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									DUAL LANGUAGE REPORTING BY NAIROBI STOCK
       EXCHANGE LISTED COMPANIES


BAA ACCOUNTING IN LESS DEVELOPING AND EMERGING ECONOMIES
                  SPECIAL INTEREST GROUP



               BIRMINGHAM BUSINESS SCHOOL
                 UNIVERSITY OF BIRMINGHAM
                      9th JANUARY 2009


              Venancio Tauringana and Musa Mangena
Structure of the Presentation

1. Introduction

2. Objectives of the Study

3. Importance of Dual Reporting

4. Foreign Corporate Ownership in Kenya

5. Corporate Reporting in Kenya

6. Literature Review & Hypotheses Development



                                                2
Structure of the Presentation (Cont)

7. Data and methodology

8. Results and Discussion

9. Summary and Concluding Remarks

10. Further Research




                                       3
1. Introduction

  A unique feature of corporate reporting on the Nairobi Stock
  Exchange (NSE) is dual language reporting. This takes the form of
  some companies presenting the narrative information (and in some
  cases financial statements) in both English and Swahili languages
  side by side (see Tauringana, Kyeyune and Opio, 2008).




                                                                  4
 1. Introduction
Nature of dual reporting (Example): Kenya Airways 2006
1. Introduction
  But what is the status of dual reporting in Kenya?

  Company law
  Kenyan Companies Act (1978, Chapter 486) states that:

 “communication between the company and its members should be in
  a manner acceptable to both parties but financial accounts should
  be kept in English”.




                                                                  6
1. Introduction
  What is the status of dual reporting in Kenya? (Cont)

  Nairobi Stock Exchange

  “Where any of the documents ..… are not in the
   English language, translations into English must also be available
   for inspection”

 NSE Listing Manual (Third Schedule Part A) 2002




                                                                        7
1. Introduction (cont)

Since dual reporting is voluntary on the NSE :

(1) what motivates companies to report using dual language ?
    (objectives of the study)

(2) What are the potential benefits of dual reporting?
    (Importance of the study)




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2.   Objectives of the Study

     (1) To investigate the extent of dual language reporting on the
         Nairobi Stock Exchange

     (2) To determine whether foreign owned companies are more
         likely to use dual languages in their annual reports.

     (3) In addition, investigate whether substantial institutional
         investment, proportion of non-executive directors, audit
         committee finance expertise, company size, company age,
         gearing are associated with dual language reporting.



                                                                       9
3. The potential benefits of dual reporting

(1) Dual reporting is likely to increase understandability of the annual
   report (therefore usefulness of the annual report in Kenya)

(2) This may enable a wide range of stakeholders to engage with the
   company

(3) This includes private individual investors (existing & potential). Due
   to low levels of education attainment, the private investors are more
   likely to comprehend annual report messages in Swahili than
   English.




                                                                           10
3. The potential benefits of dual reporting

(4) Companies on the NSE are required to reserve 25% of any Initial
    Public Offers (IPOs) for local investors (The Capital Markets
    Authority 2002).

(5) Understandability of the annual report message can lead to
    economic growth as existing private individual investors buy more
    shares and potential private investors buy shares in the companies
    for the first time.

(7) Share ownership by more private individuals means that the wealth
    generated in the country is equitably distributed. Equitable
    distribution of wealth is a key indicator of poverty reduction.



                                                                         11
4. Foreign Corporate Ownership in Kenya
 Kenya: Country's wealth in foreign hands

  “If Kenya were a cake to be shared out, Kenyans would only lay claim to 31
   per cent of the country‟s total wealth. The rest would go to foreigners”.

   In 2004, tea, tourism, flowers and coffee earned the country Sh140 billion,
   nearly half of the annual national budget. Agriculture, tourism and banking,
   which combined to bring in the country‟s largest earnings, are in foreign
   hands.


  http://www.kimmediagroup.com/content/view/53/668/




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4. Foreign Corporate Ownership in Kenya (cont)

Tea Sector
•   EearnedSh43.5 billion in 2006 but is in hands of six companies largely
    foreign

•   The Big Six in the tea sector are : Unilever Tea Kenya, Kakuzi Ltd,
    Williamson Tea Company, Kapchorua Tea, Limuru Tea Company and
    Sasini Coffee and Tea.

http://www.kimmediagroup.com/content/view/53/668/



                                                                             13
4. Foreign Corporate Ownership in Kenya

Tea Sector (Cont)

•   The British-owned Brooke Bond Group holds:

    43.1 million shares of the total 48.8 million shares issued in Univeler Tea
    Kenya.

    54 per cent of the total 3.9 million shares issued in Limuru Tea Company

•   In Kakuzi Ltd, foreigners have a total shareholding of 68.3 per cent of the
    total 19.6 million shares issued.

     http://www.kimmediagroup.com/content/view/53/668/


                                                                                  14
4. Foreign Corporate Ownership in Kenya

Tourism

•   Earned Sh42 billion in 2005 that came from tourism ( Hotels, airlines, and
    travel/booking agents)

•   Of Kenya‟s 290,000-plus tourist hotel bed spaces, foreign hoteliers
    own 74.3 per cent

•   Tour flights to Kenya are entirely in the hands of foreign airlines.




                                                                                 15
4. Foreign Corporate Ownership in Kenya

Tourism (Cont)

• Internal travel foreigners own 7 of the 11 leading local tour travel
  firms.


  “At the end of the day, tourism in Kenya remains a foreigners‟
   enclave with indigenous Kenyans left to scratch the surface on petty
   trades like selling curios and prostitution”.

  http://www.kimmediagroup.com/content/view/53/668/




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4.    Foreign Corporate Ownership in Kenya

Horticulture

•     Earned Kenya Sh28.2 billion in 2006, is the country‟s third largest
     foreign exchange earner.
•
     Of the 44 certified companies dealing with horticulture products, 26
     are foreign-owned.

•     But an even bigger irony is that the leading 10 players in the
     industry are all foreign-owned and take 83 per cent of the total
     income from the sector.


                                                                            17
4. Foreign Corporate Ownership in Kenya:

Banks

• The leading two foreign banks have 71.4% market share

•   Barclays Bank plc of London owns 68 per cent stake in Barclays
    Bank of Kenya.

• Standard Bank owns 81 per cent shareholding in Standard
  Chartered Bank Kenya Ltd.




                                                                     18
5. Corporate Reporting in Kenya

(1) Companies Act, 1978 (Chapter 486) is based & substantially the
    same as the UK Companies Act 1948 (Ogola, 2000).

(2) Provisions in respect of accounts and audit (Sections 147-163).
    (a) duty to prepare the financial statements (section 148)
    (b) Contents of group accounts (section 152)




                                                                      19
5. Corporate Reporting in Kenya

• Companies Act requires appointment of auditors who must be
  members of the Institute of Certified Public Accountants of Kenya
  (ICPAK) and meet the criteria for an auditor as laid out in the
  Accountants Act (1977).

(2) Capital Market Authority (2002) listing rules state that every company
   shall prepare an annual report containing audited annual financial
   statements within four months of the close of its financial year.




                                                                        20
6. Literature Review & hypotheses development

   Explanation of (motives behind) dual reporting on NSE

   (1) Pursuit of legitimacy (Stanton and Stanton, 2002).

   (2) Impression management (Leventis and Weetman, 2004,
     & Beattie and Jones, 2001)




                                                            21
6.     Literature Review & hypotheses development

     Legitimacy
     “ … A condition or status which exists when the entity‟s value
       system is congruent with the value system of the larger social
       system of which the entity is part.. When a disparity, actual or
       potential, exists between the two value systems, there is a threat
       to the entity‟s legitimacy”. (Lindbolm, 1994).




                                                                            22
6.     Literature Review & hypotheses development

     Legitimacy (Cont)
     Dowling and Pfeffer (1975,p. 125) suggest companies adopt some
     of the following to become or appear legitimate:

     (1) alter definition of legitimacy through communication so that it
       conforms to the organisation‟s present practices, outputs and
       values

     (2) become identified through communication, with symbols, values
         and institutions which have strong base of social legitimacy



                                                                           23
6. Literature Review & hypotheses development

 Legitimacy (Cont)

  Information (in a language understandable to the target audience)
  is a major element that can be employed by organisations to
  manage (or manipulate) the stakeholder in order to gain their
  support and approval, or distract their opposition and disapproval”
 (De Villiers and Van Staden, 2006)




                                                                        24
6. Literature Review & hypotheses development

   Impression Management
   “refers to the study of behaviours or strategies put in place by an
    individual or organisations to be perceived favourably by others”


   “In accounting impression management theory has been adopted
   and applied to explain response of organisations dealing with
   legitimacy challenges”.

   (Hooghiemstra, 2000).


                                                                         25
6. Literature Review & hypotheses development

   Link between Legitimacy & Impression Management Theories

   “Because legitimacy revolves around the idea of managing societal
    perceptions, the impression management concept can be
    positioned within legitimacy theory” (Cho, 2007).

    “While the symbolic aspects of organisational actions have been
     central to legitimation researchers, textually-mediated discourses
     [aimed at managing impressions] have more recently been seen
     as fulfilling a similar function (Neu et al., 2002)


                                                                      26
6. Literature Review & hypotheses development

   Why would foreign owned companies want to legitimise & or
   manage impression in Kenya?

  “Hostility to foreign ownership of domestic companies is common
   the world over. By repatriating profits, foreign companies remove
   cash from a home economy. Foreign ownership is often associated
   with the sale of „national assets‟, whether these are real (extracted
   resources) or emblematic (flagship brands)”. Smith (2009).




                                                                      27
6.    Literature Review & hypotheses development

     Why would foreign companies want to legitimise & or manage
     impression in Kenya?

      “Almost £100bn a year is taken out of Africa through dodgy
       accounting practices. Some of the Kenyan flower companies are
       amongst those accused of under-reporting profits in an effort to
       avoid tax. And there's 'transfer pricing' - undervaluing goods when
       they leave Kenya so as to place the profits elsewhere.”

 http://news.bbc.co.uk/1/hi/programmes/file_on_4/6908997.stm




                                                                        28
6. Literature Review & hypotheses development

    Why would foreign companies want to legitimise & or
    manage impression in Kenya?

    BBC file on 4 programme (2005) investigation revealed that:
•     Kenya's official export statistics say almost 50 million kilos of tea
     left there in 2005 bound for Britain

•     But the British import statistics showed 75 million kilos - one and a
      half times as much - arriving here from Kenya.
    http://news.bbc.co.uk/1/hi/programmes/file_on_4/6908997.stm


                                                                          29
6. Literature Review & hypotheses development

    Why would foreign companies want to legitimise & or manage
    impression in Kenya?

Jack Ranguma, a former head of domestic tax for Kenya, told file on 4
programme that :

•      The mismatch was created by customs fraud and companies shipping
       tea to the UK were under-reporting exports in order to avoid paying tax

•      “We want our sisters to stop their corporate citizens who may not be
       paying their due taxes here”.

       Mukhisa Kituyi, Minister for Trade and Industry



                                                                                 30
  Hypotheses
(Based on motives discussed above, legitimacy, impression
 management, other theories and related prior research)

H 1:    Companies which are foreign owned are more likely
       to use dual languages in their annual reports.

H 2:     Companies with a higher percentage of institutional
       shareholding are more likely to use dual
       languages in their annual reports.




                                                               31
  Hypotheses (cont)


H 3:   Companies with a higher proportion of non-executive
        directors are more likely to use dual languages in their annual
       reports.

H 4:   Companies with a higher proportion of finance experts on
        their audit committee are more likely to use dual languages in
       their annual reports.




                                                                          32
H 5:   Big companies are more likely to use dual languages in their
       annual reports than small companies.

H 6:    Companies which have been listed on the Nairobi Stock
        Exchange for a longer period are more likely to use dual
       languages in their annual reports.

H 7:   Companies that are highly geared are more likely to use
       dual languages in their annual reports.



                                                                      33
7. Data and methodology
     (a) Companies listed on NSE as at 1 may 2007 =        48
         Less companies listed for less than 3 years         4
                                                            44
       Companies with eliminated for other reasons            5
       Final sample                                          36



Annual reports analysed (36 X 3)                       =   108




                                                                  34
7.   Methodology (Cont)
     (a) Estimation procedure

     Model :
     DULAR = 0 + 1OWNERS+ 2SUBINS+ 3PRONED +
     4FINXPT + 5LNASSET + 6COMAGE + 7GEARIN + εj




                                                       35
Table 2: Definition of variables included in the regression model
Variable(s)                                                         Definition
Dependent
DULAR                      Dual language reporting, measured as a dummy variable assuming the value of 1 if company’s
                           annual report is published in both Swahili and English; 0 otherwise.
Independent

OWNERS
                           Coded 1 if the company (or the ultimate holding company) is incorporated outside Kenya; 0 otherwise

SUBINS                     Percentage of shares owned or controlled by substantial institutional investors at annual report date.
PRONED                     Number of non-executive directors divided by the total number of directors on the company’s board of
                           directors at the annual report date
FINXPT                     The proportion of financial experts on the audit committee (measured by number of directors with finance
                           background on the audit committee) divided by the total number of directors on the audit committee at the
                           annual report date.
LNASST                     Company size measured in terms of the natural log of total assets at the annual report date

COMAGE                     Period of listing, measured as the difference between the annual report date and date the company

                           as first listed on the NSE.

GEARIN                     Long-term debt divided by shareholders’ funds plus long-term loans at the annual report date.


                                                                                                                                    36
8.    Results and Discussion

(1)   Analysis of dual and non dual reporting companies (Table 2)

(2)   Descriptive statistics of dual and non-dual reporting companies
      (Table 3)

(3)   Descriptive statistics & Chi-square results of sample by dual
      language reporting (Table 4)




                                                                        37
8.   Results and Discussion

(4) Spearman‟s rho correlations among independent variables
    (Table 5)

(5) Results of logistic regression results (Table 6)




                                                              38
Table 2: Sample of companies whose annual reports were examined in the
         study


                                       Number             Proportion
                                       of companies       of companies
                                                              %
Dual language reporting                 66                        61.11

No dual language reporting              42                        38.89

Total                                  108                      100.00




                                                                          39
  Table 3: Descriptive statistics for dual reporting variables
Variables           Dual Language       No Dual Language     Mann-Whitney
                    Reporting           Reporting            U-test
                    (n=66)               (n=42 )
                    Mean                 Mean
                    (Standard dev)      (Standard dev)       (P-value)


SUBINS                 0.4797              0.3974            -1.497
                     (0.2079)             (0.2117)           (0.134)
PRONED                 0.7291              0.6393            -2.892
                      (0.1714)            (0.1737)           (0.004)
FINXPT                 0.3156              0.2155            -3.732
                      (0.1655)            (0.1178)           (0.000)
ASSETS              20,655.55            3546.74             -5.445
                    (28453.16)           (4577.38)           (0.000)
COMAGE                  59.36              60.50                 0.611
                       (26.98)            (24.07)            (0.541)
GEARIN                  0.5458              0.7033           -1.478
                        (0.28)              (0.50)               (0.139)




                                                                            40
Table 4: Descriptive statistics & Chi-square results of sample by dual
         language reporting



                                Dual language    No Dual Language Chi-Square
                               Reporting         Reporting

 OWNERS Coded 0                  54.17%          25.00%             4.383**
             Coded 1             75.00%          45.83%            ________
 *** Significant at the 5% level (two-tailed).




                                                                               41
Table 5: Spearman’s rho Correlations Among Independent Variables


VARIABLE      PRONED        FINXPT      SUBINS      OWNERS LNASST        COMAGE      GEARIN
PRONED            1.000
FINXPT           -0.323**      1.000
SUBINS           -0.524**      0.193* 1.000
OWNERS           -0.309**      0.158 0.459**          1.000
LNASST           -0.020        0.080 -0.129           0.206*    1.000
COMAGE          -0.187        -0.057    0.297**       0.341**   0.234*     1.000
GEARIN          -0.153          -0.057 -0.056         0.045     0.094       0.244*       1.000
**. Corrlation is significant at the 0.01 lvel (2-tailed)
* . Correlation is significant at the 0.05 level (2-tailed)




                                                                                                 42
Table 6: Results of logistic regression results
Coefficient/Standard error/Wald ²
Variables                                                                    Expected                       Model
                                                                             Sign.
Intercept                                                                                                   -28.830
                                                                                                              7.966
                                                                                                             13.097**
Ownership Characteristics
OWNERS                                                                         +                                 4.090
                                                                                                                  1.502
                                                                                                                 7.414**
SUBINS                                                                         +                                 8.631
                                                                                                                 2.870
                                                                                                                 9.043**
Corporate Governance Characteristics
PRONED                                                                         +                            -3.727
                                                                                                             3.411
                                                                                                              1.194
FINXPT                                                                         +                             5.001
                                                                                                              2.302
                                                                                                             4.718*
Company Specific Variables
LNASSET                                                                        +                                9.185
                                                                                                               2.200
                                                                                                              17.423**
COMAGE                                                                         +                              -0.021
                                                                                                               0.18
                                                                                                               1.424
GEARIN                                                                         +                            -13.477
                                                                                                               3.682
                                                                                                              13.395**
Number                                                                                                         108
Constant (-2LL)                                                                                              144.342
Model χ²                                                                                                     8       6       .   2       8       7       *       *




P   s       e       u       d       o       R       ²                                                                            0       .   6       0       0




O       v       e       r       a   l   l   f   i       t                                                        6       1       .   1       %




**.                             Significant at the 1% Level (two-tailed); *. Significant at the 5% level.




                                                                                                                                                                     43
9.   Summary and Concluding Remarks
•    Objective of the research – extent of dual language reporting and
     whether foreign ownership & factors determine dual reporting

•     Foreign ownership, substantial institutional investment, finance
     expertise, company size, gearing are associated with dual reporting

•    Foreign ownership results are consistent with legitimacy and impression
     management theories

•    Policy implication given the potential benefits of dual reporting. Should
     dual reporting be mandatory for all companies?




                                                                                 44
10. Further Research

•   Are annual report in dual language better understood by private
    investors?

• Are private investors more likely to invest in companies that report in
  dual languages

• Does the wider share ownership lead to economic development as
  private shareholders share the country‟s economic wealth?




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