Socio-economic determinants of mortality in Taiwan: Combining individual and aggregate data
AbstractThere 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Health Policy.
Volume (Year): 99 (2011)
Issue (Month): 1 (January)
Contact details of provider:
Web page: http://www.elsevier.com/locate/healthpol
Mortality Relative income hypothesis Aggregation bias;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Angus Deaton, 2002.
"Health, inequality, and economic development,"
209, Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies..
- Angus Deaton, 2001. "Health, Inequality, and Economic Development," NBER Working Papers 8318, National Bureau of Economic Research, Inc.
- Angus Deaton, 2002. "Health, inequality, and economic development," Working Papers 270, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing..
- Deaton, A., 2001. "Health, Inequality, and Economic Development," Papers, Princeton, Woodrow Wilson School - Development Studies 200, Princeton, Woodrow Wilson School - Development Studies.
- Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, Elsevier, vol. 30(1-2), pages 109-126.
- 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.
- Hugh Gravelle & John Wildman & Matthew Sutton, . "Income, Income Inequality and Health: What can we Learn from Aggregate Data?," Discussion Papers, Department of Economics, University of York 00/26, Department of Economics, University of York.
- 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.
- S. Illeris & G. Akehurst, 2001. "Introduction," The Service Industries Journal, Taylor & Francis Journals, vol. 21(1), pages 1-4, January.
- Hausman, Jerry A & Taylor, William E, 1981.
"Panel Data and Unobservable Individual Effects,"
Econometrica, Econometric Society,
Econometric Society, vol. 49(6), pages 1377-98, November.
- 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.
- 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.
- 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.
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei) or () The email address of this maintainer does not seem to be valid anymore. Please ask to update the entry or send us the correct address.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.