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TRAIL BLAZERS, TECHNICIANS, ADVISORS, POLICY MAKERS, AND AMBASSADORS

TRAIL BLAZERS, TECHNICIANS, ADVISORS, POLICY MAKERS, AND AMBASSADORS. 3 rd Africa Symposium on Statistical Development 3-7 December 2007 “Best Practice & Exchanging Experience: Africa 2010 Round of Population and Housing Censuses”.

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TRAIL BLAZERS, TECHNICIANS, ADVISORS, POLICY MAKERS, AND AMBASSADORS

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  1. TRAIL BLAZERS, TECHNICIANS, ADVISORS, POLICY MAKERS, AND AMBASSADORS 3rd Africa Symposium on Statistical Development 3-7 December 2007 “Best Practice & Exchanging Experience: Africa 2010 Round of Population and Housing Censuses” 3rd Africa Symposium on Statistical Development

  2. Explaining persistent high fertility in Uganda using ethnicity; A case of Ateso and Basoga ethnic groups of Uganda. Lubaale Yovani A Moses Institute of Statistics and Applied Economics, Makerere University 3rd Africa Symposium on Statistical Development

  3. Outline of the presentation • Introduction • Ethnicity in Uganda • Ethnicity and fertility • Hypotheses, Data source and analysis • Findings • Current ASFR & TFR (Ateso & Basoga) • Geographical location • Rural urban • Possession of transport goods • Source of information • Educational level • Source of livelihood • Marital status • Proportion in the district • Discussion and conclusion 3rd Africa Symposium on Statistical Development

  4. Population increase in Uganda • Uganda is population doubles in less than 25 years. • This is due to high Total fertility rates which have not changed over the last 60 + years. • Implications high growth rates higher than economic growth rates, hence increased poverty, increasing population density • * Used a different method in the analysis as opposed to what we are using today • + Not all recodes were used for the analysis 3rd Africa Symposium on Statistical Development

  5. Ethnicity in Uganda 3rd Africa Symposium on Statistical Development

  6. Ethnic behaviours • Data collected about ethnicity and religion but very little analysis done • Ethnic and religious belonging do explain many behaviours and attitudes of individuals but little analysis done e.g • Can we use ethnicity in explaining high fertility, constant wars in certain regions within the African continent? • Do we need specific policy implications related to ethnicity for example hygiene behaviour? • Is there a similarity between religion and ethnicity that can help us understand our populations better? • Can we analyze this data which is already in existence to help good policy formulation • Can we recommend after the Ugandan experience that ethnic belonging should be among the major questions to include in our censuses? 3rd Africa Symposium on Statistical Development

  7. Hypotheses, data sources and methodology • Hypotheses • The fertility behaviour of Basoga and Ateso ethnic groups in different districts are similar. • After controlling for socioeconomic differences, the differentials in fertility between Basoga and Ateso will remain. • One of the main determinants of the differential relationship between ethnicity and fertility at the district level will be the proportion of the population represented by two groups (Soga and Ateso). • Data source: • 2002 Uganda Population and housing census • Gaps: • UBOS only analyzed numbers in regard to ethnicity • Methodology • Direct methods of fertility estimation used. Two measures discussed namely Age specific fertility rate and Total fertility rate (TFR) 3rd Africa Symposium on Statistical Development

  8. Findings: Basoga and Ateso fertility rates 3rd Africa Symposium on Statistical Development

  9. ASFR between Soga and Ateso 3rd Africa Symposium on Statistical Development

  10. TFR selected districts in Uganda among Basoga and Ateso • Can geographical location determine fertility differences between members of the same ethnicity? 3rd Africa Symposium on Statistical Development

  11. Rural-urban • Does residence (rural-urban) affect ethnicities the same way? 3rd Africa Symposium on Statistical Development

  12. Fertility by Possession of TV and radio in household • Fertility of individuals with and without a TV is similar to Urban-rural fertility 3rd Africa Symposium on Statistical Development

  13. Fertility by Possession of transport goods in household Does the type of transport good an individual has determine the fertility outcome or it’s a measure economic ability? 3rd Africa Symposium on Statistical Development

  14. Fertility and source of information • Fertility is highest among those whose source of information is by word of mouth and lowest among those whose source o information was fixed form 3rd Africa Symposium on Statistical Development

  15. Fertility and educational level • Controlling for literacy, the Ateso have a higher fertility compared to the Basoga. • Within the same ethnicity, the difference between literate and illiterate Ateso is same as difference between literate and illiterate Basoga at 1.6 and 1.5 children respectively 3rd Africa Symposium on Statistical Development

  16. Source of livelihood • In all categories of livelihood except those engaged in trade, the fertility of Ateso is higher than that of the Basoga. • This implies that livelihood cannot be used to explain the slight difference in fertility between the Ateso and the Basoga. 3rd Africa Symposium on Statistical Development

  17. Marital status and fertility • Fertility for both ethnic groups was highest among the monogamous marital union. • The highest difference between Ateso and Basoga is among the divorced. • Non marital fertility is also high more than that of developed and some sub Saharan Africa. 3rd Africa Symposium on Statistical Development

  18. Proportion of Basoga and Ateso within the district and fertility determination 3rd Africa Symposium on Statistical Development

  19. Proportion of Basoga and Ateso, continued 3rd Africa Symposium on Statistical Development

  20. Recommendations • Unless ethnicity is deemed to a very sensitive issue, it should be included as a core question • There is need for more and deeper analysis in regard to ethnicity and religion particularly in relation to fertility. • The data from the Uganda census on ethnicity and religion should be used as model for other statistical offices before they can adopt these questions. Further analysis and presentation should be encouraged in future symposiums • CSOs should ensure that they have copies of papers, dissertations, and other publications that used data from these characteristics the Central Statistical offices is kept. • There is need to establish a formal data sharing arrangement between academic training institutions and CSO 3rd Africa Symposium on Statistical Development

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