Kodila-Tedika, Oasis and Asongu, Simplice (2015): Intelligence, Human Capital and HIV/AIDS: Fresh Exploration. Published in: Intelligence , Vol. 53, No. November–December (November 2015): pp. 154-159.
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Abstract
This study complements existing literature on the relationship between HIV/AIDS and human capital by introducing previously unexplored indicators as well as more robust empirical strategies. The overarching purpose is to assess whether previous findings on the relationship withstand empirical scrutiny when alternative indicators and methodologies are employed. Four main HIV/AIDS measurements are regressed on intelligence for a maximum of 195 cross-sectional averages over the past decade. The empirical evidence is based on OLS, IWLS and 2SLS. The following findings are established. First, human capital decreases HIV prevalence with the magnitude on ‘Women’s share of population ages 15+ living with HIV’ substantially higher. This implies improving average human capital levels across communities would be more beneficial to girls above the age of 15 living with HIV. The relatively similar negative magnitudes across other dependent variables implies that increasing human capital decreases deaths from HIV/AIDS by almost the same rate as it reduces infections to the disease. Moreover, the HIV infection rate in children between the ages of 0 and 14 does not significantly change with human capital improvements. More policy implications are discussed.
Item Type: | MPRA Paper |
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Original Title: | Intelligence, Human Capital and HIV/AIDS: Fresh Exploration |
Language: | English |
Keywords: | Health; Human capital; Intelligence |
Subjects: | D - Microeconomics > D6 - Welfare Economics > D60 - General I - Health, Education, and Welfare > I1 - Health > I10 - General I - Health, Education, and Welfare > I2 - Education and Research Institutions > I20 - General J - Labor and Demographic Economics > J2 - Demand and Supply of Labor > J24 - Human Capital ; Skills ; Occupational Choice ; Labor Productivity O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O15 - Human Resources ; Human Development ; Income Distribution ; Migration |
Item ID: | 68320 |
Depositing User: | Simplice Asongu |
Date Deposited: | 10 Dec 2015 16:00 |
Last Modified: | 26 Sep 2019 14:58 |
References: | Andrés, R. A., Asongu, S. A., & Voxi, A., (2013). The Role of Formal Institutions on Knowledge Economy, Journal of the Knowledge Economy. http://link.springer.com/article/10.1007%2Fs13132-013-0174-3 Ang, J. B., & Kumar, S., (2014). Financial development and barriers to the cross-border diffusion of financial innovation, Journal of Banking & Finance 39, 43-56. Asongu, S. A., (2014). Globalisation and health worker crisis: what do wealth effects tell us? International Journal of Social Economics, 41(12), 1243-1262. Asongu, S. A., & Nwachukwu, J. C., (2016). The Role of Lifelong Learning in Political Stability and Non-violence: Evidence from Africa, Journal of Economic Studies: Forthcoming. Asongu, S. A., & Nwachukwu, J. C., (2015). Foreign aid volatility and lifelong learning: demand-side empirics to a textual literature, African Governance and Development Institute Working Paper, No. 15/016. Barber, N. (2005). Educational and ecological correlates of IQ: A cross national investigation. Intelligence, 33, 273–284. Bariagaber, H., (2001). Demographic and socio-economic consequences of HIV/AIDS in sub-Saharan Africa, Pula: Botswana Journal of African Studies, 15(2), 168-184. Barro, Robert, (1991). Economic Growth in a Cross-Section of Countries. Quarterly Journal of Economics 106, 407–443. Benhabib, J., Spiegel, M., (1994). The Role of Human Capital in Economic Development: Evidence from Aggregate Cross-Country Data. Journal of Monetary Economics 34, 143–173. Caselli, Francesco, Esquivel, Gerardo, Lefort, Fernando, 1996. Reopening the Convergence Debate: a New Look at Cross-Country Growth Empirics. Journal of Economic Growth 3, 363–389. Cohen, D. & Soto, M. (2007) Growth and Human Capital: Good Data, Good Results. Journal of Economic Growth 12: 51-76. De la Fuente, A. &Doménech, R. (2006) Human Capital in Growth Regressions: How Much Difference Does Data Quality Make? Journal of the European Economic Association 4: 1-36. FAO Statistics Division (2010). Food Balance Sheets. Rome, Italy: Food and Agriculture Organization of the United Nations. Hanushek, E. A. &Woessmann, L. (2008). The Role of Cognitive Skills in Economic Development. Journal of Economic Literature, 46(3), 607-668. Hanushek, E. A., & Kimko, D. D. (2000). Schooling, Labor-Force Quality, and the Growth of Nations. American Economic Review, 90, 1184-1208. Hanushek, E.A. & Woessmann, L. (2009) Do better schools lead to more growth? Cognitive skills, economic outcomes, and causation. IZA Discussion Papers No. 4575 Jones, G. & Schneider, W. J. (2006). Intelligence, human capital, and economic growth: A Bayesian Averaging of Classical Estimates (BACE) approach. Journal of Economic Growth, 11, 71-93. Kanazawa, S. (2006). Mind the gap… in intelligence: Re-examining the relationship between inequality and health. British Journal of Health Psychology, 11, 623–642. Kalonda-Kanyama I, Kodila-Tedika O (2012). Quality of Institutions: Does Intelligence Matter?, Working Papers 308. Economic Research Southern Africa. Kodila-Tedika, O., & Asongu, S. A., (2015a). “The effect of intelligence on financial development: a cross-country comparison”, Intelligence, 51(July-August), pp. 1-9. Kodila-Tedika, O., & Asongu, S. A., (2015a). “Women in Power and Power of Women: the Liberian Experience”, African Governance and Development Institute Working Paper, No. 15/021, Yaoundé. Kodila-Tedika, O., (2014), Governance and Intelligence: Empirical Analysis from African Data, Journal of African Development, 16(1), pp. 83-97 Rindermann, Heiner, Kodila-Tedika, Oasis & Christainsen, Gregory, (2014). Cognitive capital, governance, and the wealth of nations, MPRA Paper 57563, University Library of Munich, Germany. Kodila-Tedika, O., & Mutascu, M., (2014). Tax Revenues and Intelligence: A Cross-Sectional Evidence, MPRA Paper 57581, University Library of Munich, Germany. Kodila-Tedika, O. & Bolito-Losembe, R. (2014), Poverty and Intelligence: Evidence Using Quantile Regression, Economic Research Guardian, (1): 25-32. Krueger, A., & Lindhal, M., (2001). Education for growth: why and for whom? Journal of Economic Literature XXXIX, 1101–1136. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., Vishny, R.W., (1999). The Quality of Government. Journal of Law, Economics, and Organization, 15, 222-279. Levine, R. &Renelt, D. (1992) A sensitivity analysis of cross-country growth regressions. AmericanEconomic Review 82: 942-963. Lutz, W. (2009) Sola schola et sanitate: human capital as the root cause and priority for international development? Philosophical Transactions of the Royal Society B 364: 3031- 3047 Lynn , R. (2012), IQs predict differences in the technological development of nations from 1000 BC through 2000 AD, Intelligence 40 (2012) 439–444. Lynn, R. &Meisenberg, G. in press. The relation of malnutrition with cognitive and economic variables in 120 nations. Personality and Individual Differences. Lynn, R. &Vanhanen, T. (2001) National IQ and economic development: a study of eighty- one nations. Mankind Quarterly 41: 415-435. Lynn, R. &Vanhanen, T. (2002) IQ and the Wealth of Nations. Westport CT: Praeger. Lynn, R. &Vanhanen, T. (2006) IQ and Global Inequality. Augusta GA: Washington Summit. Lynn, R. &Vanhanen, T. (2012a) Intelligence. A Unifying Construct for the Social Sciences. London: Ulster Institute. Lynn, R., &Vanhanen, T. (2012b). National IQs: A review of their educational, cognitive, economic, political, demographic, sociological, epidemiological, geographic and climatic correlates. Intelligence, http://dx.doi.org/10.1016/j.intell.2011.11.004. Lynn, R., Meisenberg, G., Mikk, J., & Williams, A. (2007). National differences in intelligence and educational attainment. Journal of Biosocial Science, 39, 861–874. Mankiw, Gregory, Romer, David, Weil, David, 1992. A contribution to the empirics of growth. Quarterly Journal of Economics 107, 407–437. Meisenberg, G. & Lynn, R. (2011). Intelligence: A measure of human capital in nations. Journal of Social, Political and Economic Studies, 36(4), 421-454. Meisenberg, G. & Lynn, R. (2012). Cognitive Human Capital and Economic Growth: Defining the Causal Paths. Journal of Social, Political and Economic Studies, 37(4), 141- 179. Potrafke, N. (2012). Intelligence and corruption. Economics Letters, 114, 109-112. Ram, R. (2007). IQ and economic growth: Further augmentation of Mankiw-Romer-Weil model. Economics Letters, 94, 7-11. Reeve, C. I. (2009). Expanding the g-nexus: Further evidence regarding the relations among IQ, religiosity, and national health outcomes. Intelligence, 37, 495–505. Rindermann, H. (2007a). Intelligence, cognitive abilities, human capital, and rationality at differentlevels. PsychologischeRundschau, 58(2), 137-145. Rindermann, H. (2007b). The g-factor of international cognitive ability comparisons: The homogeneity of results in PISA, TIMSS, PIRLS and IQ-tests across nations. European Journal of Personality, 21, 667-706. Rindermann, H., Sailer, S., & Thompson, J. (2009). The impact of smart fractions, cognitive ability of politicians and average competence of peoples on social development. Talent Development & Excellence, 1, 3–25. Rushton, J. P., &Templer, D. I. (2009). National differences in intelligence, crime, income and skin color. Intelligence, 37, 341–346. Sala-i-Martin, X., Doppelhofer, G. & Miller, R.I. (2004) Determinants of long-term growth: a Bayesian averaging of classical estimates (BACE) approach. American Economic Review 94: 813-835. Templer, D. I. (2008). Correlational and factor analytic support for Rushton's differential K life history theory. Personality & Individual Differences, 45, 440–444. Weede, E. &Kämpf, S. (2002). The impact of intelligence and institutional improvements on economic growth. Kyklos, 55, 361-380. Yamaguchi, K., (2012), “HIV/AIDS in the Muslim-Majority Countries: Formula for Low Prevalence”, Bemidji State University, https://www.bemidjistate.edu/academics/departments/political-science/wp-content/uploads/sites/40/2015/05/kaoru-yamaguchi_thesis.pdf (Accessed: 26/06/2015). |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/68320 |