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HIV Prevalence and Poverty in Africa: Micro and Macro-Econometric Evidence applied to Burkina-Faso

Author

Listed:
  • Jean-Pierre Lachaud

    (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique)

Abstract

Based on the data of the Demographic and Health Survey, and of the Household Priority Survey, carried out in 2003, the present study, examining the factors of the HIV prevalence in Burkina Faso, provides two conclusions. Firstly, the fight against poverty is not necessarily a means of reducing at the same time in a drastic way the HIV/AIDS prevalence, an assertion based on several elements of empirical analysis. First of all, the concentration curve, measuring the « socioeconomic » inequality of the seroprevalence, is « pro-poor ». Then, the micro-econometric estimates of the probit models suggest a positive relation between the HIV prevalence of the adult women and men, and the standard of living of the individuals. At the same time, the probit models highlight a probability of HIV prevalence increasing with : (i) the age, and ; (ii) the localization in Ouagadougou, the capital, and in the majority of the areas of the west and south-west of the country, compared to the other zones. On the other hand, the sexual relations with condoms reduce the chances of seroprevalence, an effect growing with the wealth of the households. Lastly, the macro-econometric approach reveals the existence of a positive (negative) relation between, on the one hand, the level of the regional HIV prevalence, and, on the other hand, the average monetary provincial standard of living (the poverty) of the households. At the same time, the relation between the HIV prevalence and the poverty, apprehended at the regional level, is not linear. Moreover, the estimate of the spatial econometrics models indicates an impact of the crisis of Côte d’Ivoire on the HIV prevalence in Burkina Faso, consecutively with the massive return of a large number of refugees, displaced or repatriated persons originating from Côte d’Ivoire – in particular, since 2000 –, country where the seroprevalence is, on average, five times higher than in Burkina Faso. Secondly, and correlatively, the relation between the HIV pre
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Jean-Pierre Lachaud, 2007. "HIV Prevalence and Poverty in Africa: Micro and Macro-Econometric Evidence applied to Burkina-Faso," Post-Print hal-00404908, HAL.
    • Handle: RePEc:hal:journl:hal-00404908
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    Citations

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    Cited by:

    1. Djemaï, Elodie, 2008. "Risk Taking of HIV-Infection and Income Uncertainty: Empirical Evidence from Sub-Saharan Africa," MPRA Paper 15605, University Library of Munich, Germany, revised 09 Jan 2009.
    2. repec:dau:papers:123456789/7310 is not listed on IDEAS
    3. repec:dau:papers:123456789/7314 is not listed on IDEAS
    4. Durevall, Dick & Lindskog, Annika, 2012. "Economic Inequality and HIV in Malawi," World Development, Elsevier, vol. 40(7), pages 1435-1451.
    5. Martine AUDIBERT, 2008. "Endemic diseases and agricultural productivity: Challenges and policy response," Working Papers 200823, CERDI.
    6. DJEMAI, Elodie, 2018. "Roads and the spread of HIV in Africa," Journal of Health Economics, Elsevier, vol. 60(C), pages 118-141.
    7. Fabrice Murtin & Federica Marzo, 2013. "Hiv/Aids And Poverty In South Africa: A Bayesian Estimation Of Selection Models With Correlated Fixed-Effects," South African Journal of Economics, Economic Society of South Africa, vol. 81(1), pages 118-139, March.
    8. Martine AUDIBERT, 2009. "Issues and Challenges of Measurement of Health:Implications for Economic Research," Working Papers 200922, CERDI.
    9. Karlsson, Martin & Nilsson, Therese & Pichler, Stefan, 2014. "The impact of the 1918 Spanish flu epidemic on economic performance in Sweden," Journal of Health Economics, Elsevier, vol. 36(C), pages 1-19.
    10. repec:spo:wpmain:info:hdl:2441/5lbapr8bjc81qrd7pa70f0iqp1 is not listed on IDEAS
    11. Bruno Arpino & Elisabetta De Cao & Franco Peracchi, 2011. "Using panel data to partially identify HIV prevalence When HIV status is not missing at random," Working Papers 048, "Carlo F. Dondena" Centre for Research on Social Dynamics (DONDENA), Università Commerciale Luigi Bocconi.
    12. Wendy Janssens & Jacques Gaag & Tobias Rinke de Wit & Zlata Tanović, 2014. "Refusal Bias in the Estimation of HIV Prevalence," Demography, Springer;Population Association of America (PAA), vol. 51(3), pages 1131-1157, June.
    13. Filippini, M. & Heimsch, F. & Masiero, G., 2014. "Antibiotic consumption and the role of dispensing physicians," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 242-251.
    14. Djemaï, Elodie, 2008. "Is the risk taking of HIV-infection influenced by income uncertainty? : Empirical Evidence from Sub-Saharan Africa," MPRA Paper 11731, University Library of Munich, Germany.
    15. Ibrahim Kasirye, 2016. "HIV/AIDS Sero-prevalence and Socio-economic Status: Evidence from Uganda," African Development Review, African Development Bank, vol. 28(3), pages 304-318, September.
    16. Fabrice Murtin & Federica Marzo, 2007. "HIV/AIDS and Poverty in South Africa: a Bayesian Estimation," Cahiers de recherche 07-08, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    17. Marjorie Opuni & Amber Peterman & David Bishai, 2011. "Inequality in prime‐age adult deaths in a high AIDS mortality setting: does the measure of economic status matter?," Health Economics, John Wiley & Sons, Ltd., vol. 20(11), pages 1298-1311, November.
    18. Elodie Djemai, 2017. "Roads and the Spread of AIDS in Africa," Working Papers DT/2017/16, DIAL (Développement, Institutions et Mondialisation).
    19. Poulin, Michelle & Dovel, Kathryn & Watkins, Susan Cotts, 2016. "Men with Money and the “Vulnerable Women” Client Category in an AIDS Epidemic," World Development, Elsevier, vol. 85(C), pages 16-30.
    20. de Walque, Damien, 2006. "Discordant couples : HIV infection among couples in Burkina Faso, Cameroon, Ghana, Kenya, and Tanzania," Policy Research Working Paper Series 3956, The World Bank.

    More about this item

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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