WORLD CENSUS OF AGRICULTURE PROGRAMME_2_ by hcj

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									LAUNCHING: AGRI - GENDER DATABASE
   a statistical toolkit for the production of
     sex-disaggregated agricultural data




                             21st AFCAS
                           Accra, 28 - 31 October 2009




                      Diana Tempelman
                      Senior Officer, Gender and Development
                      FAO Regional Office for Africa, Accra
     1st edition
    October ‘09




2
         AGRI - GENDER DATABASE
             a statistical toolkit for the production of
               sex-disaggregated agricultural data


    RESULT OF:

       Nearly 2 decades collaboration FAO & NBS-s
        in Africa

       “joint-venture” with N = 100+ statisticians

       Support of N = 10,000+++ men and women
        farmers responding to census / survey Q.
3
               AGRI - GENDER DATABASE
           a statistical toolkit for the production of
             sex-disaggregated agricultural data


    1.   Early days –      first half 1990-ies

    2.   Developing methodology - WCA 2000
         (1996-2005)

    3.   Consolidation - WCA 2010                (2006 – 2015)

    4.   Remaining challenges

4    * WCA = World Census of agriculture
     1. Early days
            (1991-1995)
    Togo, Benin, Burkina Faso, Botswana




5
                                              Early
    1. Early days   –   first half 1990-ies REACTIONS




                    “Those feminists
                     from Beijing!”
                                           Though
                                             t?



       Thought       “Yes, women’s
          ?         agricultural work
                    doesn’t show in
                       statistics”
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                                                         ACTIONS
    1. Early days           – first half 1990-ies

    re-analysing existing raw data
    data by sex of Head of Holding



                   technical support to user-producers
                   workshops availability / demand / users of
                   sex-disaggregated agricultural data




    revision of concepts & definitions
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                                                         OUTCOME
    1. Early days          – first half 1990-ies


       Awareness on need for sex-disaggregated data



       Knowledge among statisticians



       Openness to test collection sex-disaggregated data through
        existing agricultural surveys / censuses


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    2. Developing a methodology:
             WCA 2000 (1996-2005)
       Senegal, Guinea, Cape Verde, Burkina Faso,
      Mali, Lesotho, Namibia, Mozambique, Tanzania,
                    Cameroon, Uganda



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                                    ACTIONS
     2. Developing a methodology:
       WCA 2000 (1996-2005)

     Gender analysis training


              Data analysis & presentation at
              sub-national level

       Data presentation at
       sub-household level
10     ALL MEMBERS’ WORK
                                    OUTCOME
     2. Developing a methodology:
       WCA 2000 (1996-2005)




     Lessons learned
     document




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     2. Developing a methodology:            OUTCOME
       WCA 2000 (1996-2005)


     Thematic census reports:   Tanzania, Niger




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     3. Consolidation
     WCA 2010 (2006 - 2015)




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     3. EXAMPLES of Best practises
        from WCA 2010


    Analysis of demographic data

    Access to productive resources (/ sex of HoHH & individual)

    Destination of agricultural produce / sex of HoHH (min.)

    Credit, labour and time-use

    Poverty indicators


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                            ACTIONS

     AGRI-GENDER DATABASE




        TODAY
     29 October ‘09




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                 AGRI-GENDER DATABASE
                            INTRODUCTION

     Data Items                                SECTION 1        SECTION 2
     1   Agricultural population and households Questionnaire   Table
     2 Access to productive resources          Questionnaire     Table
     3 Production and productivity             Questionnaire    Table
     4 Destination of agricultural produce      Questionnaire    Table
     5 Labour and time-use                      Questionnaire    Table
     6 Income and expenditures                  Questionnaire    Table
     7 Membership of agricultural/farmer organisations
                                                         Questionnaire
         Table
     8 Food security                            Questionnaire Table
     9 Poverty indicators                       Questionnaire Table
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                                                                                                 DATA
                         1.1 - Demographic data: Guinea
                         FEMINISATION AGRICULTURAL SECTOR


                                   Guinea                                           Guinea – Labé Region
      85+                                                 85+

 80 - 84                                             80 - 84


 75 - 79                                             75 - 79

  70 -74                                              70 -74


 65 - 69                                             65 - 69


 60 - 64                                             60 - 64


 55 - 59                                             55 - 59


 50 - 54                                             50 - 54

                                                     45 - 49
 45 - 49

                                                     40 - 44
 40 - 44

                                                     35 - 39
 35 - 39

                                                     30 - 34
 30 - 34

                                                     25 - 29
 25 - 29
                                                     20 - 24
 20 - 24
                                                      15 -19
  15 -19
                                                     .10 - 14
.10 - 14
                                                        .5 - 9
   .5 - 9
                                                          >5
       >5

                                                                             Male                  Female
                            Male            Female   Scale maximum = 90000
Scale maximum = 800000



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                                                                                 DATA
     1.2 - Demographic data - NIGER
     Average FFH: smaller but more dependents


     Average size and dependency ratio of agricultural households by sex
     of Head of Household at regional and national level

                                      Male HoHH                    Female HoHH
        Region
                                            Dependency                    Dependency
                            Average size                 Average size
                                               ratio                         ratio
        AGADEZ                  5,5               0,87       4,0             0,90
        DIFFA                   5,8               0,84       3,6             0,92
        DOSSO                   7,6               0,82       4,4             0,89
        MARADI                  7,7               0,95       3,9             0,96
        TAHOUA                  6,6               0,86       4,3             1,16
        TILLABERY               8,3               0,83       4,5             0,99
        ZINDER                  5,9               0,85       3,7             1,07
        NIAMEY                  6,1               0,69       4,8             0,65
                    Total       6,9               0,86       4,0             1,03


18      Source: RGAC 2004-2007, Niger
                                                 DATA
     1.3 - Demographic data - Tanzania
     labour constraints in          headed HH


       Active male members / sex of HoHH, Tanzania

              Selected    Male active / sex of HoHH
              regions    Male HoHH Female HoHH
           Dodoma            1.1              0.3
           Mtwara            1.0              0.5
           Iringa            1.1              0.2
           Mbeya             1.1              0.3
           Mara              1.0              0.5

           Tanzania          1.1           0.4
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      2.1- Access to productive resources, LAND


                                  Section 2 : Inventory of plots of agricultural holdings (NIGER)
          Identification          Family name & first   Sex of Plot         Type     Plot culture     Type of          Type of land           Type
                                       name of           manager           de plot     history        culture            tenure             of Relief
             Plots, farms           Plotmanager                         management
         1                  2              3                4                 5           6              7                    8                   9
        Field           Plot        Write first and      Male 1       Individual 1   cultivated 1   Cul, pur 1      1 Inheritance       1 Plane
                                    family name of      Female 2      Collective 2   fallow 2       Cult, mixed 2   2 Purchase          2 valley bottom
                                     Plotmanager,                                                                   3 renting or crop   2 slope
                                   starting with the                                                                sharing
                                         HoHH                                                                       4 Loan
                                                                                                                    5 Gift
                                                                                                                    6 Other
     |____|____
                    |____|____|                          |____|           |____|       |____|         |____|              |____|             |____|
          |
     |____|____
                    |____|____|                          |____|           |____|       |____|         |____|              |____|             |____|
          |




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Male sub-holder: Area under collective management
per type of acquisition - NIGER

                5%
                     1%
                          3%
                                                                            DATA
           1%
                                                    Inherited
      7%                                            Purchased
                                                    Share-cropping
                                                    Loan
                                                    Gift
                                                    Other
                                83%




                               Female sub-holder: Area under collective
                               management per type of acquisition - NIGER


  LAND Collective                        9%     5%
    management                   11%                                         Inherited
     / Head of HH                                                            Purchased
                                                                             Share-cropping
                                0%                                           Loan
                                                                             Gift
                                  6%                                 69%     Other

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Male sub-holder: Area under individual management
per type of acquisition at national level - NIGER
                 2%      1%
                                                                                  DATA
           10%
      2%
                                                      Inherited
    9%                                                Purchased
                                                      Share-cropping
                                                      Loan
                                                      Gift
                                                      Other
                                   76%



                                 Female sub-holder: Area under individual
                                 management per type of acquisition at national level,
                                 NIGER
      LAND Individual
          management                            12%
                                                             1%

 / active HH members                                                        35%          Inherited
                                                                                         Purchased
                                                                                         Share-cropping
                                                                                         Loan
                                                                            3%           Gift
                                          48%                                            Other
 22                                                                    1%
 2.2 - Access to productive resources: ANIMALS


      Household level question

     Section 2 : Number of sedentary animals par kind and sex of owner
     Code      Kind of animal, sex and age       Total number       Number owned by women
      1                         2                     3                         4
          10   Cattle
      11       Female                          |____|____|____|          |____|____|____|

      12       Male                            |____|____|____|          |____|____|____|

      13       Castrated male                  |____|____|____|          |____|____|____|


          30   Sheep                           |____|____|____|          |____|____|____|


          40   Goat                            |____|____|____|          |____|____|____|
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                                                                     DATA

     Sedentary animals / type of animal / sex of owner, Niger




                cattle                     sheep                     goats
        Men              Women     Men             Women     Men             Women
       77.7 %            22.3 %   60.3 %           39.7 %   45.5 %           54.5 %




       Source: RGAC 2004-2007, Niger
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                                                                                                                   DATA

      Ownership chicken / sex of owner, Niger


         -1- Chicken                                                     -2- PINTADES

              Repartition des poulets par proprietaire au niveau              Repartition des pintades selon le proprietaire au
                                  du Niger                                                    niveau de Niger



                  22%                                                              18%                  14%
                                                 32%
                                                               Femmes                                                         Femmes
                                                               Hommes                                                         Hommes
                                                               Enfants                                                        Enfants


                        46%                                                                       68%




25   Source: RGAC 2004-2007, Niger
                                                                                                                   DATA

     Ownership pigeons / sex & age of owner, Niger

       -3- Ducks                                                      -4- Pigeons

            Repartition des canards par proprietaire au Niger              Repartition des pigeons par proprietaire au Niger



                                                                                              3%        14%
                21%                        22%

                                                            Femmes                                                         Femmes
                                                            Hommes                                                         Hommes
                                                            Enfants                                                        Enfants


                            57%                                                  83%




26    Source: RGAC 2004-2007, Niger
     2.3 – a - Access to credit Tanzania

     Q 13.1: During the year 2002/2003 did any of the
     household members borrow money for
     agriculture?
           Yes or no


     Q 13.2 If yes, then give details of the credit
     obtained during the agricultural year 2002/2003
     (if the credit was provided in kind, for example by
27   the provision of inputs, then estimate the value)
     2.3 – b Use of CREDIT / sex HH member Tanzania

                                          Credit details                                                Source “a”
                                          Use codes to indicate source                                        |__|
                                          Provide to Male=1, Female=2                                         |__|
                                                                                                  Tick boxes below
                    S/N                   Use of credit                                           to indicate the
                                                                                                  use of the credit
                    13.2.1                Labour
                    13.2.2                Seeds
                    13.2.3                Fertilisers
                    13.2.4                Agrochemicals
                    13.2.5                Tools/equipment
                    13.2.6                Irrigation structures
                    13.2.7                Livestock
                    13.2.8                Other ………………………………

         Source of credit
                                            3 = Cooperative               6 = Private individual
28       1 = Family, friend or relative
         2 = Commercial bank
                                            4 = Savings and credit soc.
                                            5 = Trader/trade store
                                                                          7 = Religious organisation/NGO/Project
                                                                          8 = Other (specify) ………………………
                                                                                    DATA
     Female HoHH use credit to hire labour -
                                 to purchase seeds
         TANZANIA
                    Chart 7.5 Percent of Households that have access to Credit by sex of
                              Household Head
     Percent




               30



               20


               10



               0
                    Labour    Seeds    Fertili -   Agro-che   Tools / Irrigation Livestock   Other
                                        zers        micals    Equip   Structures
29   Use of Credit                                             ment      Male Headed    Female Headed
           4 – Destination of agricultural produce
           Part 2 – Crop usage proportions (percentages) ETHIOPIA



     1             2             3         4        5          6           7           8        9
                                                 Proportions of total product for
     Sr.      Name of crop
                             Household                     Wages in Animal          Other
     No.                                  Seed   Sale*                                         Total
                       code consumption                     kind     feed           (gifts.)
 0 1
 0 2
 0 3
 0 4
 0 5
 Etc.

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                                                                      DATA

           Destination of birds / sex of HoHH, Niger




       Household                             Baptism – Marriages -
                            Celebrations                                    Other
      consumption                                  funerals
 Male          Female     Male      Female     Male       Female     Male       Female

     3,1         2,4      1,3         1,0      0,8          0,5      0,5            8,0




            Source: RGAC 2004-2007, Niger
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     5 - Time-use, Ethiopia
     Source: Ethiopian Agricultural Sample Enumeration Miscellaneous Questions – 2001/02 (1994 E.C.)




     21         How much time do men and women spend in the household on each
     of the following agricultural activities? Use the codes given below the table
                                                                      Adults                    Children
      S/N    Activity                                         Male             Female    Boys           Girls
                                                             (code)            (code)   (code)         (code)
      21.1   Tilling                                          |__|              |__|     |__|              |__|
      21.2   Sowing                                           |__|              |__|     |__|              |__|
      21.3   Weeding                                          |__|              |__|     |__|              |__|
      21.4   Harvesting                                       |__|              |__|     |__|              |__|
      21.5   Feeding/Treating                                 |__|              |__|     |__|              |__|
      21.6   Milking                                          |__|              |__|     |__|              |__|
      21.7   Marketing of agricultural products               |__|              |__|     |__|              |__|

        Codes:
        1 = Not participated                              4 = Three fourth of the time (3/4)
        2 = One fourth of the time (1/4)                  5 = Full time
32      3 = One half of the time (1/2)                    6 = Not applicable
                                                                                                                                                                 DATA

                     5 -2 - Division of Labour, Tanzania


                       Chart 5.17 Percent of Households by Type of Labour - MALE Headed                                     Chart 5.18 Percent of Households by Type of Labour
                                 Households                                                                                            - Female Headed Households
     Off - farm Income Generation                                                               Off - farm Income Generation
                        Fish Farming                                                                               Fish Farming
                              Fishing                                                                                    Fishing
                          Beekeeping                                                                                 Beekeeping
                        Making Beer                                                                                Making Beer
      Building / Maintaining Houses                                                              Building / Maintaining Houses
              T imber Wood Cutting                                                                       T imber Wood Cutting
                        Pole Cutting                                                                               Pole Cutting
                 Collecting Firewood                                                                        Collecting Firewood
                   Collecting Water                                                                           Collecting Water
                    Poultry Keeping                                                                            Poultry Keeping




                                                                                           Type of Labour
Type of Labour




                          Pig Rearing                                                                                Pig Rearing
                              Milking                                                                                    Milking
           Goat & Sheep Marketing                                                                     Goat & Sheep Marketing
              Goat & Sheep Herding                                                                       Goat & Sheep Herding
              Goat & Sheep Rearing                                                                       Goat & Sheep Rearing
                   Cattle Marketing                                                                           Cattle Marketing
                      Cattle Herding                                                                             Cattle Herding
                      Cattle Rearing                                                                             Cattle Rearing
                     Crop Marketing                                                                             Crop Marketing
                    Crop Processing                                                                            Crop Processing
                          Harvesting                                                                                 Harvesting
                    Crop Protection                                                                            Crop Protection
                             Weeding                                                                                    Weeding
                             Planting                                                                                   Planting
Soil Preparation by Oxen / T ractor                                                        Soil Preparation by Oxen / T ractor
           Soil Preparation by Hand                                                                   Soil Preparation by Hand
                       Land Clearing                                                                              Land Clearing
                                       0%        20%        40%     60%      80%    100%                                            0%        20%        40%      60%      80%    100%
             Head of Household Alone        Adults Males             Adult Female                         Head of Household Alone        Adults Males              Adult Female

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             Adults                         Boys                     Girls                                Adults                         Boys                      Girls
             Boys
          Percent & Girls                   All Household Members    Hired Labour                         Boys
                                                                                                       Percent & Girls                   All Household Members     Hired Labour
      8/9 – Food security / Poverty indicators Tanzania


     34.6.1 Number of meals the household normally has per day
                                                                                                           |__|
     34.6.2 Number of days the household consumed meat last week
                                                                                                           |__|
     34.6.3 How often did the household have problems in satisfying the food
            needs of the household last year (code)                                                        |__|


         Code 34.6.3
        1 = Never                 3 = Sometimes                 6 = Always
        2 = Seldom                4 = Other

       Source: United Republic of Tanzania – Agricultural Sample Census 2002/2003- Small holder/Small Scale Farmer
34     Questionnaire: Section 34
                                                                                                    DATA
                               8 - Food security
                               Frequency of food shortages, Tanzania


                                                                                    A higher percent male-headed
                             Chart 9.4 Percent of Male and Female Headed            HHs never has food shortage.
                             Households by Frequency of Facing Food Shortages
                        50                                                          A higher percent of female-
                                                                                    headed HHs has often or always
                        40
Percent of Households




                                                                                    food shortages.
                        30
                                                                                    The same pattern appears in the
                        20                                                          regions.

                        10

                         0
                               Never     Seldom    Sometimes   Often     Always
                              Frequency of Food S hortage        Male      Female

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     4. Remaining challenges




36
                                                 Discussion points

     4.1 – Remaining challenges


        analysis of available
         sex-disaggregated data




                    use sex-disaggregated data –
                     policy-making, implementation & impact assessment


37
                                    Discussion points
     4.2 - Remaining challenges



        integration national
         statistical systems




                   Progress & impact indicators
38
                                    Discussion points
     4.3 - Remaining challenges

     IMPROVED DATA COLLECTION
        Labour


                     Decision-making


        Responsibilities
39
                                  Discussion points

     4.4 – Remaining challenges




       Increasing
sex-disaggregated data
   in COUNTRY STAT
40
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