the country. The
      core list of indicators and data reflecting the                    CCA consultant will then compile and edit the
      key issues discussed in their respective areas.                    final draft for printing.
      Drafts will then be discussed and revised and
      put forward for consultation with the Govern-               8.    Follow-up
      ment and other key development partners;
                                                                  The United Nations Country Team will review the
                                                                  CCA document and indicators on a regular basis.




17 Theme groups not only reflect the current work of the United Nations system in Kenya, but also the key areas where assistance
   by the United Nations system can make an impact



                                                                                                                                   65
     Annex VIII: Tables of disaggregated data

                            Table 1.0: Rural absolute poverty by Province

                            1982               1992            1994             1997
        Province          Headcount          Headcount       Headcount        Headcount
                            %AE*               %AE             %AE              %AE

        Coast                54.55               43.50          55.63            62.10
        Eastern              47.73               42.16          57.75            58.56
        Central              25.69               35.89          31.93            31.59
        Rift Valley          51.05               51.51          42.87            50.10
        Nyanza               57.88               47.41          42.21            63.05
        Western              53.79               54.81          53.83            58.75
        North-Eastern          -                   -            58.00              -

        Total rural          47.89               46.33          46.75            52.93

        *AE = Adult equivalent
        CBS : Economic Survey, 1997, Second Poverty in Kenya Report Vol II, 2000




                                          Table 1.1: Decomposition of Urban Poverty Measures, 1997

     Urban Centres                                           Headcount                   Poverty     Severity     % of          %
                                          1994                                            Gap          of       Population   Change
                                         Pα=0       Pα=0        Pα=0          Pα=0        Pα=1       Poverty                 1997/94
                                         ADULT      ADULT      HHOLDS       Individs       AE         Pa=2                     AE
                                          AE*        AE                                                AE                     Pa=0

     Food Poverty Line
     (Monthly Kshs.1,253.90 per adult)
     Overall Urban                       29.23      38.29       32.35        38.37       10.65        4.04       100.00      31.00
     Nairobi                             27.26      38.38       34.68        38.17       10.40        3.90        48.06      40.79
     Mombasa                             33.12      38.57       31.02        39.78       10.96        4.07        13.86      16.46
     Kisumu                              44.09      53.39       45.77        53.64       16.61        6.88        5.26       21.09
     Nakuru                              37.18      26.81       19.75        26.31       6.52         2.50        6.78       -27.89
     Other Urban                         27.07      37.91       30.19        37.98       10.82        4.11        26.05      40.04

     Absolute Poverty Line
     (Monthly Kshs.2,648.04 per adult)
     Overall Urban                       28.95      49.20       43.45        50.11       15.67         6.86      100.00       69.95
     Nairobi                             25.90      50.24       46.59        51.17       14.07         5.47       48.06       93.98
     Mombasa                             33.14      38.32       33.52        39.44       14.29         6.96       13.86       15.63
     Kisumu                              47.75      63.73       58.11        63.97       23.09        11.42       5.26        33.47
     Nakuru                              30.01      40.58       32.84        41.06       10.58         3.84       6.78        35.22
     Other Urban                         28.73      52.38       43.53        53.30       19.20         9.22       26.05       82.32

     Hard Core Poverty Line
     (Monthly Kshs.1,253.90 per adult)
     Overall Urban                       10.07      7.58        5.89         7.70         1.91        0.68       100.00      -24.73
     Nairobi                             9.32       3.83        3.33         3.82         1.18        0.45        48.06      -58.91
     Mombasa                             7.56       9.31        6.55         9.47         2.36        0.85        13.86      23.15
     Kisumu                              19.59      16.77       11.22        17.42        4.40        1.70        5.26       -14.40
     Nakuru                              8.62       3.68        2.93         3.21         0.76        0.17        6.78       -57.31
     Other Urban                         11.02      12.72       9.41         12.83        2.82        0.93        26.05      15.43

     *AE = Adult Equivalent
     Source: Welfare Monitoring Survey 1997 database




66
                    Table 1.2 : Absolute poverty measures by rural region of residence*, 1997 (Kshs 1,238.86)

Name of district    (Kshs 978.26)                Headcount                    Poverty      Severity of      % of         %
                        1994                                                   Gap          Poverty      Population   Change

                         Pα=0          Pα=0         Pα=0         Pα=0          Pα =1        Pα =2                     1997/94
                          AE            AE         HHOLDS       Individ         AE           AE                       Pα=0 AE

Central rural            31.93         31.39         25.72       31.37         9.25          3.94          14.52       -1.69
Kiambu                   29.32         25.08         19.61       25.06         6.08          2.46           4.59      -14.46
Kirinyaga                35.41         35.70         31.19       35.60         12.43         5.62           1.83        0.82
Murang’a                 37.11         38.62         32.15       38.58         11.02         4.47           3.95        4.07
Nyandarua                33.34         26.95         22.41       26.96         8.51          3.44           1.48      -19.17
Nyeri                    25.62         31.05         24.29       30.95         10.35         4.81           2.68      21.19
Coast rural              55.63         62.10         51.97       62.19         24.40         11.87          5.53       11.63
Kilifi                   66.88         66.30         53.01       66.00         26.14         12.40          2.52       -0.87
Kwale                    40.23         60.55         51.45       61.20         25.25         13.14          1.74      50.51
Lamu                     29.53         39.35         29.36       39.38         11.04         4.09           0.25      33.25
Taita Taveta             50.65         65.82         60.54       66.30         24.88         11.82          0.82      29.95
Tana River               71.76         34.22         28.55       32.71         8.97          3.77           0.18      -52.31

Eastern rural            57.75         58.56         53.08       58.24         22.37         10.71         15.23       1.40
Mbeere                                 51.36         44.80       49.98         21.14         10.50          0.63          -
Embu                     62.86         55.76         53.94       56.19         23.47         11.69          0.76      -11.29
Kitui                    55.09         64.91         60.58       64.58         25.80         12.48          2.71      17.83
Machakos                 68.72         62.96         58.75       63.25         22.85         10.53          3.18       -8.38
Meru                     30.64         40.96         36.44       40.53         13.37          6.20          1.43      33.68
Makueni                  76.06         73.51         63.06       73.72         32.24         16.94          2.44       -3.35
Tharaka Nithi            46.15         55.58         46.79       55.05         18.92         8.52          1.23       20.43
Nyambene                               47.29         44.65       45.47         16.13          6.90          2.86          -

Nyanza rural             42.21         63.05         56.68       62.89         23.43         11.43         16.64       49.37
Kisii                    31.58         57.22         52.67       56.87         22.50         11.65          2.79       81.19
Kisumu                   46.91         65.44         61.08       65.16         26.70         13.87          2.07       39.50
Siaya                    46.90         58.02         50.41       57.93         20.92          9.78          2.77       23.71
Homa Bay                 47.74         77.49         72.16       77.25         29.54         14.63          2.03       62.32
Migori                   34.08         57.63         48.19       57.41         16.57          6.74          3.28       69.10
Nyamira                  51.57         66.74         60.43       67.20         26.92         13.52          3.71       29.42

Rift Valley rural        42.87         50.10         44.08       50.17         17.58         8.17          20.54      16.86
Kajiado                  22.49         27.87         24.33       28.26         10.41         4.91           1.08      23.92
Kericho                  59.56         52.42         48.10       52.41         18.11         8.50           2.33      -11.99
Laikipia                 45.55         33.88         24.47       33.37          8.33         3.36           1.04      -25.62
Nakuru                   36.61         45.08         36.45       45.10         14.75         6.25           3.40      23.14
Nandi                    41.73         64.15         59.11       65.16         23.08         11.12          2.08      53.73
Narok                    27.33         52.17         44.35       52.28         17.12         6.95           0.96      90.89
Bomet                    46.53         61.80         58.40       62.53         24.80         12.54          2.11      32.82
Transmara                              56.59         53.67       57.12         19.26         8.77           0.87          -
Baringo                  40.77         36.95         31.85       36.91         12.49         5.69           1.39       -9.37
Elgeyo-Marakwet          27.23         47.82         40.87       46.61         13.83         5.37           1.05      75.62
Trans Nzoia              48.57         54.83         53.07       55.03         19.53         9.11           1.66      12.89
Uasin Gishu              33.54         42.22         37.54       41.86         12.05         4.92           1.67      25.88
West Pokot               48.52         68.46         63.69       67.96         33.98         18.86          0.92      41.10
Western rural            58.83         58.75         53.56       59.32         22.81         11.16         11.35       -0.14
Bungoma                  56.00         55.21         49.40       55.36         20.42         9.49           3.17       -1.41
Busia                    56.90         65.99         60.85       66.63         27.90         14.30          1.64      15.98
Kakamega                 51.34         56.69         49.98       57.47         23.15         11.68          4.12      10.42
Vihiga                   53.00         61.97         59.25       62.84         21.91         10.33          2.42      16.92

Total rural              46.75         52.93         46.35       53.06         19.33         9.19          83.81       13.22

Source: Welfare Monitoring Survey III, 1997 database
*The 1997 survey excluded the Districts of Garissa, Mandera, Wajir,Marsabit, Samburu, Isiolo and Turkana, which were
surveyed in 1994. It included the new Districts of Mbeere, Nyambene and Transmara




                                                                                                                                67
                          Table 1.3 : Food poverty measures by rural region of residence*, 1997 (Kshs 927.08)


     Name of district   (Kshs 978.26)              Headcount                    Poverty      Severity of      % of        %
                            1994                                                 Gap          Poverty      Population   Change

                            Pα=0         Pα=0            Pα=0       Pα=0         Pα =1         Pα =2                    1997/94
                             AE           AE            HHOLDS     Individ        AE            AE                      Pα=0 AE

     Central rural          32.95        29.73           23.38     29.63         8.58           3.58            17.32    -9.77
     Kiambu                 37.82        24.19           17.58     23.91          6.19          2.70             5.48   -36.04
     Kirinyaga              34.70        37.10           31.50     37.01         13.06          5.86             2.18     6.92
     Murang’a               36.62        32.50           25.48     32.63          9.37          3.72             4.71   -11.25
     Nyandarua              30.74        26.75           22.37     26.78          7.58          2.62             1.76   -12.98
     Nyeri                  20.30        31.77           24.40     31.49          8.99          3.85             3.20   56.50
     Coast rural            50.95        59.46           50.25     59.32         21.83         10.04            6.59    16.70
     Kilifi                 65.35        63.68           51.91     63.10         23.02         10.33            3.01     -2.56
     Kwale                  31.77        58.94           49.52     59.41         22.65         10.77            2.08    85.52
     Lamu                   24.20        31.86           24.56     32.64          9.70          4.15            0.30    31.65
     Taita Taveta           42.61        62.44           58.69     62.46         22.89         10.67            0.98    46.54
     Tana River             70.55        31.23           25.93     29.77          9.82          4.29            0.22    -55.73
     Eastern rural          59.50        56.82           51.00     56.42         19.75         9.04             18.18    -4.50
     Mbeere                              57.42           45.40     55.17         20.01          9.41             0.76       -
     Embu                   60.91        54.77           50.95     55.12         21.29         10.48             0.91   -10.08
     Kitui                  64.85        63.23           59.66     62.98         22.90         10.51             3.23    -2.50
     Machakos               65.86        64.47           58.14     64.58         20.52          8.90             3.79    -2.11
     Meru                   39.28        40.68           35.73     40.55         13.24          5.97             1.70     3.56
     Makueni                69.86        71.43           62.44     71.64         29.32         14.77             2.91     2.25
     Tharaka Nithi          46.69        51.65           41.76     51.08         18.00          8.50             1.47   10.62
     Nyambene                            40.48           38.47     38.53         11.30          4.19             3.41       -
     Nyanza rural           41.31        58.16           50.84     58.15         20.55         9.43             19.85    40.79
     Kisii                  39.98        53.49           46.82     52.71         19.00          8.98             3.33    33.79
     Kisumu                 42.28        60.33           54.99     59.89         23.25         11.47             2.47    42.69
     Siaya                  41.11        52.61           43.64     53.01         17.61          7.85             3.30    27.97
     Homa Bay               40.90        66.94           62.78     66.80         25.45         12.28             2.42    63.67
     Migori                 31.81        51.09           41.12     51.48         14.52          5.70             3.91    60.61
     Nyamira                55.22        66.03           58.81     66.67         25.05         11.57             4.43    19.58
     RiftValley rural       45.75        48.02           41.13     47.61         16.53         7.55             24.51    4.96
     Kajiado                30.22        25.17           22.24     25.36          9.63          4.84             1.28   -16.71
     Kericho                58.52        50.88           43.95     50.02         16.90          7.98             2.77   -13.06
     Laikipia               46.78        26.34           19.49     25.81          7.10          2.68             1.24   -43.69
     Nakuru                 32.69        42.26           33.92     42.10         13.51          5.95             4.06   29.28
     Nandi                  45.32        55.39           53.05     55.76         21.34         10.28             2.48   22.22
     Narok                  35.84        49.24           40.99     48.68         14.53          5.53             1.14   37.39
     Bomet                  52.49        63.86           56.58     63.84         24.21         11.62             2.52   21.66
     Transmara                           54.26           50.43     53.32         16.57          7.16             1.03      -
     Baringo                49.99        35.32           30.95     34.66         11.65          5.09             1.66   -29.35
     Elgeyo-Marakwet        34.28        47.57           38.61     46.54         14.37          5.79             1.25   38.77
     Trans Nzoia            55.25        54.21           49.02     54.02         18.76          8.47             1.98    -1.88
     Uasin Gishu            38.10        43.62           37.10     42.92         12.46          5.04             1.99   14.49
     West Pokot             42.97        69.74           62.78     68.63         32.32         16.59             1.10   62.30
     Western rural          52.25        58.58           52.45     58.69         21.39         10.16            13.54    12.11
     Bungoma                55.05        57.12           50.58     56.74         20.42          9.57             3.78     3.76
     Busia                  53.18        61.40           55.84     61.77         24.91         12.11             1.95    15.46
     Kakamega               48.98        57.99           50.09     58.25         22.60         11.10             4.92    18.40
     Vihiga                 53.42        59.58           56.26     59.95         18.24          8.02             2.89    11.53
     TOTAL RURAL            47.19        50.65           43.39     50.58         17.55          8.02         100.00      7.33

     Source: Welfare Monitoring Survey, 1997 database
     * See footnote to Table 1.2




68
                     Table 1.4 : Hardcore poverty measures by rural region of residence*, 1997 (Kshs 927.08)


Name of district   (Kshs 978.26)               Headcount                   Poverty       Severity of      % of        %
                       1994                                                 Gap           Poverty      Population   Change

                       Pα=0          Pα=0         Pα=0         Pα=0         Pα =1         Pα =2                     1997/94
                        AE            AE         HHOLDS       Individ        AE            AE                       Pα=0 AE

Central rural          16.17         15.56        12.81        15.57         4.00          1.41          17.36       -3.77
Kiambu                 14.76          7.78         6.58         7.63         2.09          0.73          5.47       -47.29
Kirinyaga              19.05         21.45        17.98        20.64         5.94          2.24          2.18       12.60
Murang’a               21.25         20.70        16.33        21.05         4.98          1.68          4.76        -2.59
Nyandarua              17.68         17.32        14.92        17.44         3.91          1.15          1.78        -2.04
Nyeri                   8.51         16.32        12.84        16.28         4.55          1.76          3.18       91.77

Coast rural            36.53         44.78        36.83        45.14        13.54          5.39           6.58      22.58
Kilifi                 43.02         48.98        36.88        49.02        14.72          5.64           3.03      13.85
Kwale                  26.17         44.80        38.24        45.72        14.26          6.08           2.04      71.19
Lamu                   20.52         18.44        13.61        18.45         4.19          1.37           0.31      -10.14
Taita Taveta           33.33         47.25        45.13        47.91        13.49          5.27           0.98      41.76
Tana River             51.24         12.77         9.87        11.85         4.16          1.71           0.22      -75.08

Eastern rural          39.25         40.95        36.18        40.57        12.15          4.74          18.12        4.33
Mbeere                               42.38        34.58        40.80        12.35          5.08          0.76           -
Embu                   36.20         43.22        39.53        43.45        14.09          5.78          0.92        19.39
Kitui                  40.13         47.04        44.71        46.35        14.57          5.71          3.24        17.22
Machakos               46.65         42.76        37.16        42.65        11.97          4.55          3.81        -8.34
Meru                   19.03         23.83        21.44        23.66         6.53          2.55          1.70        25.22
Makueni                52.32         58.59        46.96        58.91        19.47          8.33          2.82        11.98
Tharaka Nithi          23.87         32.48        28.20        32.16         9.32          3.62          1.47        36.07
Nyambene                             29.79        28.55        28.28         7.42          2.27          3.40           -

Nyanza rural           22.86         41.98        37.77        42.09        13.13          5.47          19.91       83.64
Kisii                  12.51         38.82        35.26        39.00        13.40          5.96          3.33       210.31
Kisumu                 28.85         46.06        42.62        45.41        15.97          7.18          2.45        59.65
Siaya                  27.08         37.52        31.41        37.75        10.66          4.07          3.29        38.55
Homa Bay               24.97         53.92        48.20        54.15        16.84          7.19          2.42       115.94
Migori                 16.14         29.30        26.11        29.99         7.26          2.69          3.95        81.54
Nyamira                33.88         50.14        46.07        50.59        16.38          6.74          4.46        47.99
RiftValley rural       27.34         31.67        27.35        31.50         9.14          3.51          24.55       15.84
Kajiado                14.58         21.15        16.96        21.70         6.02          2.18          1.30        45.06
Kericho                42.67         32.26        30.42        32.22         9.28          3.53          2.76       -24.40
Laikipia               30.30         15.83        10.47        16.18         3.67          1.32          1.25       -47.76
Nakuru                 23.21         29.15        21.38        29.00         6.57          2.20          4.07        25.59
Nandi                  23.31         40.65        38.60        40.82        13.00          5.36          2.49        74.39
Narok                   9.49         34.03        27.88        34.28         7.91          2.43          1.15       258.59
Bomet                  32.53         42.68        39.20        42.40        14.46          6.05          2.51        31.20
Transmara                            34.04        34.95        32.99         8.38          2.90          1.01           -
Baringo                20.56         22.76        19.00        22.26         6.37          2.42          1.67        10.70
Elgeyo-Marakwet        12.88         26.01        21.85        25.78         5.89          1.87          1.27       101.94
Trans Nzoia            29.28         32.33        30.10        32.14        10.62          4.26          2.00        10.42
Uasin Gishu            20.71         20.73        18.49        20.72         5.44          1.88          2.01         0.10
West Pokot             30.88         59.66        53.91        58.29        21.73          9.44          1.06        93.20

Western rural          35.78         41.67        37.91        41.84        12.45          5.03          13.48       16.46
Bungoma                40.91         39.04        32.51        39.12        10.57          3.89          3.77        -4.57
Busia                  42.03         50.64        45.82        50.98        17.08          7.28          1.96        20.49
Kakamega               31.42         40.64        35.60        40.76        12.89          5.39          4.87        29.34
Vihiga                 32.09         40.77        42.28        41.00        11.01          4.39          2.87        27.05

TOTAL RURAL            29.19         34.82        30.10        34.88        10.32          4.09         100.00       19.29

Source: Welfare Monitoring Survey III,1997 database *See footnote to Table 3-3




                                                                                                                              69
                                           Table 1.5: Population growth in Kenya 1944-2010

     Year              Reconstructed               Rate of              Year           Projected            Rate of
                      population (000’s)        growth (%pa)                        population (000’s)   growth (%pa)

     1944                    5578                    1.89               1990                 23715           3.16
     1945                    5684                    1.99               1991                 24477           3.07
     1946                    5799                    2.09               1992                 25240           2.97
     1947                    5921                    2.19               1993                 26002           2.88
     1948                    6052                    2.29               1994                 26762           2.79
     1949                    6192                    2.52               1995                 27519           2.68
     1950                    6350                    2.55               1996                 28267           2.59
     1951                    6514                    2.59               1997                 29010           2.51
     1952                    6685                    2.62               1998                 29746           2.41
     1953                    6862                    2.65               1999                 30473           2.32
     1954                    7047                    2.65               2000                 31189           2.24
     1955                    7236                    2.70               2001                 31896           2.15
     1956                    7434                    2.76               2002                 32588           2.05
     1957                    7642                    2.81               2003                 33264           1.96
     1958                    7860                    2.86               2004                 33922           1.87
     1959                    8088                    2.94               2005                 34561           1.77
     1960                    8329                    3.01               2006                 35178           1.68
     1961                    8584                    3.02               2007                 35773           1.58
     1962                    8847                    3.03               2008                 36344           1.49
     1963                    9119                    3.07               2009                 36890           1.40
     1964                    9404                    3.10               2010                 37408
     1965                    9700                    3.13
     1966                   10009                    3.15
     1967                   10329                    3.23
     1968                   10668                    3.35
     1969                   11031                    3.50
     1970                   11424                    3.62
     1971                   11846                    3.71
     1972                   12293                    3.78
     1973                   12767                    3.85
     1974                   13268                    3.92
     1975                   13798                    3.95
     1976                   14354                    3.97
     1977                   14935                    3.99
     1978                   15542                    3.99
     1979                   16175                    4.00
     1980                   16835                    3.92
     1981                   17508                    3.83
     1982                   18191                    3.74
     1983                   18885                    3.67
     1984                   19590                    3.55
     1985                   20298                    3.43
     1986                   21006                    3.33
     1987                   21717                    3.23
     1988                   22430                    3.16
     1989                   23150

     CBS: Kenya Population Census 1989, Analytical Report Vol.III

     Pending conventional corrections to the released 1999 census enumeration these populations
     are reasonable forecasts. They take the medium fertility decline and AIDS impact into account




70
                Table 1.6: Population projections for provinces and districts(thousands) medium fertility decline

Province/District         1991       1992      1993       1994        1995       1996       1997      1998     1999        2000

Nairobi                   1564       1635      1708       1782        1857       1932       2009      2086     2164        2243
Kiambu                    1044       1072      1100       1128        1156       1182       1209      1234     1259        1283
Kirinyaga                  417        426       435        444         453        461        469       477      484         491
Murang’a                   916        935       954        972         990       1006       1023      1038     1052        1066
Nyandarua                  358        368       378        388         398        408        417       426      435         444
Nyeri                      668        680       692        704         715        725        735       744      752         760

Central                   3403       3481      3559       3636        3712       3782       3853      3919     3982        4044
Kilifi                     659        677       696        714         732        750        767       784      801         817
Kwale                      428        439       450        460         471        481        491       501      510         519
Lamu                        65         67        69         71          73         75         76        78       80          82
Mombasa                    517        531       545        559         573        586        600       612      625         637
Taita Taveta               215        220       225        230         235        240        244       249      253         257
Tana River                 147        152       157        161         166        171        175       180      184         188

Coast                     2031       2086      2142       2195        2250       2303       2353      2404     2453        2500
Embu                       402        414       425        436         448        458        469       480      490         500
Isiolo                      78         81        85         88          91         94         98       101      105         108
Kitui                      716        737       758        779         799        819        839       859      878         897
Machakos                  1548       1590      1632       1674        1715       1755       1795      1834     1872        1909
Marsabit                   143        147       150        154         157        161        164       167      170         173
Meru                      1290       1329      1367       1405        1443       1480       1517      1553     1589        1624
Eastern                   4177       4298      4417       4536        4653       4767       4882      4994     5104        5211

Garissa                    198        203       209        215          220       226        231       236          241     246
Mandera                    190        198       206        215          223       231        240       248          257     266
Wajir                      197        202       206        210          214       217        221       224          227     230
North-Eastern              585        603       621        640          657       674        692       708          725     742

Kisii                     1461       1504      1546       1589        1631       1672       1713      1753     1792        1831
Kisumu                     792        814       836        857         878        899        919       939      958         977
Siaya                      698        711       722        733         744        754        763       771      779         786
South Nyanza              1360       1399      1438       1476        1514       1551       1588      1624     1659        1693
Nyanza                    4311       4428      4542       4655        4767       4876       4983      5087     5188        5287

Baringo                    326        336       347        357         367        377        387       397      407         416
Elgeyo Marakwet            239        247       255        262         270        278        285       293      300         307
Kajiado                    284        297       310        324         338        352        366       381      396         411
Kericho                   1064       1102      1141       1180        1219       1258       1297      1336     1375        1414
Laikipia                   247        257       268        279         291        302        313       325      337         349
Nakuru                     947        987      1028       1069        1111       1154       1196      1240     1283        1327
Nandi                      494        511       528        545         562        579        596       613      630         647
Narok                      432        454       477        501         526        550        576       602      628         655
Samburu                    122        126       130        134         137        141        145       148      152         155
Trans Nzoia                447        464       481        499         516        534        551       569      587         604
Turkana                    192        195       197        199         201        203        204       205      206         206
Uasin Gishu                509        528       547        566         585        604        623       642      661         680
West Pokot                 252        259       267        275         282        289        297       304      311         318
Rift Valley               5555       5763      5976       6190        6405       6621       6836      7055     7273        7489

Bungoma                    827        858       889        920         951        982       1014      1045     1076        1108
Busia                      435        446       458        469         480        491        502       512      522         532
Kakamega                  1588       1638      1689       1739        1788       1838       1887      1935     1983        2031
Western                   2850       2942      3036       3128        3219       3311       3403      3492     3581        3671

NATIONAL                24476       25236     26001      26762       27520      28266      29011     29745    30470       31187


CBS: Kenya Population Cencus 1989, Analytical Report Vol V11




                                                                                                                                  71
                              Table 1.7: Population projections for provinces and districts (thousands)
                                                  medium fertility decline – males

     Province/District      1991       1992      1993       1994        1995       1996       1997         1998    1999    2000

     Nairobi                 889        928       967       1007        1048       1089       1130         1172    1214    1256
     Kiambu                  525        540       554        568         583        596        610          623     636     649
     Kirinyaga               208        213       217        222         227        231        235          239     243     247
     Murang’a                443        453       462        472         481        489        498          506     513     520
     Nyandarua               177        182       187        192         197        202        206          211     216     220
     Nyeri                   326        333       339        345         351        356        362          367     371     376
     Central                1679       1721      1759       1799        1839       1874       1911         1946    1979    2012

     Kilifi                  315        324       333        342         351        360        369          377     385     394
     Kwale                   208        213       218        223         228        233        237          242     246     250
     Lamu                     34         35        36         37          38         39         40           41      42      43
     Mombasa                 288        296       304        312         320        327        335          342     350     357
     Taita Taveta            106        109       111        114         116        119        121          124     126     128
     Tana River               75         77        79         82          84         87         89           91      94      96
     Coast                  1026       1054      1081       1110        1137       1165       1191         1217    1243    1268

     Embu                    197        203       208        214         220        225        231          236     241     247
     Isiolo                   40         42        44         45          47         49         51           53      54      56
     Kitui                   339        349       360        370         381        391        401          411     421     431
     Machakos                749        770       790        811         831        851        871          890     909     927
     Marsabit                 72         74        76         78          79         81         83           84      86      87
     Meru                    636        655       674        693         712        731        749          767     785     803
     Eastern                2033       2093      2152       2211        2270       2328       2386         2441    2496    2551

     Garissa                 103        106       108        111          113       116        118         121     123      125
     Mandera                  99        104       108        113          117       122        126         131     136      141
     Wajir                   102        104       106        108          110       112        114         115     117      118
     North-Eastern           304        314       322        332          340       350        358         367     376      384

     Kisii                   704        724       743        763         783        802        821          839     858     876
     Kisumu                  393        404       415        426         436        447        457          468     478     487
     Siaya                   324        330       336        342         347        352        357          362     367     371
     South-Nyanza            651        669       687        705         722        739        756          773     790     806
     Nyanza                 2072       2127      2181       2236        2288       2340       2391         2442    2493    2540

     Baringo                 162        168       173        178         183        188        193          198     203     208
     Elgeyo-Marakwet         119        123       126        130         134        138        142          146     149     153
     Kajiado                 148        155       162        170         178        186        194          202     210     219
     Kericho                 543        562       582        602         622        643        663          683     703     724
     Laikipia                126        131       136        142         147        153        158          164     170     176
     Nakuru                  482        502       523        543         564        585        607          628     650     672
     Nandi                   250        258       267        275         284        292        301          309     318     326
     Narok                   216        227       239        251         263        276        289          302     316     329
     Samburu                  60         63        65         67          69         71         73           75      77      79
     Trans-Nzoia             225        234       242        251         259        268        276          285     294     302
     Turkana                  91         92        93         93          93         94         94           93      93      93
     Uashin-Gishu            262        271       281        291         300        310        320          330     340     350
     West-Pokot              126        130       134        138         142        146        150          153     157     161
     Rift Valley            2810       2916      3023       3131        3238       3350       3460         3568    3680    3792

     Bungoma                 404        418       433        448         463        479        494          509     524     539
     Busia                   205        210       216        221         226        231        237          241     246     251
     Kakamega                757        781       805        829         853        877        901          925     948     971
     Western                1366       1409      1454       1498        1542       1587       1632         1675    1718    1761

     NATIONAL              12179      12562     12939      13324       13702      14083      14459        14828   15199   15564

     CBS: Kenya Population Census 1989,Analytical Report Vol VII




72
          Table 1.8: Population projections for provinces and districts (thousands) medium fertility decline females

Provinces/Districts     1991        1992      1993      1994         1995      1996       1997      1998      1999      2000

Nairobi                  675         708      741        774          809       843        878       914      950        987
Kiambu                   518         532      546        560          573       586        599       611      623        635
Kirinyaga                209         214      218        222          226       230        234       237      240        243
Murang’a                 473         482      492        501          509       517        525       532      539        545
Nyandarua                181         186      192        196          201       206        211       215      220        224
Nyeri                    342         348      353        359          364       369        373       377      381        384
Central                 1723        1762     1801       1838         1873      1908       1942      1972     2003       2031

Kilifi                   343         353      362        371          381       390        398       407      415        424
Kwale                    220         226      231        237          243       248        253       259      264        269
Lamu                      31          32       33         34           35        35         36        37       38         38
Mombasa                  229         235      241        247          253       259        265       270      276        281
Taita Taveta             109         111      114        116          119       121        123       125      127        129
Tana River                73          75       77         80           82        84         86        88       90         93
Coast                   1005        1032     1058       1085         1113      1137       1161      1186     1210       1234

Embu                     205         211      217        222          228       233        239       244      249        254
Isiolo                    38          39       41         43           44        46         47        49       50         52
Kitui                    377         388      398        408          419       428        438       447      457        466
Machakos                 799         821      842        863          884       904        924       944      963        981
Marsabit                  71          73       74         76           78        80         81        83       85         86
Meru                     654         673      693        712          731       750        768       786      804        821
Eastern                 2144        2205     2265       2324         2384      2441       2497      2553     2608       2660

Garissa                   95          98       101       104          107        110       113        115      118       121
Mandera                   91          95        98       102          106        110       113        117      121       125
Wajir                     95          97        99       101          103        105       107        109      110       112
North-Eastern            281         290       298       307          316        325       333        341      349       358

Kisii                    757         780      803        826          848       870        892       914      935        955
Kisumu                   399         410      421        431          442       452        462       471      481        490
Siaya                    375         381      386        392          397       401        405       409      412        415
South Nyanza             709         730      751        771          792       812        831       850      869        888
Nyanza                  2240        2301     2361       2420         2479      2535       2590      2644     2697       2748

Baringo                  164         160      174        179          184       189        194       199      204        209
Elgeyo Marakwet          120         124      128        132          136       140        143       147      151        154
Kajiado                  136         142      148        154          160       166        173       179      185        192
Kericho                  521         540      559        578          597       616        634       653      672        690
Laikipia                 121         127      132        138          143       149        155       161      167        173
Nakuru                   465         485      505        526          547       568        590       611      633        655
Nandi                    244         253      261        270          279       287        296       304      312        321
Narok                    216         227      238        250          262       274        287       299      312        325
Samburu                   62          64       65         67           69        70         72        74       75         77
Trans Nzoia              222         231      239        248          257       266        275       284      293        302
Turkana                  101         103      105        106          108       109        111       112      113        113
Uasin Gishu              247         257      266        275          284       294        303       312      321        330
West Pokot               126         129      133        137          140       144        147       151      154        157
Rift Valley             2745        2842     2953       3060         3166      3272       3380      3486     3592       3698

Bungoma                  424         440      456        472          488       504        520       536      552        568
Busia                    230         236      242        248          254       259        265       270      276        281
Kakamega                 831         857      883        909          935       961        986      1011     1035       1060
Western                 1485        1533     1581       1629         1677      1724       1771      1817     1863       1909

NATIONAL               12298      12673     13058      13437       13817      14185      14552     14913    15272      15625



CBS: Kenya Population Cencus 1989, Analytical Report Vol VIII




                                                                                                                               73
                     Table 1.9: Nutritional stunting (moderate malnutrition) among under -fives in Kenya (% Stunted)

     Province                    1977              1979                    1982               1987                 1994          1998
     National                      24                 27                     37                 32                   34          33.0
     Coast                         14                 40                     49                 50                   38          39.0
     Eastern                       34                 24                     39                 39                   39          37.0
     Central                       26                 21                     34                 25                   29          28.0
     Rift Valley                   25                 24                     31                 27                   32          33.0
     Nyanza                        21                 34                     43                 41                   36          31.0
     Western                       16                 24                     41                 22                   37          35.0
     North Eastern                  -                  -                      -                  -                   26             -
     Nairobi                        -                  -                      -                  -                   30          26.0
     Republic of Kenya’s, Kenya’s Programme for Action for Children in the 1990s; KDHS (1998)




                          Table 2.0: Distribution of nutrition status indicators in 1982,1987,1994 and 1997 by district

                                            Per cent Stunted <-2SD HA Median                           Per cent Wasted <-2SD WH Median
     Province /District          1982             1987             1994               1997            1982                1987   1994
     Baringo                      31.1             24.9             33.1              22.8              9.9                5.9   11.3
     Bomet                           -                -             38.0              30.7                -                  -    2.0
     Bungoma                      38.4             22.8             41.7              21.4              2.0                1.7    6.3
     Busia                        42.2             27.0             38.7              30.2              4.4                6.4    9.2
     Central                      33.6             25.0             28.7              21.2              4.0                2.5    4.9
     Coast                        48.6             49.5             38.3              20.6              3.5                3.7    7.8
     Eastern                      39.0             38.5             38.5              20.1              3.5                3.7    7.8
     Elgeyo Marakwet              27.9             15.0             30.9              15.1              4.0                2.9    8.0
     Embu                         41.3             30.1             35.5              10.8              3.0                5.4    6.4
     Garissa                         -                -             36.0                 -                -                  -   33.4
     Homa Bay                     37.6             44.8             41.6              23.6              4.4                7.8    6.0
     Isiolo                          -                -             29.0              13.9                -                  -    9.2
     Kajiado                      31.0             24.7             31.8              17.0              5.0                9.9    9.1
     Kakamega                     40.9             18.4             40.7              17.8              3.2                2.8    7.7
     Kericho                      32.0             45.8             39.3              14.7              5.9                1.8    2.8
     Kiambu                       31.0             17.9             32.1              29.5              1.9                1.1    5.6
     Kilifi                       52.9             51.7             49.5              29.7              7.7                4.5    6.8
     Kirinyaga                    39.9             15.3             16.7              21.4              3.7                2.7    5.0
     Kisii                        50.8             44.4             40.6              19.8              5.0                3.4    6.2
     Kisumu                       30.8             38.2             31.6              17.9              7.2                6.3    8.7
     Kitui                        45.8             37.8             45.8              25.2              2.6                4.7    4.0
     Kwale                        54.8             56.1             53.0              23.9              6.1                6.7    5.2
     Laikipia                     31.1             25.7             32.4              14.8              9.9                8.2    7.3
     Lamu                         52.9                -             24.3               9.6              7.7                  -    1.3
     Machakos                     39.4             45.9             39.7              21.9              3.2                2.1   11.3
     Makueni                         -                -             50.0                 -                -                  -    2.7
     Mandera                         -                -             20.4                 -                -                  -   27.7
     Marsabit                        -                -             39.0                 -                -                  -   13.0
     Meru                         32.7             38.0             37.7              16.6              4.6                3.9    3.8
     Migori                          -                -             44.8              22.6                -                  -    6.1
     Mombasa                         -                -             36.9              11.2                -                  -    9.6
     Murang’a                     35.8             24.9             32.4              20.6              5.2                5.3    6.0
     Nairobi                         -                -             30.2              16.2                -                  -    5.5
     Nakuru                       50.9             37.3             39.7              16.2              3.1                3.7    5.8
     Nandi                        19.1             22.8             29.4              15.8              5.7                2.6    5.2
     Narok                        31.0             59.7             40.4              16.9              5.0                6.4    1.7
     National                     37.1             32.1             33.6              18.5              4.5                4.0    7.8
     North-Eastern                   -                -             26.4               7.2                -                  -   25.4
     Nyamira                         -                -             31.8              17.7                -                  -    6.0
     Nyandarua                    27.9             27.0             30.6              14.6              3.7                1.1    5.3
     Nyanza                       43.1             41.3             36.4              19.3              5.5                6.2    5.5
     Nyeri                        32.5             32.6             27.2              20.2              4.8                2.7    2.4
     Rift Valley                  31.4             26.9             31.8              17.1              5.4                4.6    8.2
     Samburu                         -                -             40.4                 -                -                  -   30.3
     Siaya                        49.7             33.7             33.8              18.9              8.4               11.7    3.8
     Taita Taveta                 30.0             41.2             23.6              18.4              6.7                4.6    7.5
     Tana River                   52.9                -             33.4              25.2              7.7                  -   17.5
     Tharaka Nithi                   -                -             24.0              26.8                -                  -    2.9
     Trans-Nzoia                  32.4             11.5             29.8              16.4              6.5                5.0    9.1
     Turkana                         -                -             27.7                 -                -                  -   15.2
     Uasin Gishu                  27.0              7.9             23.8              15.6              4.2                5.8   10.1
     Vihiga                          -                -             26.4              17.6                -                  -   12.5
     Wajir                           -                -             29.2              17.0                -                  -   15.6
     West Pokot                   27.9                -             41.4              27.8              4.0                  -    9.0
     Western                      40.5             22.4             37.0              22.0              3.0                3.5    8.0
     CBS/UNICEF:5th Nutrition Survey,1994




74
                                         Table 2.1: Key Education indicators for selected years

                 Indicator                               1994              1995              1996              1997            1998           1999*

Number Of Pre-Primary Schools                          19083.0          20186.0         21261.0            23344.0        23997.0        25429.0
Number Of Primary Schools                              15906.0          16115.0         16552.0            17080.0        17356.0        17623.0
Number Of Secondary                                     2834.0           2878.0          3004.0             3028.0         3081.0         3197.0
Enrolment in Pre-Primary Schools                      951997.0         988826.0       1033367.0          1064053.0      1076606.0      1063883.0
Per cent Girls Enrolled                                   49.0             48.7            49.0               49.2           48.5           48.8
Enrolment in Primary Schools                         5557008.0        5536400.0       5597700.0          5677300.0      5919600.0      5867800.0
Per cent Girls Enrolled                                   49.3             49.4            49.2               49.2           49.4           49.0
Enrolment In Secondary Schools                        619839.0         632388.0        658253.0           687473.0       700538.0       638509.0
Per cent Females Enrolled                                 45.7             45.9            46.4               47.1           46.7           47.2
Gross Enrolment rate in pre-primary schools               35.1                -            35.7               35.6           34.9
Gross Enrolment rate in primary schools                   82.2                -            77.5                                                 68.2
Gross Enrolment rate in secondary schools                 22.9             22.2            22.7                23.2             23.2            18.7
Adult literacy rate                                       75.0
Gross admission rate in primary schools                                    120.6             117.2            115.0            114.0           109.3
Pupil Teacher ratio in pre-primary schools                  34.0            34.0              31.0             28.5             29.1            26.1
Pupil Teacher ratio in primary schools                      31.0            30.0              30.0             30.4             33.1            33.1
Pupil Teacher ratio in secondary schools                    16.0            15.0              16.0             15.5             17.3            16.0
Completion rate in primary schools                          43.4               -              44.3             46.1             47.2            47.7
Completion rate in secondary schools                        88.3            84.5              79.4                -                -               -

CBS: Economic Survey, Various issues;and Ministry of Education
*Provisional




                                       Table 2.2: Key Education Indicators by Gender, 1989-1999

       Pre-school      Gross Admission rate      Gross Primary School          Primary School           Secondary School       Secondary School
          GRE          in Primary School by        Enrolment Rate             Completion Rate            Gross Enrolment        Completion Rate
                              sex (%)                 by Sex (%)                  by Sex (%)             Rate by Sex (%)*         by Sex (%)

Year                 Male     Female     Total   Male Female       Total   Male    Female    Total    Male    Female   Total   Male Female Total

1989      34.7       138.4     132.1     135.2                             47.9     43.2     45.6      36.7    24.8    30.7
1990      35.4       135.4     128.7     132.1   104.0   99.6      101.8   45.7     40.5     43.2      34.7    25.8    30.2    86.7    86.0     86.4
1991      35.0       129.7     122.9     126.3   93.4    89.5       91.4   46.4     41.6     44.1      32.8    25.3    29.0    78.5    77.9     78.2
1992      33.7       127.1     121.1     124.2   92.0    90.0       91.0   44.7     48.2     46.4      32.5    25.2    28.8    82.3    85.0     83.4
1993      35.2       122.0     116.3     119.2   88.9    86.7       87.8   44.5     42.2     43.4      26.2    20.9    23.5    70.7    66.6     68.9
1994      35.1       123.4     117.8     120.6   89.1    87.8       88.5   44.6     43.0     43.9      28.9    24.3    26.6    82.3    81.9     82.1
1995      35.3       120.5     113.9     117.2   87.4    86.3       86.8   43.0     42.1     42.6      24.0    20.5    22.2    76.2    78.2     77.1
1996      35.7       120.5     113.9     117.2   87.3    85.5       86.4   45.1     43.5     44.3      24.2    21.1    22.7    95.8    94.9     95.4
1997      35.6       117.8     112.1     115.0   88.7    86.6       87.7   46.3     45.8     46.1      24.5    21.9    23.2    88.6    87.9     88.3
1998      34.9       117.1     111.0     114.0                             46.4     48.1     47.2      24.6    21.7    23.2    85.8    83.1     84.5
1999                 112.0     106.6     109.3   88.3    85.8      87.1    47.6     47.7     47.7      21.4    16.4    18.7    80.9    77.7     79.4

*There is a change in data source in 1995 making for non-comparability
Ministry of Education: Statistics Section




                                        Table 2.3: Adult education enrolment by sex, 1989-1999

                     Year                Male              Female                   Total            % of Female Enrolment

                     1989               33,548             100,383                 133,931                    75.0
                     1990               32,696             105,458                 138,154                    76.3
                     1991               34,709             104,867                 139,576                    75.1
                     1992               25,425             84,049                  109,474                    76.8
                     1993               26,027             81,271                  107,298                    75.7
                     1994               26,595             87,684                  114,279                    76.7
                     1995               27,572             88,479                  116,051                    76.2
                     1996               26,612             89,029                  115,641                    77.0
                     1997               28,139             73,215                  101,354                    72.2
                     1998               26,190             74,081                  100,271                    73.9
                     1999               24,955             65,731                  90,686                     72.5

                     CBS, Economic Survey- various issues




                                                                                                                                                       75
                     Table 2.4: Percentage distribution of household members who never attended school

     Region                      Number                 N-Poor              Number             Poor      Total

     Nairobi                     1117216                   4.7              384935             10.2       6.1
     Kiambu                       558560                   6.8              231754             11.7       8.2
     Kirinyaga                    201438                   9.7              110237             14.2      11.3
     Muranga                      434786                   7.5              258185             11.7       9.1
     Nyandarua                    168162                   7.7              104987             14.2      10.2
     Nyeri                        371951                   8.5              134018             10.1       8.9
     CENTRAL                     1734897                   7.7              839182             12.1       9.1
     Kilifi                       206347                  33.7              374413               45      41.0
     Kwale                        220518                  43.6              152858             60.1      50.4
     Lamu                          44803                  26.7               13505             25.1      26.3
     Mombasa                      292211                    12              153938             13.1      12.4
     Taita Taveta                  97881                  13.5              102509               21      17.3
     Tana River                    45021                  44.9               86152             59.7      54.6
     COAST                        906781                  27.2              883375             40.4      33.7
     Embu                         122540                  11.3              198951             18.6      15.8
     Isiolo                        18088                  26.2               50771             40.5      36.7
     Kitui                        289788                  24.1              348254             30.6      27.6
     Machakos                     260494                  12.5              499747             24.8      20.6
     Marsabit                      26613                  49.3              104618             84.9      77.7
     Meru                         507552                  18.1              234892             25.2      20.3
     Makueni                      146644                    13              458198             19.6      18.0
     Tharaka Nithi                147206                    10              139459              9.7       9.9
     EASTERN                     1518924                  17.1             2034891             26.5      22.5
     Garissa                      107709                  72.1               77416             85.1      77.5
     Mandera                       75745                  58.5               99310             80.5      71.0
     Wajir                         73693                  77.7               97515             89.6      84.5
     NORTH EASTERN                257148                  69.7              274242               85      77.6
     Kisii                        569540                  19.4              273141             17.2      18.7
     Kisumu                       363319                  17.8              323893             20.5      19.1
     Siaya                        333202                  26.4              299836             26.8      26.6
     Homa Bay                     354328                  25.4              295049             30.1      27.5
     Migori                       344347                  25.1              182855             34.9      28.5
     Nyamira                      202773                  19.9              230890             21.1      20.5
     NYANZA                      2167510                  22.1             1605664             24.6      23.2
     Kajiado                      198706                  35.4               59580             41.4      36.8
     Kericho                      220862                    19              330007               20      19.6
     Laikipia                     107529                   9.9               88806             23.5      16.1
     Nakuru                       572979                  18.9              319170             23.7      20.6
     Nandi                        259680                    12              175479             22.9      16.4
     Narok                        291098                  38.2              111189             59.8      44.2
     Bomet                        203722                  20.8              182733             21.8      21.3
     Baringo                      167814                  19.1              119492             24.9      21.5
     Elgeyo Marakwet              150998                  17.1               58909             25.9      19.6
     Samburu                       20052                  43.1               98427               79      72.9
     Trans Nzoia                  214044                  12.2              180881             20.1      15.8
     Turkana                       39272                  51.5              125377             68.3      64.3
     Uasin Gishu                  318520                  13.9              142612             22.7      16.6
     West Pokot                   101932                  49.1              104189             54.4      51.8
     RIFT VALLEY                 2867208                  21.7             2096852             31.8      26.0
     Bungoma                      347533                  11.3              408952               17      14.4
     Busia                        165179                    20              216693             28.1      24.6
     Kakamega                     436751                  15.4              451313             22.3      18.9
     Vihiga                       248679                  13.1              289414             15.3      14.3
     WESTERN                     1198142                  14.4             1366372             20.2      17.5
     Rural                       9380978                    21             8493712             29.3      24.9
     Urban                       2386847                   7.3              991801             12.5       8.8

     Total                      11767825                  18.2             9485513             27.5      22.4

     Source: First Report on Poverty in Kenya (1998) Volume II Annex Table 4.1




76
            Table 2.5: Per centage distribution of household members by region and education level sec+

Region                      Number                 N-Poor               Number             Poor           Total

Nairobi                     1094356                  51.1               352010                34          46.9
Kiambu                        52910                  40.2               206231              18.4          22.9
Kirinyaga                    183596                  26.3                95737              12.3          21.5
Muranga                      418396                  21.3               233541               9.9          17.2
Nyandarua                    159819                  18.9                91575                11          16.0
Nyeri                        348235                  28.8               122032              19.9          26.5
CENTRAL                     1639255                  29.1               749117              14.3          24.5
Kilifi                       138578                  20.4               207333               8.1          13.0
Kwale                        126926                  22.4                61319              13.6          19.5
Lamu                          34134                  18.8                10485              11.4          17.1
Mombasa                      266588                  35.4               134292              22.7          31.1
Taita Taveta                  85713                  15.9                81923               9.9          13.0
Tana River                    25046                    21                35370              14.6          17.3
COAST                        676985                  26.1               530722              13.2          20.4
Embu                         110868                  24.7               163625              15.1          19.0
Isiolo                        13635                  28.1                30786              13.7          18.1
Kitui                        222519                  21.3               242952              13.8          17.4
Machakos                     231135                  33.1               378430              13.5          20.9
Marsabit                      14159                   8.4                16024                 9           8.7
Meru                         417059                  25.6               175668              16.6          22.9
Makueni                      130314                  24.9               370031              17.1          19.1
Tharaka Nithi                133227                  25.3               127094               7.6          16.7
EASTERN                     1272917                  25.9              1504611              14.4          19.7
Garissa                       30590                  25.8                11501               6.6          20.6
Mandera                       32342                  35.5                19408               2.3          23.0
Wajir                         16684                  13.3                10317               5.2          10.2
NORTH EASTERN                 79615                  27.1                41225               4.1          19.3
Kisii                        464094                  28.1               227463              17.3          24.5
Kisumu                       302889                  26.8               261752              14.4          21.1
Siaya                        246314                  12.2               219450               8.5          10.5
Homa Bay                     268166                  12.3               207352               8.2          10.5
Migori                       260689                  10.7               119631               8.4          10.0
Nyamira                      163271                  27.7               183760              18.8          23.0
NYANZA                      1705422                  20.5              1219408              12.8          17.3
Kajiado                      130817                  25.2                35309              10.4          22.1
Kericho                      180983                  15.5               270118              10.8          12.7
Laikipia                     100671                  22.1                68228               8.2          16.5
Nakuru                       470591                    24               245319              11.2          19.6
Nandi                        236215                  24.1               138012               6.2          17.5
Narok                        182999                  11.7                44685               5.7          10.5
Bomet                        162657                  23.7               142923              17.3          20.7
Baringo                      140119                  21.5                92030              16.2          19.4
Elgeyo Marakwet              126669                  18.8                43937               8.9          16.3
Samburu                       11698                  25.3                21612               6.4          13.0
Trans Nzoia                  188351                  23.4               144499               7.6          16.5
Turkana                       21124                  14.8                42296              10.9          12.2
Uasin Gishu                  276920                  24.8               110477              16.8          22.5
West Pokot                    53292                  20.4                47509               3.2          12.3
RIFT VALLEY                 2283107                  21.7              1446955              10.8          17.5
Bungoma                      312354                  25.9               345198                17          21.2
Busia                        135324                    26               156627               9.1          16.9
Kakamega                     375197                  30.7               352886              16.1          23.6
Vihiga                       220076                  15.4               246049               7.6          11.3
WESTERN                     1042950                  25.4              1100760              13.6          19.3
Rural                       7518820                  21.7              6064722              11.9          17.3
Urban                       2275787                  46.1               880086              28.4          41.2

Total                       9794606                  27.3              6944807             14.1           21.8

Source: First Report on Poverty in Kenya - Volume II (1998) Annex Table 4.2




                                                                                                                  77
                                        Table 2.6: Distribution of land per population by region

     Region                                                        Population          Land Km2              L/P * 1000

     Nairobi                  1117216              384935           1502151                 684                  0.5
     Kiambu                    558560              231754            790314                2448                  3.1
     Kirinyaga                 201438              110237            311675                1437                  4.6
     Muranga                   434786              258185            692971                2476                  3.6
     Nyandarua                 168162              104987            273149                3528                 12.9
     Nyeri                     371951              134018            505969                3284                  6.5
     CENTRAL                  1734897              839182           2574079               13173                  5.1
     Kilifi                    206347              374413            580760               12414                 21.4
     Kwale                     220518              152858            373376                8257                 22.1
     Lamu                       44803               13505             58308                6506                111.6
     Mombasa                   292211              153938            446149                 210                  0.5
     Taita Taveta               97881              102509            200390               16959                 84.6
     Tana River                 45021               86152            131173               38694                295.0
     COAST                     906781              883375           1790156               83040                 46.4
     Embu                      122540              198951            321491                2714                  8.4
     Isiolo                     18088               50771             68859               25605                371.8
     Kitui                     289788              348254            638042               29389                 46.1
     Machakos                  260494              499747            760241               14178    1365083      10.4
     Marsabit                   26613              104618            131231               73952                563.5
     Meru                      507552              234892            742444                9922    1029109       9.6
     Makueni                   146644              458198            604842
     Tharaka Nithi             147206              139459            286665
     EASTERN                  1518924             2034891           3553815              155760                 43.8
     Garissa                   107709               77416            185125               43931                237.3
     Mandera                    75745               99310            175055               26470                151.2
     Wajir                      73693               97515            171208               56501                330.0
     NORTH EASTERN             257148              274242            531390              126902                238.8
     Kisii                     569540              273141            842681                1976    1276344       1.5
     Kisumu                    363319              323893            687212                2093                  3.0
     Siaya                     333202              299836            633038                2523                  4.0
     Homa Bay                  354328              295049            649377                5714    1176579       4.9
     Migori                    344347              182855            527202
     Nyamira                   202773              230890            433663
     NYANZA                   2167510             1605664           3773174               12526                  3.3
     Kajiado                   198706               59580            258286               20963                 81.2
     Kericho                   220862              330007            550869                4890    937324        5.2
     Laikipia                  107529               88806            196335                9718                 49.5
     Nakuru                    572979              319170            892149                7024                  7.9
     Nandi                     259680              175479            435159                2745                  6.3
     Narok                     291098              111189            402287               18513                 46.0
     Bomet                     203722              182733            386455
     Baringo                   167814              119492            287306               10627                 37.0
     Elgeyo Marakwet           150998               58909            209907                2722                 13.0
     Samburu                    20052               98427            118479               20809                175.6
     Trans Nzoia               214044              180881            394925                2468                  6.2
     Turkana                    39272              125377            164649               61769                375.2
     Uasin Gishu               318520              142612            461132                3784                  8.2
     West Pokot                101932              104189            206121                5076                 24.6
     RIFT VALLEY              2867208             2096852           4964060              171108                 34.5
     Bungoma                   347533              408952            756485                3074                  4.1
     Busia                     165179              216693            381872                1629                  4.3
     Kakamega                  436751              451313            888064                3520    1426157       2.5
     Vihiga                    248679              289414            538093
     WESTERN                  1198142             1366372           2564514                8223                  3.2
     Rural                    9380978             8493712          17874690
     Urban                    2386847              991801           3378648

     Total                   11767825             9485513          21253338             571416                  26.9

     Sources: First Report on Poverty in Kenya - Volume II Annex Table 4.1
     Statistical Abstract 1995 Tables 5 and 68




78
            Table 2.7: Percentage distribution of population 6 years + who never attended school in 1997

Region                     Number                N-Poor              Number                 Poor           Total

Nairobi                     791126                  3.0               816404                  6.2           4.6
Kiambu                      777372                  8.1               273863                 10.2           8.6
Kirinyaga                   254996                 11.2               146292                 15.6          12.8
Muranga                     530164                 11.7               337360                 11.9          11.8
Nyandarua                   234790                  7.3               100017                 12.5           8.9
Nyeri                       413557                  8.8               192512                 10.5           9.3
CENTRAL                    2210878                  9.4              1050046                 11.7          10.1
Kilifi                      194886                 25.2               392589                 45.7          38.9
Kwale                       148647                 31.9               240866                 44.7          39.8
Lamu                         39568                 18.4                22724                 38.6          25.8
Mombasa                     282880                  7.8               179588                 15.9          10.9
Taita Taveta                 62315                  6.7               126367                 14.9          12.2
Tana River                   30610                 60.5                20042                 37.3          51.3
COAST                       758904                 19.6               982175                 35.7          28.7
Mbere                        62943                  9.9                70953                 16.9          13.6
Embu                         92025                  9.0               105449                 16.7          13.1
Isiolo                        7047                  0.0                 9273                 25.2          14.3
Kitui                       203692                 20.8               381682                 28.6          25.9
Machakos                    272025                  9.7               484799                 16.5          14.1
Marsabit
Meru                        191743                  9.0               142741                 17.3          12.5
Makueni                     142755                 14.6               391456                 18.8          17.7
Tharaka Nithi               118479                 13.9               149867                 16.1          15.1
Nyabene                     323486                 26.0               298082                 28.8          27.3
EASTERN                    1414195                 15.7              2034302                 21.1          18.9
Garissa                      12046                 67.4                31409                 41.1          48.4
Mandera
Wajir                          660                 31.2                 1443                 37.1          35.2
NORTH EASTERN                12706                 65.5                32852                 41.0          47.8
Kisii                       276989                 10.9               403690                 15.1          13.4
Kisumu                      216611                 13.8               407237                 15.9          15.2
Siaya                       248560                 27.3               366574                 25.2          26.0
Homa Bay                     99581                 15.9               344471                 22.5          21.0
Migori                      302344                 13.4               415652                 20.8          17.7
Nyamira                     275756                 21.6               565759                 22.0          21.9
NYANZA                     1419842                 17.2              2503384                 20.2          19.1
Kajiado                     184767                 36.0                86151                 34.7          35.6
Kericho                     267722                 11.2               273591                 17.2          14.2
Laikipia                    156621                 11.9                94892                 16.1          13.5
Nakuru                      533265                  9.8               432868                 17.8          13.4
Nandi                       168039                 15.2               293094                 19.0          17.6
Narok                       113214                 30.6               119365                 25.9          28.2
Bomet                       178372                 11.4               292765                 17.4          15.1
Trans Mara                   82461                 42.2               105884                 40.5          41.2
Baringo                     190231                 20.0               114599                 20.9          20.3
Elgeyo Marakwet             121641                 15.2               111168                 20.3          17.6
Samburu
Trans Nzoia                 191530                 13.9               224858                 19.6          17.0
Turkana
Uasin Gishu                 260887                  7.5               233885                 16.6          11.8
West Pokot                   66836                 35.6               140997                 52.1          46.8
RIFT VALLEY                2515582                 16.3              2524115                 21.9          19.1
Bungoma                     316004                 10.1               411630                 15.8          13.3
Busia                       120158                 16.8               234742                 30.9          26.1
Kakamega                    413444                 14.3               536436                 16.1          15.3
Vihiga                      201392                 12.6               334374                 16.1          14.8
WESTERN                    1050998                 13.0              1517182                 18.3          16.1
Rural                      8492928                 15.5              9790031                 22.0          19.0
Urban                      1681303                  5.0              1670429                  8.9           6.9

Total                     10174231                 13.8            11460460                  20.1          17.1

Source: WMS III (1997) Unpublished data




                                                                                                                   79
             Table 2.8: Percentage distribution of population 6 years + by region and education level secodary + in 1997

     Region                        Number                N-Poor              Number                 Poor              Total

     Nairobi                        798745                 48.8               778281                 23.4             36.3
     Kiambu                         727907                 30.3               248576                 15.0             26.4
     Kirinyaga                      228688                 18.8               124185                  7.6             14.9
     Muranga                        477422                 18.4               302001                 10.9             15.5
     Nyandarua                      223432                 19.7                87805                  7.1             16.1
     Nyeri                          385898                 31.5               173963                 16.6             26.9
     CENTRAL                       2043347                 25.3               936530                 12.2             21.2
     Kilifi                         148744                 25.6               215804                  7.5             14.9
     Kwale                          101286                 13.8               133203                  5.5              9.1
     Lamu                            33207                 26.1                14878                  2.0             18.6
     Mombasa                        271214                 50.7              1522951                 24.1             28.1
     Taita Taveta                    58976                 27.1               110358                 11.9             17.2
     Tana River                      12090                 18.9                12685                 14.7             16.7
     COAST                          625516                 34.6               639878                 11.8             23.1
     Mbere                           58669                 24.3                 5898                 15.9             23.5
     Embu                            85398                 37.5                90489                 13.1             24.9
     Isiolo                           7047                 47.7                 7133                 15.0             31.3
     Kitui                          165519                 19.5               277669                  7.4             11.9
     Machakos                       250326                 20.1               409756                 13.2             15.8
     Marsabit
     Meru                           177994                 29.1               119903                 23.0             26.6
     Makueni                        125541                 25.2               324163                 11.0             15.0
     Tharaka Nithi                  103631                 23.7               127538                 15.9             19.4
     Nyambene                       239762                  6.9               213586                  4.0              5.5
     EASTERN                       1213886                 21.1              1629225                 11.6             15.7
     Garissa                          3928                 79.6                19392                 31.8             39.9
     Mandera
     Wajir                             454                 18.1                  907                  4.5              9.0
     NORTH EASTERN                    4382                 73.2                19392                 30.5             38.4
     Kisii                          250482                 29.0               344371                 21.3             24.5
     Kisumu                         195297                 27.2               350334                 16.2             20.1
     Siaya                          183152                 13.1               278386                  9.8             11.1
     Homa Bay                        83839                 19.6               267956                  5.4              8.8
     Migori                         267410                 13.9               332816                  8.5             10.9
     Nyamira                        216782                 38.4               441063                 21.8             27.3
     NYANZA                        1196963                 23.9              2014926                 14.7             18.1
     Kajiado                        122823                 26.0                56654                  9.7             20.9
     Kericho                        240879                 19.4               227179                  5.8             12.8
     Laikipia                       141003                 19.5                81862                 14.1             17.5
     Nakuru                         493656                 27.5               367113                 13.4             21.5
     Nandi                          145841                 25.5               242257                 11.0             16.4
     Narok                           79894                 25.6                89315                  2.9             13.6
     Bomet                          160441                 27.2               243259                 11.7             17.9
     Trans Mara                      48639                 28.2                64897                  3.9             14.3
     Baringo                        156173                 19.5                91263                  7.8             15.2
     Elgeyo Marakwet                104637                 17.5                89350                  8.7             13.4
     Samburu
     Trans Nzoia                    168344                 26.9               183743                 12.1             19.2
     Turkana
     Uasin Gishu                    244833                 28.1               196820                 20.1             24.5
     West Pokot                      43222                 21.5                68689                 13.6             16.7
     RIFT VALLEY                   2150384                 24.6              2002402                 11.3             18.2
     Bungoma                        289644                 27.7               350887                 17.7             22.2
     Busia                          103236                 14.0               165185                  6.9              9.6
     Kakamega                       354828                 29.2               453930                 14.0             20.7
     Vihiga                         176071                 19.6               281998                 13.9             16.1
     WESTERN                        923779                 25.2              1252001                 14.1             18.8

     Rural                         7300866                 22.3              7721369                 11.1             16.5
     Urban                         1656136                 48.7              1551267                 26.4             37.9

     Total                         8957002                 27.2              9272637                 13.6             20.3

     Source: WMS III (1997) Unpublished data




80
                              Table 2.9: Distribution of land per population by region in 1997

Region                                                       Population          Land Km2                  L/P * 1000

Nairobi                   791126              816404          1607530                 684                      0.4
Kiambu                    777372              273863          1051235                2448                      2.3
Kirinyaga                 254996              146292           401288                1437                      3.6
Muranga                   530164              337360           867524                2476                      2.9
Nyandarua                 234790              100017           334807                3528                     10.5
Nyeri                     413557              192512           606069                3284                      5.4
CENTRAL                  2210878             1050046          3260924               13173                      4.0
Kilifi                    194886              392589           587475               12414                     21.1
Kwale                     148647              240866           389513                8257                     21.2
Lamu                       39568               22724            62292                6506                    104.4
Mombasa                   282880              179588           462468                 210                      0.5
Taita Taveta               62315              126367           188682               16959                     89.9
Tana River                 30610               20042            50652               38694                    763.9
COAST                     758904              982175          1741079               83040                     47.7
Mbere                      62943               70953           133896
Embu                       92025              105449           197474                2714        197624      13.7
Isiolo                      7047                9273            16320               25605                  1568.9
Kitui                     203692              381682           585374               29389                    50.2
Machakos                  272025              484799           756824               14178        1291035     11.0
Marsabit
Meru                      191743              142741           334484                9922        1224398       8.1
Makueni                   142755              391456           534211
Tharaka Nithi             118479              149867           268346
Nyambene                  323486              298082           621568
EASTERN                  1414195             2034302          3448497              155760                     45.2
Garissa                    12046               31409            43455
Mandera
Wajir                         660               1443              2103
NORTH EASTERN                                  12706             32852              45558        126902

Kisii                     276989              403690           680679                1976        1522194       1.3
Kisumu                    216611              407237           623848                2093                      3.4
Siaya                     248560              366574           615134                2523                      4.1
Homa Bay                   99581              344471           444052                5714        1162048       4.9
Migori                    302344              415652           717996
Nyamira                   275756              565759           841515
NYANZA                   1419842             2503384          3923226               12526                      3.2
Kajiado                   184767               86151           270918               20963                     77.4
Kericho                   267722              273591           541313                4890        1012450       4.8
Laikipia                  156621               94892           251513                9718                     38.6
Nakuru                    533265              432868           966133                7024                      7.3
Nandi                     168039              293094           461133                2745                      6.0
Narok                     113214              119365           232579               18513        420924       79.6
Bomet                     178372              292765           471137
Trans Mara                 82461              105884           188345
Baringo                   190231              114599           304830               10627                     34.9
Elgeyo Marakwet                               121641           111168              232809           2722
11.7
Samburu
Trans Nzoia               191530              224858           416388                2468                      5.9
Turkana
Uasin Gishu               260887              233885           494772                3784                      7.6
West Pokot                 66836              140997           207833                5076                     24.4

RIFT VALLEY              2515582             2524115          5039697              171108                     34.0
Bungoma                   316004              411630           727634                3074                      4.2
Busia                     120158              234742           354900                1629                      4.6
Kakamega                  413444              536436           949880                3520        1485646       2.4
Vihiga                    201392              334374           535766
WESTERN                  1050998             1517182          2568180                8223                      3.2

Rural                    8492928             9790031         18282959
Urban                    1681303             1670429          3351732

Total                   10174231            11460460         21634691              571416                     26.4

Sources: WMS III (1997) Unpublished data
Statistical Abstract 1998 Tables 5 and 68




                                                                                                                        81
                                                     Table 3.0: Primary school enrolment by sex in 1995

     PROVINCE/DISTRICT                                            TOTAL
                                       Boys                        Girls                 Total            B/G    B/G**
     CENTRAL
     Kiambu                           69,560                   70,329                   139,889           0.99   1.00
     Kirinyaga                        56,319                   58,028                   114,347           0.97
     Muranga                         130,922                  131,241                   262,163           1.00
     Nyandarua                        61,143                   60,917                   122,060           1.00
     Nyeri                            87,024                   87,092                   174,116           1.00
     Thika                            59,147                   58,153                   117,300           1.02
     Thika Mun.                        6,070                    6,463                    12,533           0.94
     Total                           470,185                  472,223                   942,408           1.00

     COAST
     Kilifi                           61,068                   58,171                   119,239           1.05
     Kwale                            42,151                   32,427                    74,578           1.30
     Lamu                              7,056                    6,590                    13,646           1.07
     Mombasa                          35,175                   33,212                    68,387           1.06
     Taita Taveta                     30,155                   29,289                    59,444           1.03
     Tana River                        9,618                    7,667                    17,285           1.25
     Total                           185,223                  167,356                   352,579           1.11

     EASTERN
     Embu                             54,334                   55,906                   110,240           0.97
     Isiolo                            7,351                    6,294                    13,645           1.17
     Kitui                            55,459                   55,666                   111,125           1.00   0.99
     Machakos                        106,522                  106,628                   213,150           1.00   1.00
     Makueni                         107,379                  107,904                   215,283           1.00
     Marsabit                          6,366                    4,239                    10,605           1.50
     Meru                             55,035                   56,391                   111,426           0.98   0.94
     Nyambene                         48,519                   53,797                   102,316           0.90
     Mwingi                           30,597                   30,979                    61,576           0.99
     Tharaka Nithi                    34,316                   37,123                    71,439           0.92
     Total                           505,878                  514,927                 1,020,805           0.98

     NAIROBI                           78,924                     78,156                157,080           1.01
     NORTH EASTERN
     Garissa                            7,522                      2,626                 10,148           2.86
     Mandera                            4,235                      2,290                  6,525           1.85
     Wajir                              5,754                      2,679                  8,433           2.15
     Total                             17,511                      7,595                 25,106           2.31

     NYANZA
     Kisumu Mun                       13,598                   13,059                    26,657           1.04   1.06
     Nyamira                          52,514                   52,642                   105,156           1.00
     Siaya                            96,220                   91,332                   187,552           1.05
     Homa Bay                         96,688                   86,657                   183,345           1.12   1.11
     Kisii                           112,955                  113,499                   226,454           1.00   1.00
     Kisumu                           62,171                   58,606                   120,777           1.06
     Kuria                            14,796                   13,003                    27,799           1.14
     Migori                           59,555                   54,392                   113,947           1.09
     Total                           508,497                  483,190                   991,687           1.05

     RIFT VALLEY
     Trans-Mara                       13,391                   11,440                    24,831           1.17
     Narok                            24,176                   18,902                    43,078           1.28   1.24
     Kajiado                          29,061                   23,235                    52,296           1.25
     Samburu                           9,911                    5,658                    15,569           1.75
     Keiyo                            19,154                   19,879                    39,033           0.96   1.00
     Marakwet                         18,160                   17,485                    35,645           1.04
     Nandi                            65,341                   65,863                   131,204           0.99
     Trans Nzoia                      48,448                   48,332                    96,780           1.00   1.00
     Kitale mun.                       4,118                    4,132                     8,250           1.00
     Uasin Gishu                      42,864                   43,479                    86,343           0.99   0.99
     Eldoret mun.                      9,930                    9,815                    19,745           1.01
     West Pokot                       22,254                   18,995                    41,249           1.17
     Turkana                          21,160                   13,030                    34,190           1.62
     Laikipia                         32,163                   31,541                    63,704           1.02
     Kericho                          64,993                   64,377                   129,370           1.01   1.02
     Nakuru Mun.                      16,786                   16,743                    33,529           1.00
     Nakuru                           93,694                   91,375                   185,069           1.03   1.02
     Bomet                            68,146                   66,654                   134,800           1.02
     Baringo                          44,371                   44,071                    88,442           1.01
     Total                           648,121                  615,006                 1,263,127           1.05

     WESTERN
     Bungoma                         102,231                  105,330                   207,561           0.97   0.96
     Busia                            64,749                   61,923                   126,672           1.05
     Kakamega                        138,645                  142,385                   281,030           0.97   0.96
     Vihiga                           67,149                   71,107                   138,256           0.94
     Mt. Elgon                        15,192                   14,893                    30,085           1.02
     Total                           387,966                  395,638                   783,604           0.98
     GRAND TOTAL                    2,802,305               2,734,091                 5,536,396           1.02
     * Provisional
      Source: MoE, Statistics Section; DEOs Statistical returns




82
                                             Table 3.1: Secondary school enrolment by sex in 1995

PROVINCE/DISTRICT                                            TOTAL


                                 Male                    Female                   Total             B/G    B/G**


CENTRAL
Kiambu                            12,095                     14,816               26,911            0.82   0.91
Kirinyaga                          5,516                      7,163               12,679            0.77
Muranga                           14,558                     15,333               29,891            0.95
Nyandarua                          6,653                      6,142               12,795            1.08
Nyeri                             13,305                     13,179               26,484            1.01
Thika                             10,806                      9,226               20,032            1.17
Thika Mun.                         1,246                      2,513                3,759            0.50
Total                             64,179                     68,372              132,551            0.94

COAST
Kilifi                             4,872                      2,976                7,848            1.64
Kwale                              3,418                      2,659                6,077            1.29
Lamu                                 644                        512                1,156            1.26
Mombasa                            5,702                      5,212               10,914            1.09
Taita Taveta                       4,144                      4,069                8,213            1.02
Tana River                           671                        505                1,176            1.33
Total                             19,451                     15,933               35,384            1.22

EASTERN
Embu                               6,457                      7,142               13,599            0.90
Isiolo                             1,102                        756                1,858            1.46
Kitui                              6,395                      5,230               11,625            1.22   1.27
Machakos                          16,080                     13,937               30,017            1.15   1.20
Makueni                           11,340                      8,879               20,219            1.28
Marsabit                             957                        496                1,453            1.93
Meru                               5,817                      6,111               11,928            0.95   1.10
Nyambene                           5,121                      3,638                8,759            1.41
Mwingi                             2,387                      1,661                4,048            1.44
Tharaka -Nithi                     5,706                      5,435               11,141            1.05
Total                             61,362                     53,285              114,647            1.15

NAIROBI                           16,711                     13,573               30,284            1.23
NORTH-EASTERN
Garissa                            1,232                       444                 1,676            2.77
Mandera                              897                       245                 1,142            3.66
Wajir                              1,003                       163                 1,166            6.15
Total                              3,132                       852                 3,984            3.68

NYANZA
Nyamira                           10,828                      9,351               20,179            1.16   1.22
Siaya                              9,182                      6,142               15,324            1.49
Homa Bay                           6,851                      3,141                9,992            2.18   2.12
Kisii                             21,258                     16,904               38,162            1.26
Kisumu                            11,509                      7,688               19,197            1.50
Kuria                              1,641                        741                2,382            2.21
Migori                             4,955                      2,470                7,425            2.01
Total                             66,224                     46,437              112,661            1.43

RIFT VALLEY
Trans Mara                           825                        415                1,240            1.99
Narok                              1,637                      1,122                2,759            1.46   1.60
Kajiado                            2,302                      2,552                4,854            0.90
Samburu                              966                        463                1,429            2.09
Keiyo                              3,243                      3,520                6,763            0.92   1.08
Marakwet                           1,854                      1,194                3,048            1.55
Nandi                              6,169                      5,111               11,280            1.21
Trans Nzoia                        3,588                      3,241                6,829            1.11
Uasin Gishu                        4,961                      4,843                9,804            1.02
West Pokot                         1,685                      1,103                2,788            1.53
Turkana                            1,230                        652                1,882            1.89
Laikipia                           3,304                      2,553                5,857            1.29
Kericho                            8,790                      6,114               14,904            1.44   1.49
Nakuru                            10,833                      7,786               18,619            1.39   1.27
Nakuru Mun.                        4,517                      4,332                8,849            1.04
Bomet                              6,786                      4,340               11,126            1.56
Baringo                            6,454                      5,536               11,990            1.17
Total                             69,144                     54,877              124,021            1.26

WESTERN
Busia                              4,905                      3,313                8,218            1.48
Bungoma                           11,816                      8,953               20,769            1.32   1.35
Kakamega                          15,224                     14,263               29,487            1.07   0.97
Vihiga                             8,199                      9,855               18,054            0.83
Mt. Elgon                          1,460                        868                2,328            1.68
Total                             41,604                     37,252               78,856            1.12

GRAND TOTAL                     341,807                  290,581                 632,388            1.18

* Provisional
 Source: MoE, Statistics Section; DEOs Statistical returns




                                                                                                                   83
                                            Table 3.2: Wage employment by province,1990-1999

                                                                (‘000’s)

     Province           1990        1991        1992        1993       1994       1995         1996     1997      1998     1999*

     Nairobi            393.9      374.4        375.2      376.1      393.7       400.1         410.9    414.9    418.2    420.8
     Coast              171.0      181.6        186.3      187.3      189.6       194.5         201.3    203.6    205.4    206.6
     North Eastern       12.4       12.9         13.1       13.4       13.8        14.3          14.8     15.1     15.4     15.4
     Eastern            114.0      123.4        125.5      127.3      129.2       132.4         136.1    137.9    139.1    139.6
     Central            199.9      205.8        206.3      209.5      212.4       219.9         230.1    235.2    238.5    239.5
     Rift Valley        295.3      307.6        312.4      316.6      320.3       338.4         357.6    367.0    371.8    374.3
     Nyanza             133.4      142.3        144.6      146.1      146.7       153.8         160.7    164.4    166.4    167.0
     Western             87.8       93.7         98.7       99.2       99.8       103.6         107.3    109.3    110.1    110.4

     Total             1407.7     1441.7      1462.1     1475.5      1505.5      1557.0        1618.8   1647.4   1664.9   1673.6

     *Provisional
     CBS: Economic Survey, various issues




84
                                                                            Table 3.3 : Wage employment by sector,1989-1999

                                                                                                                               (‘000’s)

                                                1989        1990            1991             1992               1993            1994               1995             1996             1997             1998      1999
     Private Sector                            682.8       709.5           726.6            763.2              789.5           817.2              867.0            917.9            946.8            967.2      990.3
     Public Sector                             685.6       699.8           715.1            698.7              686.0           688.3              690.0            700.9            700.6            697.7      683.3

     CBS: Economic Surveys



                                                                      Table 3.4: Wage employment in the public sector 1989-1999


                                                                                                    (‘000’s)

                                              1989      1990            1991         1992              1993             1994               1995             1996            1997             1998       1999
     Central government                      277.6      273.7          270.9        269.0             267.9            259.3              241.4            228.0           219.1            214.1       208.5
     Teachers Service Commission             195.1      203.0          219.2        208.6             211.9            223.3              219.1            232.9           241.3            247.7       242.3
     Parastatal bodies                       107.9      117.4          117.3        115.3             107.7            106.9              111.4            114.3           112.8            108.9       105.2
     Majority control by the public sector    50.5       54.0            52.8        50.0              48.9             48.8               50.3             53.9             52.5             49.9       48.5
     Local government                         54.1       51.7            52.1        50.8              49.6             50.0               67.8             71.8             74.9             77.1       78.7

     CBS:Economic Surveys




                                                                Table 3.5: Estimated real average wage earnings per employee 1989-1999




                                             1989       1990           1991          1992              1993            1994               1995             1996            1997             1998        1999

     Private sector                          312.9      992.1          914.1        829.8             662.2            606.2              742.5            833.9           907.7        1018.4         1150.7
     Public sector                           352.0     1061.8          969.7        850.0             643.6            591.6              687.2            761.8           819.9         946.5         1032.1

     TOTAL                                   332.5     1026.7          941.7        839.4             653.6            599.5              717.9            802.3           870.1            988.3      1102.3

     Memorandum items in public sector

     Central government                      393.9     1147.2        1041.5         920.8             679.7            614.6              734.4            776.5        826.0            945.7          994.2
     Teacher’s Service Commission            262.9      820.0         780.9         682.6             517.4            482.2              533.7            604.9        659.5            800.2          842.8
     Parastatal bodies                       436.5     1285.4        1136.0         976.8             784.7            710.0              801.3            860.1        914.7           1025.0         1171.7
     Majority control by the public sector   360.2     1239.2        1156.9        1026.2             804.6            759.5              929.7           1064.3       1185.5           1354.0         1543.9
     Local government                        270.5      866.1         822.6         700.9             523.6            544.8              687.8            839.8        920.5           1044.5         1213.1

     TOTAL                                   352.0     1061.8          969.9        850.0             643.6            591.6              687.2            761.8           819.9            946.5      1032.1

     CBS: Economic Surveys




85
86
                                                                                  Table 3.6: Persons engaged, recorded Totals1990-1999

                                                                                                         000’s

                                                       1990                1991            1992          1993              1994            1995            1996            1997             1998         1999*

     Mordern establishments -urban & rural

     Wage employees                                  1409.4              1441.7          1461.9        1475.5             1505.5         1557.0          1618.8          1647.4            1664.9       1673.6
     % Growth                                           3.6                 2.3             1.4           0.9                2.0            3.4             4.0             1.8               1.1          0.5
     Self-employed and unpaid family workers           48.2                52.2            53.8          56.2               58.3           61.1            63.2            64.1              64.8         65.1
     Informal sector**                                937.4              1063.2          1237.5        1466.4             1792.4         2240.5          2643.8          2986.9            3353.5       3738.8
     % Change                                         140.3                13.4            16.4          18.5               22.2           25.0            18.0            13.0              12.3         11.5

     Total                                           2395.0              2557.1          2753.2       2998.1              3356.2         3858.6          4325.8          4698.4           5083.2        5477.5

     % Change                                            3.5                6.8              7.7             8.9            11.9           15.0             12.1             8.6              8.2          7.8

     *Provisional.
     **The definition of micro and small enterprises differs from the CBS defintion of the informal sector

     CBS: Economic Surveys




                                                                                                                   Table 3.7: Estimated production of selected agricultural commodities, 1995-1999**

                                                                                              CROP                       Unit                 1995           1996           1997           1998        1999*

                                                                                              Maize                   million bags           29.99          24.00           24.60         27.30        25.00
                                                                                              Beans                              “            4.43           2.30            1.55          3.00         4.00
                                                                                              Potatoes                million tons            0.93           0.74            0.37          0.90         0.90
                                                                                              Sorghum                 million bags            0.88           0.40            0.39          0.56         0.90
                                                                                              Millet                             “            0.60           0.26            0.26          0.37         0.40

                                                                                              *Provisional
                                                                                              Source: Ministry of Agriculture
                                                             Table 3.8: Recorded marketed production at current prices, 1991-1999

                                                                                         (K_ Million)

     Marketed Production                    1991     1992               1993                 1994           1995               1996    1997     1998    1999*
     Cereals
     Maize                                   46.4     76.9              96.0                134.2           160.4             155.9    140.5    140.0    154.9
     Wheat                                   49.9     35.3              20.6                 63.1            81.6             105.7    109.9    149.3     50.3
     Others                                  35.1     40.8              41.7                 75.8            59.8              68.2     64.4     49.7     65.5
     Total                                  131.4    153.0             158.3                273.1           301.8             329.8    314.8    339.0    270.7
     Temporary industrial crops
     Sugarcane                              107.4    115.2             158.6                256.8           341.2             356.3    332.2    398.4    382.0
     Pyrethrum                               16.5     19.0              19.9                 27.9            22.1              16.7     16.1     17.5     20.3
     Others                                  15.7     20.8              19.7                 29.1            30.4              45.2     64.6     83.1     96.3

     Total                                  139.6    155.0             198.2                313.8           393.7             418.2    412.9    499.0    498.6

     Other temporary crops                   13.2      8.0               8.0                 10.1            10.1              16.0     22.7     23.9     26.1
     Permanent Crops
     Coffee                                 202.7    218.3             384.8                587.9           764.5             717.9    827.3    659.9    502.5
     Tea                                    390.0    446.7             993.4                915.0           829.8            1016.8   1181.8   1956.9   1554.4
     Sisal                                   18.8     16.7              16.9                 18.8            26.7              27.3     39.3     39.8     43.7
     Others                                   3.3      4.1               9.5                 10.3             8.0              14.5     18.9     16.1     17.5

     Total                                  614.9    685.8            1404.6               1532.0          1629.0            1776.5   2067.3   2672.7   2118.1

     Total crops                            899.1   1001.8            1769.1               2129.0          2334.6            2540.5   2817.7   3534.6   2913.5
     Livestock and products
     Cattle and calves                      193.8    207.1             235.2                252.7           302.6             363.1    435.7    443.9    444.3
     Dairy produce                           78.9     63.8              97.2                161.5           253.8             193.2    143.1     97.3    134.7
     Chicken and eggs                                                                        78.7            73.1              69.2     67.2     70.0     71.6
     Others                                  48.3     49.3              57.8                 68.1            78.4              86.3     93.0     94.3    101.6

     Total                                  321.0    320.2             390.2                561.0           707.9             711.8    739.0    705.5    752.2

     Grand total                           1220.1   1322.0            2159.3               2690.0          3042.5            3252.3   3556.7   4240.1   3665.6

     *Provisional
     CBS: Economic Survey,various issues




87
88
                                                                   Table 3.9: Sale of some major crops to marketing boards,1990-1999*

     Crop                                    Unit      1990          1991            1992            1993           1994             1995    1996     1997     1998    1999*

     Maize++                          000 tons         527.7         303.5           324.1           241.8          316.0           401.0    295.5    204.6    218.0   223.5
     Wheat+                                  “          78.5         199.0           125.9            73.1          105.2           125.5    130.0    124.2    176.7    52.9
     Rice paddy+                             “                        12.9            14.2            11.4           13.5            14.6     15.9     14.4     11.7    24.3
     Cotton+                                 “          18.8           8.4             2.8             2.5            1.8             0.2      0.5      0.5      0.5     0.2
     Coffee                                  “         111.9          87.1            88.4            77.8           81.5            95.8    103.2     68.0     51.3    64.3
     Tea                                     “         197.0         203.6           188.1           211.1          209.4           244.5    257.2    220.7    294.3   248.8
     Sisal                                   “          39.3          38.8            34.1            35.1           33.9            27.8     28.1     20.1     19.9    21.9
     Sugar-cane+                      mn. Tons           4.2           4.0             3.7             3.8            3.3             3.8      3.9      4.3      4.6     4.4
     Pyrethrum(extract equivalent)        tons         136.4         183.8           211.6           220.5          172.2           122.8     93.0     89.4     67.4    78.1

     Provisional
     +No purchases of paddy, wheat, cotton and sugar-cane by Boards
     ++Includes maize purchases by the National Cereals and Produce Board and millers
     CBS: Economic Surveys, various issues




                                                                      Table 4.0: Purchased agricultural inputs*,1990-1999 (K_ million)

     Inputs                                 1990       1991          1992            1993            1994           1995             1996    1997     1998    1999**

     MATERIAL INPUTS

     Fertilizers                            48.47      51.40         38.48           49.57           52.16          53.25           52.20    96.71    86.92   102.61
     Other agricultural chemicals           11.13      12.90         12.39           14.04           14.01          14.58           15.21    17.82    16.02    18.91
     Livestock drugs and medicines          18.82      20.44         18.73           22.24           23.00          23.90           25.60    28.70    30.33    32.00
     Fuel and power                         34.58      36.21         45.04           92.69          112.79         136.03          146.91   241.62   251.80   273.87
     Bags                                   11.47      12.64         13.87           14.64           15.81          16.81           17.82    24.15    25.62    22.56
     Manufactured feeds                     31.18      32.07         33.78           36.67           39.05          41.35           38.00    36.02    38.07    37.46
     Purchased seeds                        27.09      29.25         34.76           39.46           45.14          50.25           46.20    54.25    87.91    73.19
     Other material inputs                   8.47       9.07          9.36           10.24           10.55          11.14           11.70    12.06    12.60    10.49

     Total                              191.21        203.98        206.41         279.55          312.51         347.31           353.64   511.33   549.27   571.09

     SERVICE INPUTS                         14.18      15.75         16.26           18.24           19.01          20.26           21.80    22.65    24.46    25.19

     TOTAL INPUTS                       205.39        219.73        222.67          297.79         331.52          367.57          375.44   533.98   573.73   596.28

     *Except labour
     **Provisional.
     CBS: Economic Surveys,various issues
                                                                                                                                                                                   Year
                                                                                                                                                                                                                                                                                                    Year




                                                                                                                                                               1999
                                                                                                                                                               1998
                                                                                                                                                               1997
                                                                                                                                                               1996
                                                                                                                                                               1995
                                                                                                                                                               1994
                                                                                                                                                               1993
                                                                                                                                                               1992
                                                                                                                                                               1991
                                                                                                                                                               1990
                                                                                                                                                               1989
                                                                                                                                                                                                                                                                              1999
                                                                                                                                                                                                                                                                              1998
                                                                                                                                                                                                                                                                              1997
                                                                                                                                                                                                                                                                              1996
                                                                                                                                                                                                                                                                              1995
                                                                                                                                                                                                                                                                              1994
                                                                                                                                                                                                                                                                              1993
                                                                                                                                                                                                                                                                              1992
                                                                                                                                                                                                                                                                              1991
                                                                                                                                                                                                                                                                              1990
                                                                                                                                                                                                                                                                              1989
                                                                                                                                                                                                                                                                              1988
                                                                                                                                                                                                                                                                              1987




                                                                 Year



                                                       1989/90
                                                       1988/89
                                                       1987/88




                                                       1998/99
                                                       1997/98
                                                       1996/97
                                                       1995/96
                                                       1994/95
                                                       1993/94
                                                       1992/93
                                                       1991/92
                                                       1990/91
                                                                                                                                     CBS: Economic Surveys




                               CBS: Economic Surveys
                                                                                                                                                                                                                                                     CBS: Economic Surveys




                                                                                                                                                                                                                  Table 4.2: Tea Production




                                                        68.1
                                                        53.4
                                                        68.0
                                                        97.0
                                                        95.4
                                                        79.9
                                                        75.1
                                                        85.3
                                                        86.4
                                                                                                                                                                                                                                                                               99.1
                                                                                                                                                                                                                                                                               78.4
                                                                                                                                                                                                                                                                               84.2
                                                                                                                                                                                                                                                                               84.8
                                                                                                                                                                                                                                                                               71.1
                                                                                                                                                                                                                                                                               65.2
                                                                                                                                                                                                                                                                               62.4




                                                       103.9
                                                       116.9
                                                       128.7
                                                                                               Table 4.3: Coffee production
                                                                                                                                                                                                                                                                              152.6
                                                                                                                                                                                                                                                                              169.3
                                                                                                                                                                                                                                                                              188.8
                                                                                                                                                                                                                                                                              134.2
                                                                                                                                                                                                                                                                              151.5
                                                                                                                                                                                                                                                                              136.9




                                                                                                                                                               248.70
                                                                                                                                                               294.17
                                                                                                                                                               220.72
                                                                                                                                                               257.16
                                                                                                                                                               244.53
                                                                                                                                                               209.42
                                                                                                                                                               211.16
                                                                                                                                                               188.07
                                                                                                                                                               203.60
                                                                                                                                                               197.00
                                                                                                                                                               180.60
                                                                                                                                                                                                                                                                                                    Volume ‘000 tons
                                                                                                                                                                                                                                                                                                                       Table 4.1: Exports of fresh horticultural produce




                                                                                                                                                                                   Tea Production ‘000 tonnes




                                                                 Coffee production ‘000 tons
                                                                   Table 4.4: Production and sale of livestock and dairy products, 1990-1999*

                                                                 Unit                                                         1990                           1991   1992    1993                      1994                                    1995                           1996   1997   1998   1999**

     Recorded milk production***                             Mn. litres                                                       392                            359     362    365                                 258                           350                             257    197    126     180

     Kenya Co-operative Creameries milk processed:
     Wholemilk and cream                                     Mn. litres                                                        340                            321   336.2    343                       204                                     175                            165    108     71     156
     Butter and ghee                                             Tons                                                         4550                           3479    4231   4128                      2409                                    3131                           2327    917    480    1238
     Cheese                                                      Tons                                                          172                            250     218    221                       126                                     141                            193    112     18     257
     Dried whole milk powder                                     Tons                                                         1396                            975    1493   1322                      2237                                    2480                            973    351    396
     Dried skim-milk powder                                      Tons                                                         2992                           3035    2731   2869                      2121                                    3101                           2349   1244    434
     Other products                                              Tons                                                          399                            387     433    456                       218                                     208                            349    110     30

     Livestock slaughtered
     Cattle and calves                                       000 Head                                                          828                            969    921     980                       991                                    1067                           1219   1320   1443    1489
     Sheep and goats                                         000 Head                                                         1206                           1345   1278    1280                      1310                                    1327                           1407   1603   1752    1869
     Pigs                                                    000 Head                                                           84                             83     81      88                        91                                      91                             98     88     81      82

     *Figures on milk processed are revised
     **Provisional.
     *** Including sale licensed by the Kenya Dairy Board.




89
90
                                                                Table 4.5: Analysis of key fiscal trends,1992/93-1999/2000


                                                      1992/93      1993/94              1994/95              1995/96         1996/97   1997/98*   1998/99**   1999/2000**

     1.   Current surplus/deficit as %of current
          revenue                                     -12.4          -17.3                 3.4                  5.5            4.8       8.8          8.2          0.7

     2.   Current surplus/deficit as %of capital
          expenditure plus net lending                -85.9        -145.0                28.0                 43.2            38.8     109.7         96.0          7.3

     3.   Ratio of capital expenditure to current
          revenue                                      10.9            9.6               12.1                 13.3            11.3       8.5          7.5          9.5

     4.   Overall deficit as % of current revenue     -13.5          -20.0                 2.7                 -2.8           -3.0       4.2         -1.4          -5.9

     5.   Overall deficit as % of total expenditure    -7.7          -11.2                 2.0                 -2.2           -2.4       2.5         -1.0          -3.9

     6.   External grants and loans as % of capital
          Expenditure plus Net Lending                151.7          66.6                74.5                 31.5            -4.6     -12.5        -90.7         -50.8

     7.   Net short-term borrowing as % of Capital
          Expenditure plus net lending                137.1         229.2               104.6                 -26.8          124.0      69.2       -123.9         71.7

     8.   Current revenue as % of GDP at current
          Market prices                                27.0          31.4                32.4                 28.8            23.2      28.8         26.0         25.0

     9.   Total government expenditure as % of
          GDP at current market prices                 48.2          55.8                48.6                 37.0            33.2      49.9         35.0         38.0

     10. Overall deficit as % of GDP at current
         market prices                                 -3.6           -5.6                -3.6                 -0.9           -0.7       1.2          0.6          -1.4

     *Provisional.
     **Estimates
                                                                                            Table 4.6: Total expenditure on roads, 1990/91-1999/00


     Indicator                                    1990/91               1991/92               1992/93              1993/94             1994/95          1995/96              1996/97             1997/98               1998/99            1999/00*

     Trunk roads                                    45.1                 40.1                  42.0                  38.7                 48.6             120.6                39.3               49.8                  71.1              152.5
     Primary roads                                  16.2                 11.4                  20.8                  24.7                 37.2              55.8                41.5               57.8                  37.6               36.5
     Secondary roads                                12.4                 10.9                  17.0                   8.7                 18.3               8.3                34.2               15.9                   6.8               24.4
     Unclassified roads
     Miscellaneous roads                            27.1                 21.0                  18.3                   2.8                 17.6              40.5                23.3               20.0                  18.8               82.0
     Total 100.8                                    83.4                 98.1                  74.9                 121.7                225.2             138.3               143.5              134.3                 295.4
     Rec.(maintenance and repair)                   25.5                 28.1                  10.4                  62.2                128.8             168.3               235.4              234.1                 253.7              315.1

     Total                                         126.3                111.5                 108.5                 137.1                250.5             393.5              373.7               377.6                 388.0              610.5

     *Provisional



                                                             Table 4.7.: Development expenditure on water supplies and related services, 1990/91-1999/2000 (K_’000)

                                                              1990/91              1991/92                1992/93             1993/94            1994/95           1995/96             1996/97             1997/98           1998/99    1999/2000*

     Water development                                         1,410                 2,141                 5,986                 8,620            43,096            34,554              29,551             16,214            18,187        36,120
     Training of water development staff                         229                   258                   156                   137             2,710             2,899                 775                665               625           108
     Rural water supplies                                     18,101                15,136                16,387                15,732            18,834            24,921              25,773             43,243             8,278        13,293
     Self-help water supplies**                                  106                    96                    79                    53               164               196                  60                 90                50            45
     County council and urban water supplies                   1,543                 2,293                 3,547                 5,391             4,441             5,085               6,323              6,718             1,635         8,352
     Miscellaneous and special water programmes                3,537                 5,856                 5,848                 6,023             3,580             4,279               5,950              5,640            13,584         3,643
     Regional and irrigation development                           -                     -                     -                     -            32,864            35,794              19,520             13,996                 0             0
     Water Conservation and Pipeline Corporation              35,821                20,557                40,944                52,408           106,747           106,704             107,828             55,957            22,240        19,300
     Others                                                                                                                                                                                                11,341                 0             0

     TOTAL                                                    60,747                46,337                72,947                88,364           212,436           214,432             195,780            153,864            64,599        80,861

     Sources: Ministry of Environment and Natural Resources, National Water
     Conservation and Pipeline Corporation
     *Provisional
     **Includes contribution by the Ministry of Environment and Natural Resources


                                                                                                      Table 4.8: Balance of trade,1990-1999

                                       1990                 1991                  1992                  1993                    1994                 1995               1996                     1997                 1998                1999

     Exports(f.o.b.)
     Domestic exports                1,232,360          1,611,179               1,708,085             3,625,207               4,170,724           4,656,184            5,696,299            5,722,973               5,722,266           5,742,084
     Re-exports                         11,650             18,288                  34,183                53,040                 111,408             210,763              213,701              299,285                 336,761             363,550

     Total 1,244,010                 1,629,467         1,742,268             3,678,247                4,282,132               4,866,947           5,910,000            6,022,258            6,059,027               6,105,634

     Imports(c.i.f.)
     Commercial                       2,397,548         2,500,911            2,828,853                 4,845,061              5,556,159            7,495,494           8,144,219            9,264,130                9,526,905          9,420,570
     Government                         148,082           145,002              126,010                   211,358                197,829              262,930             280,089              269,546                  362,527            329,620
     Total 2,545,630                  2,645,913         2,954,863            5,056,419                 5,753,988              7,758,424            8,424,308           9,533,676            9,889,432                9,750,190
     Visible balance                 -1,301,620        -1,016,447           -1,212,595                -1,378,172             -1,471,850           -2,891,477          -2,514,308           -3,511,418               -3,830,405         -3,644,556

     Total Trade                     3,789,640         4,275,380             4,697,131                8,734,666              10,036,120          12,625,371           14,334,308           15,555,934           15,948,459             15,855,824

     CBS: Economic Survey




91
92
                                                         Table 4.9: Central Government Expenditure on Main Services, 1990/91-1999/2000 (K_ Million)

                                                       1990/91                        1991/92                             1992/93                               1993/94                      1994/95
                                              Rec.      Dev.       Total    Rec.       Dev.          Total     Rec.        Dev.          Total         Rec.      Dev.      Total    Rec.      Dev.      Total
                                             Account   Account             Account    Account                 Account     Account                     Account   Account            Account   Account

     GENERAL PUBLIC ADMINISTRATION

     General administration                    156      166        322        178        148         325        243         190           433           277       234      510        471     490       962
     External affairs                          51.4     2.24       53.6       61.3       1.34        62.6       68.3        5.27         73.5           118      3.42      122        102      5.3      108
     Public order and safety                    161     23.7        185        183       15.5         198        214        17.7          232           281      9.21      290        371     12.6      384

     TOTAL                                     369       192        561        422       165         586        525          213          738           675       246      922        945      508     1453

     Defence                                    262     33.9        295        207       25.9         232        244        26.6          270            330     12.8      343         309    6.29      315
     Education                                  620       67        687        663       59.1         722        784          71         855           1004      65.3     1070         299    88.4     1388
     Health                                     133     39.5        173        152       37.6         190        175          57          232            229     97.7      327         295    55.3      351
     Housing and community welfare             4.17     13.1       17.3       4.66       9.49        14.1       4.37        4.76         9.13           9.79       28     37.8        12.4    32.9     45.4
     Social welfare                            42.4     38.9       81.3       46.9       31.5        78.4         52        43.2         95.2           52.4     18.3     70.7        67.3    44.8      112

     ECONOMIC SERVICES

     General administration                      23      121        144       26.6       75.4         102       31.3        43.4         74.7            41      87.1       128      53.9     51.8       106
     Agriculture, forestry & fishing           91.1      105        196        101        111         212        130         201          331           161       303       464       184      192       376
     Mining, manufacturing & construction      38.6     40.2       78.9       40.8       8.82        49.7         47        17.4         64.4          59.7      28.4      88.1        75     11.4      86.4
     Electricity, gas, steam & water           25.8     57.8       83.7       27.5         41        68.5       33.1        41.3         74.5          44.3      38.8       171      53.4     84.8       138
     Roads                                     13.3     94.2        107       15.3       84.2        99.5       18.1         116          134          54.8       100       155       137      131       268
     Other transport & communications          11.4     18.6         30       10.6       0.21        10.8       11.1        15.4         26.6          6.27      0.42      6.69      1037     94.9       105
     Other economic services                    107     6.76        113        106       1.46         107        137        1.33          139          38.4      0.59        39      46.5     0.65      47.2

     TOTAL ECONOMIC SERVICES                   310       444        753        328       322         650        408          436          844           405       558     1051        559      567     1126

     OTHER SERVICES, INCLUDING PUBLIC DEBT    1538         0       1538      1972           0       1972       3123            0        3123           5275         0     5275       3447        0     3447

     TOTAL**                                  3278       828       4106      3795        650        4445       5316          851        6167           7981      1027     9008       6934     1303     8237

     General administration                    613      271         885     751.19      431.5       1183      898.27       312.7         1211         1097        254      1351    1067.96   811.8      1880
     External affairs                          128      13.7        142     119.43      13.96       133.4     138.37        1.35        139.7         138.1       2.9       141     150.48    7.54       158
     Public order and safety                   391      15.7        407     459.24      21.26       480.5     553.22       18.91        572.1           567     16.24     583.3     696.81   16.43     713.2

     TOTAL                                    1133       301       1433     1329.9      466.7       1797     1589.86         333        1923           1802     273.1     2075     1915.25   835.8     2751

     Defence                                   440      11.9        452     515.67       7.92      523.6      501.96        6.09        508.1         526.8      2.16       529      527.4    6.65     534.1
     Education                                1491      94.9       1586     1590.9      83.23       1674     2221.14       90.05         2311          2271     90.04      2361    2470.51   89.79      2560
     Health                                    371      83.9        454     397.38        131      528.4      454.71       197.9        652.6         459.8     62.66     522.5     468.72   195.7     664.4
     Housing and community welfare            16.6      83.5        100      105.6      74.22      179.8        94.3       78.93        173.2         82.88        59     141.9      93.75   81.48     175.2
     Social welfare                            82.7     70.7        153       1.95          0        1.95       1.16           0          1.16        15.61      1.52     17.13      19.38    1.74     21.12
                                                              1990/91                         1991/92                         1992/93                      1993/94                      1994/95
                                                  Rec.         Dev.        Total    Rec.       Dev.        Total     Rec.      Dev.      Total    Rec.      Dev.      Total    Rec.      Dev.      Total
                                                 Account      Account              Account    Account               Account   Account            Account   Account            Account   Account

     ECONOMIC SERVICES

     General administration                         63.5       58.8         122      65.94       73.8     139.7      98.51    53.84     152.4    100.2     67.43     167.7     131.73   279.7     411.5
     Agriculture, forestry & fishing                 216        171         387     220.15        128     348.1     213.43    174.4     387.8    243.4     229.9     473.3     221.11   265.8     486.9
     Mining, manufacturing & construction           70.4       11.2        81.6      86.91      27.67     114.6      89.88    21.47     111.4    78.16     37.89     116.1     101.13   33.31     134.4
     Electricity, gas, steam &Water                 54.9        113         168      57.64      102.9     160.5      14.39    85.41      99.8    62.15     38.89       101      62.22   76.25     138.5
     Roads                                           191        193         384     248.07      149.3     397.4     241.27    135.3     376.6    266.7     139.7     406.3     321.38     296     617.4
     Other transport & communications               11.8        184         196      15.81      94.18       110      18.96    13.64      32.6       40      2.05     42.05      43.19    2.74     45.93
     Other economic services                        47.6       3.52        51.1      49.22       3.29     52.51      51.06      1.9     52.96     57.5       0.7      58.2      69.27    13.5     82.77

     TOTAL ECONOMIC SERVICES                        655         734        1389     743.74      579.1     1323       727.5     486       1213    848.1     516.5      1365     950.03   967.3     1917

     OTHER SERVICES, INCLUDING PUBLIC DEBT         3602           0        3602     3159.8            0   3160     8888.88        0      8889     5125        0       5125    5768.44      0       5768

     TOTAL**                                       7791        1380        9170     7844.9      1342      9187     14479.5    1192      15671    11132     1005      12137    12213.5   2178      14392

     *Provisional
     **Total as shown in this table minus loan repayment to the Government equals total expenditure
     +Revised Estimates
     CBS: Economic Surveys




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