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- Editorial Material] Invited Commentary: Using Financial Credits as Instrumental Variables for Estimating the Causal Relationship Between Income and Health
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DocNo of ILP : 11782
Document Type : Editorial Material
Document Title : Invited Commentary: Using Financial Credits as Instrumental Variables for Estimating the Causal Relationship Between Income and Health
Authors : Pega, F
Author Full Name : Pega, Frank
Author Keywords : causal inference; financial credits; health outcomes; income; instrumental variable analysis; tax credits
Keywords Plus? : TAX CREDIT; LOTTERY PRIZES; CASH; MACKENBACH; TRANSFERS; PROGRAMS; BENEFITS; POLITICS; OUTCOMES; TRENDS
Abstract : Social epidemiologists are interested in determining the causal relationship between income and health. Natural experiments in which individuals or groups receive income randomly or quasi-randomly from financial credits (e.g., tax credits or cash transfers) are increasingly being analyzed using instrumental variable analysis. For example, in this issue of the Journal, Hamad and Rehkopf (Am J Epidemiol. 2016;183(9):775-784) used an in-work tax credit called the Earned Income Tax Credit as an instrument to estimate the association between income and child development. However, under certain conditions, the use of financial credits as instruments could violate 2 key instrumental variable analytic assumptions. First, some financial credits may directly influence health, for example, through increasing a psychological sense of welfare security. Second, financial credits and health may have several unmeasured common causes, such as politics, other social policies, and the motivation to maximize the credit. If epidemiologists pursue such instrumental variable analyses, using the amount of an unconditional, universal credit that an individual or group has received as the instrument may produce the most conceptually convincing and generalizable evidence. However, other natural income experiments (e.g., lottery winnings) and other methods that allow better adjustment for confounding might be more promising approaches for estimating the causal relationship between income and health.
Web of Science Categories : Public, Environmental & Occupational Health
Year Published : 2016
Publisher : OXFORD UNIV PRESS INC
Publisher City : CARY
Language : English
Cited Reference Count : 42
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