The Relationship Between Education and Adult Mortality in the United States
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This article examined whether education has a causal impact on health and found that it has a large and positive correlation between education and health, and that this effect is perhaps larger than has been previously estimated in the literature.Abstract:
Prior research has uncovered a large and positive correlation between education and health. This paper examines whether education has a causal impact on health. I follow synthetic cohorts using successive U.S. censuses to estimate the impact of educational attainment on mortality rates. I use compulsory education laws from 1915 to 1939 as instruments for education. The results suggest that education has a causal impact on mortality, and that this effect is perhaps larger than has been previously estimated in the literature. Copyright 2005, Wiley-Blackwell.read more
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References
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TL;DR: In this article, the authors present a survey of the use of truncated distributions in the context of unions and wages, and some results on truncated distribution Bibliography Index and references therein.
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Instrumental variables regression with weak instruments
TL;DR: In this paper, the authors developed asymptotic distribution theory for instrumental variable regression when the partial correlation between the instruments and a single included endogenous variable is weak, here modeled as local to zero.
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On the Concept of Health Capital and the Demand for Health
TL;DR: A model of the demand for the commodity "good health" is constructed and it is shown that the shadow price rises with age if the rate of depreciation on the stock of health rises over the life cycle and falls with education if more educated people are more efficient producers of health.
Journal ArticleDOI
Problems with Instrumental Variables Estimation when the Correlation between the Instruments and the Endogenous Explanatory Variable is Weak
TL;DR: In this article, the use of instruments that explain little of the variation in the endogenous explanatory variables can lead to large inconsistencies in the IV estimates even if only a weak relationship exists between the instruments and the error in the structural equation.
Journal ArticleDOI
Identification of Causal Effects Using Instrumental Variables
TL;DR: It is shown that the instrumental variables (IV) estimand can be embedded within the Rubin Causal Model (RCM) and that under some simple and easily interpretable assumptions, the IV estimand is the average causal effect for a subgroup of units, the compliers.