<?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2d1 20170631//EN" "JATS-journalpublishing1.dtd"> <ArticleSet> <Article> <Journal> <PublisherName>ajhe</PublisherName> <JournalTitle>African Journal of Health Economics</JournalTitle> <PISSN>C</PISSN> <EISSN>o</EISSN> <Volume-Issue>Volume 10 Issue 2</Volume-Issue> <PartNumber/> <IssueTopic>Multidisciplinary</IssueTopic> <IssueLanguage>English</IssueLanguage> <Season>December 2021</Season> <SpecialIssue>N</SpecialIssue> <SupplementaryIssue>N</SupplementaryIssue> <IssueOA>Y</IssueOA> <PubDate> <Year>2021</Year> <Month>12</Month> <Day>1</Day> </PubDate> <ArticleType>Review & Research</ArticleType> <ArticleTitle>Is there a life expectancy Preston Hypothesis for Africa?</ArticleTitle> <SubTitle/> <ArticleLanguage>English</ArticleLanguage> <ArticleOA>Y</ArticleOA> <FirstPage>19</FirstPage> <LastPage>34</LastPage> <AuthorList> <Author> <FirstName>Douglason Godwin Omotor and Uche Abamba</FirstName> <LastName>Osakede</LastName> <AuthorLanguage>English</AuthorLanguage> <Affiliation/> <CorrespondingAuthor>N</CorrespondingAuthor> <ORCID/> </Author> </AuthorList> <DOI>doi.org/10.35202/AJHE.2021.1021934</DOI> <Abstract>Background: The inconclusive evidence surrounding the Preston hypothesis and scarcity of findings in Africa motivated the focus of this study. This paper examined the Preston hypothesis for all countries in Africa, over the period 1960-2018. Findings are shown for the effect of per capita income and income-proxy variables on life expectancy. Methods: Using a two-way fixed effect model, bivariate and multivariate regression were used to determine the strength of income and its proxy variables in explaining health. The direction of causality between income and health was also examined using the Dumitrescu __ampersandsign Hurlin (DH) panel granger causality test. The data used were sourced from the World Development Indicators (WDI) provided by the World Bank. Findings: The study revealed the existence of the Preston hypothesis but only in the bivariate model. Findings showed stronger effect of the proportion of Investment to GDP ratio than per capita income and other income proxy variables in explaining life expectancy. The multivariate result also showed stronger effect of investment to GDP ratio, immunization rate and fertility rate on life expectancy than per capita income and proxy variables for income. The DH test revealed reverse causality between per capita income and life expectancy. Conclusion: There is weak evidence of the existence of the Preston Hypothesis in Africa. The gains in life expectancy are largely attributed to investment, immunization and fertility rate than per capita income. Efforts to improve health in Africa should give top priority to raising investment, increase in immunization rate and reduction in fertility rate. This focus should rank high in policy maker’s agenda.</Abstract> <AbstractLanguage>English</AbstractLanguage> <Keywords>Preston Hypothesis, Life expectancy, Per capita income, Fixed Effect, Panel Granger causality</Keywords> <URLs> <Abstract>https://ajhe.org.in/ubijournal-v1copy/journals/abstract.php?article_id=13592&title=Is there a life expectancy Preston Hypothesis for Africa?</Abstract> </URLs> <References> <ReferencesarticleTitle>References</ReferencesarticleTitle> <ReferencesfirstPage>16</ReferencesfirstPage> <ReferenceslastPage>19</ReferenceslastPage> <References>1. Preston SH. The changing relation between mortality and level of economic development. Popul Stud (NY). 1975;29(2):231–48. 2. Mackenbach J, Looman C. Life expectancy and national income in Europe, 1900-2008: an update of Preston’s analysis. Int J Epidemiol. 2013;42(4):1100–10. 3. Angel S. The effect of over-indebtedness on health: comparative analyses for Europe. Kyklos. 2016;69(2):208–27. 4. Shkolnikov VM, Andreev EM, Tursun-zade R, Leon DA. Patterns in the relationship between life expectancy and Gross Domestic Product in Russia in 2005–15: a cross-sectional analysis. Lancet Public Heal. 2019;4(4):4: e181–88. 5. WorldBank. 85% of Africans live on less than $5.50 per day [Internet]. 2021. Available from: https://blogs.worldbank.org/opendata/85-africans-live-less-550-day 6. UNDP. Africa human development report. New York; 2016. 7. Husain MJ. The Preston-curve and the contribution of health to economic well-being: evidence from the DHS of India and four African Countries. J Dev Areas. 2014;48(2):85–121. 8. Erdil E, Yetkiner HI. A panel data approach for income-health causality. Hamburg; 2004. Working Papers FNU-47, Research unit Sustainability and Global Change, Hamburg University 9. Georgios G, Pineda J, Rodrand;iacute;guez F. Has the Preston curve broken down. 2010. Human Dev Research Paper 2010/32. 10. Garcia J, Narvil J, Oh S. Modern day evaluation of the Preston curve?: the relationship between life expectancy and income. Georgia Tech Library; 2016. 11. Spence M, Lewis M. Health and Growth : Commission on Growth and Development. The World Bank Group, 2633. 2009 12. Preston SH. The changing relation between mortality and level of Economic Development. Int J Epidemiol. 2007;36(3):484–90. 13. Bloom DE, Kuhn M, Prettner K. Health and economic growth. IZA Discussion Papers 11939, Institute of Labor Economics (IZA). 2018. 14. Pritchett L, Summers LH. Wealthier is healthier. J Hum Resour. 1996;31(4):841–68. 15. WHO. Health technology assessment. Geneva, Switzerland; 2020. 16. Masum H, Lackman R, Bartleson K. Developing global health technology standards: what can other industries teach us? Global Health. 2013;9(49). 17. Dalgaard C-J, Strulik H. Optimal aging and death: understanding the Preston Curve. J Eur Econ Assoc. 2012;12(3):672–701. 18. Lindahl M. Estimating the effect of income on health and mortality using lottery prizes as an exogenous source of variation in income. J Hum Resour. 2005;40(1):144–68. 19. Jetter M, Laudage S, Stadelmann D. The intimate link between income levels and life expectancy?: global evidence from 213 Years. Soc Sci Q. 2019;1–17. 20. Bersvendsen T, Ditzen J. XTHST: Testing for slope homogeneity in Stata. 2020. (11). 21. Samargandi N, Fidrmuc J, Ghosh S. Is the relationship between financial development and economic growth monotonic? evidence from a sample of middle-income countries. CESifo Working Paper Series 4743, CESifo. 2014. 22. Pesaran M, Yamagata T. Testing slope homogeneity in large panels. J Econ. 2008;142(1):50–93. 23. Blomquist J, Westerlund J. Testing slope homogeneity in large panels with serial correlation. Econ Lett. 2013;121(3):374–8. 24. Ditzen J, Bersvendsen T. XTHST: Stata module to test slope homogeneity in large panels, statistical software components S458714. Boston College Department of Economics, 2019. 25. Hurlin C, Mignon V. Second generation panel unit root tests. 2007. https://halshs.archives-ouvertes.fr/halshs-00159842/document 26. Mirestean A, Tsangarides CG. Growth determinants revisited using limited-information bayesian model averaging. J Appl Econom. 2016;31(1):106–32. 27. Tang R, S. T. Democracy’s Unique advantage in promoting economic growth: quantitative evidence for a new institutional theory. Kyklos. 2018;71(4):642–66. 28. Bruckner MAC, Tesei A. Oil price shocks, income, and democracy. Rev Econ Stat. 2012;94(2):389–99. 29. Nikolaev B, Salahodjaev R. Historical prevalence of infectious diseases, cultural values, and the origins of economic institutions. Kyklos. 2017;70(1):97–128. 30. Ang JB, Fredriksson PG, Nurhakim ALB, Tay EH. Sunlight, disease, and institutions. Kyklos. 2018;71(3):374–401. 31. Sharma R. Health and economic growth?: Evidence from dynamic panel data of 143 years. PLoS One. 2018;13(10):1–20. 32. Osakede UA, Sanusi GP. Effect of energy consumption on health outcome in Nigeria and South Africa?: the ARDL bound testing approach. African J Sustain Dev. 2018;8(2):2018–9. 33. Osakede UA, Ajayi PI. Air pollution and health status in Sub-Sahara Africa (SSA). J Econ Sustain Dev. 2019;10(22):26–33. 34. Dumitrescu E, Hurlin C. Testing for Granger non-causality in heterogeneous panels. Economic Modelling. 2012;29(4):1450–60. 35. Hurlin C, Venet B. Granger causality tests in panel data models with fixed coefficients. Mimeo, Univ Paris IX. 2001. 36. Hurlin C. Testing granger causality in heterogenous panel data models with fixed coefficients. Post-Print halshs-00363356, HAL. 2008. 37. Lin ES, Ali HE. Military Spending and Inequality: panel granger causality test. 2009. J Peace Res. 2009; 46(9):671-685. 38. Lopez L, Weber S. testing for Granger causality in panel data. 2017. The Stata Journal. 2017;17(4): 972–984 39. Granger CW. Investigating causal relations by econometric models and cross-spectral methods. Econometrica. 1969;37(3):424–438. 40. WorldBank. World Development Indicators. World Bank. 2019. 41. UN. World mortality, 2019. 2020. 42. WHO. Life expectancy situation. Geneva, Switzerland; 2020. 43. WorldBank. Country and lending groups, country classification. 2020. 44. WHO. Immunization coverage. 2020. 45. WorldBank. Literacy rate, adult total (% of people ages 15 and above) - Sub-Saharan Africa. 2020. 46. UNESCO. Adult and youth literacy: global trends in gender parity. 2010. 47. UNDP. Human Development Report 2019: Beyond income, beyond averages, beyond today: Inequalities in human development in the 21st century. 2019. 48. WorldBank. Fertility rate, total (births per woman. 2020. 49. UN. World Family planning: highlights. 2017. 50. UNICEF. Literacy among youth is rising, but young women lag behind. 2020. 51. Aboagye S, Turkson E. An empirical investigation of per capita income convergence hypothesis in Sub-Saharan Africa. CSAE Conference. 2014. 52. Adenikinju OO, Osakede UA. Per capita income and health outcome convergence in the Economic Community of West African States. Nigerian J Economic and Soc Stud. 2020; 62(3). 53. Caldwell J.C. Cultural and social factors Influencing Mortality Levels in Developing Countries. Ann Am Acad Pol Soc Sci. 1990;510. 54. Prettner K, Bloom DE, Strulik H. Declining fertility and economic well-being: do education and health ride to the rescue? Labour Econ. 2013;22:70–79. 55. Grossman M. The human capital model. In: A.J. J e. C, editor. Handbook of Health Economics. Amsterdam: Newhouse; 2000. 56. Chen W, Clarke JA, N. R. Health and wealth: short panel Granger causality tests for developing countries. J Int Trade Econ Dev An Int Comp Rev. 2014;23(6).</References> </References> </Journal> </Article> </ArticleSet>