TY  - JOUR
AU  - Stowasser, Till
AU  - Heiss, Florian
AU  - McFadden, Daniel
AU  - Winter, Joachim
TI  - "Healthy, Wealthy and Wise?" Revisited: An Analysis of the Causal Pathways from Socio-economic Status to Health
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 17273
PY  - 2011
Y2  - August 2011
DO  - 10.3386/w17273
UR  - http://www.nber.org/papers/w17273
L1  - http://www.nber.org/papers/w17273.pdf
N1  - Author contact info:
Till Stowasser
University of Wuerzburg
Department of Economics 7
Stephanstr. 1
D-97070 Wuerzburg
Germany
E-Mail: till.stowasser@uni-wuerzburg.de

Florian Heiss
University of Duesseldorf
LS Statistics and Econometrics
Universitaetsstrasse 1, Geb. 24.31
40225  Düsseldorf
Germany
E-Mail: florian.heiss@hhu.de

Daniel L. McFadden
University of California, Berkeley
Department of Economics
508-1 Evans Hall #3880
Berkeley, CA 94720-3880
Tel: (510) 643-8428
Fax: (510) 642-0638
E-Mail: mcfadden@econ.berkeley.edu

Joachim Winter
Department of Economics
LMU Munich
Ludwigstr. 33
D-80539 Munich
Germany
E-Mail: joachim.winter@lrz.uni-muenchen.de
M1  - published as Till Stowasser, Florian Heiss, Daniel McFadden, Joachim Winter. ""Healthy, Wealthy and Wise?" Revisited: An Analysis of the Causal Pathways from Socioeconomic Status to Health," in David A. Wise, editor, "Investigations in the Economics of Aging" University of Chicago Press (2012)

M3  - presented at "Aging Conference", May 6-7, 2011
AB  - Much has been said about the stylized fact that the economically successful are not only wealthier but also healthier than the less affluent. There is little doubt about the existence of this socio-economic gradient in health, but there remains a vivid debate about its source. In this paper, we review the methodological challenges involved in testing the causal relationships between socio-economic status and health. We describe the approach of testing for the absence of causal channels developed by Adams et al. (2003) that seeks identification without the need to isolate exogenous variation in economic variables, and we repeat their analysis using the full range of data that have become available in the Health and Retirement Study since, both in terms of observations years and age ranges covered. This analysis shows that causal inference critically depends on which time periods are used for estimation. Using the information of longer panels has the greatest effect on results. We find that SES causality cannot be ruled out for a larger number of health conditions than in the original study. An approach based on a reduced-form interpretation of causality thus is not very informative, at least as long as the confounding influence of hidden common factors is not fully controlled.
ER  -