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Socio-economic determinants of mortality in Taiwan: Combining individual and aggregate data

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  • Leon-Gonzalez, Roberto
  • Tseng, Fu Min

Abstract

There is a very large literature that examines the relationship between health and income. Two main hypotheses have been investigated: the income inequality hypothesis and the absolute income hypothesis. Most of previous studies that used mortality data have been criticized for estimating an aggregate model that does not account for non-linear links between health and income at the individual level. In this paper we follow a novel approach to avoid this bias, combining aggregate mortality data with individual-level data on socio-economic characteristics. We test the income inequality and absolute income hypotheses using county-level mortality data from Life Statistic of Department of Health and individual-level data from Taiwan census Family Income and Expenditure Survey (FIES) for 1976-2004. We find the evidence to support the absolute income hypothesis but not income inequality hypothesis in the case of the general population. We also find strong evidence that education does have significant effects on individuals' health and the estimates are not sensitive to income equivalent scales.

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Bibliographic Info

Article provided by Elsevier in its journal Health Policy.

Volume (Year): 99 (2011)
Issue (Month): 1 (January)
Pages: 23-36

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Handle: RePEc:eee:hepoli:v:99:y:2011:i:1:p:23-36

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Web page: http://www.elsevier.com/locate/healthpol

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Keywords: Mortality Relative income hypothesis Aggregation bias;

References

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  1. Angus Deaton, 2002. "Health, inequality, and economic development," Working Papers 209, Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies..
  2. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, Elsevier, vol. 30(1-2), pages 109-126.
  3. Gravelle, Hugh & Wildman, John & Sutton, Matthew, 2002. "Income, income inequality and health: what can we learn from aggregate data?," Social Science & Medicine, Elsevier, Elsevier, vol. 54(4), pages 577-589, February.
  4. Wilkinson, Richard G & Pickett, Kate E., 2006. "Income inequality and population health: A review and explanation of the evidence," Social Science & Medicine, Elsevier, Elsevier, vol. 62(7), pages 1768-1784, April.
  5. S. Illeris & G. Akehurst, 2001. "Introduction," The Service Industries Journal, Taylor & Francis Journals, vol. 21(1), pages 1-4, January.
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  7. John Wildman & Hugh Gravelle & Matthew Sutton, 2003. "Health and income inequality: attempting to avoid the aggregation problem," Applied Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 35(9), pages 999-1004.
  8. Jonathan Wakefield & Ruth Salway, 2001. "A statistical framework for ecological and aggregate studies," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(1), pages 119-137.
  9. Browning, Martin & Deaton, Angus & Irish, Margaret, 1985. "A Profitable Approach to Labor Supply and Commodity Demands over the Life-Cycle," Econometrica, Econometric Society, Econometric Society, vol. 53(3), pages 503-43, May.
  10. Martins, Pedro S. & Pereira, Pedro T., 2004. "Does education reduce wage inequality? Quantile regression evidence from 16 countries," Labour Economics, Elsevier, Elsevier, vol. 11(3), pages 355-371, June.
  11. Wildman, John, 2003. "Income related inequalities in mental health in Great Britain: analysing the causes of health inequality over time," Journal of Health Economics, Elsevier, Elsevier, vol. 22(2), pages 295-312, March.
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