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Estimating a health production function for Sub-Saharan Africa (SSA)

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  • Bichaka Fayissa
  • Paulos Gutema

Abstract

The paper estimates a health production function for Sub-Saharan Africa based on the Grossman (1972) theoretical model that treats social, economic, and environmental factors as inputs of the production system. In estimating this function, socioeconomic and environmental factors such as income per capita, illiteracy rate, food availability, ratio of health expenditure to GDP, urbanization rate, and carbon dioxide emission per worker are specified as determinants of health status. The parameters of the function are estimated by one-way and two-way fixed and random effects model of panel data analyses. The results of the two-way random effect model suggest that an increase in income per capita, a decrease in illiteracy rate, and an increase in food availability are strongly associated with an improvement in life expectancy at birth. Overall, the results imply that a health policy which may focus on the provision of health services, family planning programs, and emergency aids to the exclusion of other socioeconomic and environmental aspects may do little to improve the current health status of the region.

Suggested Citation

  • Bichaka Fayissa & Paulos Gutema, 2005. "Estimating a health production function for Sub-Saharan Africa (SSA)," Applied Economics, Taylor & Francis Journals, vol. 37(2), pages 155-164.
    • Handle: RePEc:taf:applec:v:37:y:2005:i:2:p:155-164
    DOI: 10.1080/00036840412331313521
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    References listed on IDEAS

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    1. Michael Grossman, 1972. "The Demand for Health: A Theoretical and Empirical Investigation," NBER Books, National Bureau of Economic Research, Inc, number gros72-1, January.
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    Cited by:

    1. Micheal Kofi Boachie & K. Ramu & Tatjana Põlajeva, 2018. "Public Health Expenditures and Health Outcomes: New Evidence from Ghana," Economies, MDPI, vol. 6(4), pages 1-25, October.
    2. Idrissa Ouedraogo & Issa Dianda & Iyewumi Titilope Adeyele, 2020. "Institutional Quality and Health Outcomes in Sub-Saharan Africa," Research in Applied Economics, Macrothink Institute, vol. 12(4), pages 22-45, December.
    3. Bergh, Andreas & Nilsson, Therese, 2010. "Good for Living? On the Relationship between Globalization and Life Expectancy," World Development, Elsevier, vol. 38(9), pages 1191-1203, September.
    4. Zhang, Zhenhua & Zhang, Guoxing & Su, Bin, 2022. "The spatial impacts of air pollution and socio-economic status on public health: Empirical evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    5. Halicioglu, Ferda, 2011. "Modeling life expectancy in Turkey," Economic Modelling, Elsevier, vol. 28(5), pages 2075-2082, September.
    6. Ouedraogo, Idrissa, 2026. "Effects of economic freedom on life expectancy in Africa," Social Science & Medicine, Elsevier, vol. 388(C).
    7. Kahouli, Bassem & Omri, Anis & Afi, Hatem, 2024. "Technological innovations and health performance: Effects and transmission channels," Technological Forecasting and Social Change, Elsevier, vol. 204(C).
    8. Uche Abamba Osakede, 2022. "Infrastructure and Health System Performance in Africa," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 20(4 (Winter), pages 375-400.
    9. Tirivayi, Nyasha & Groot, Wim, 2011. "Health and welfare effects of integrating AIDS treatment with food assistance in resource constrained settings: A systematic review of theory and evidence," Social Science & Medicine, Elsevier, vol. 73(5), pages 685-692, September.
    10. Courage Mlambo & Phillip Ngonisa & Bhekabantu Ntshangase & Nomusa Ndlovu & Bongekile Mvuyana, 2023. "Air Pollution and Health in Africa: The Burden Falls on Children," Economies, MDPI, vol. 11(7), pages 1-18, July.

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