The Estimation of Causal Effects from Observational Data

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The Estimation of Causal Effects from Observational Data

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Title: The Estimation of Causal Effects from Observational Data
Author: Morgan, Stephen L.; Winship, Christopher

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Citation: Winship, Christopher, and Stephen L. Morgan. 1999. The estimation of causal effects from observational data. Annual Review of Sociology 25: 659-706.
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Abstract: When experimental designs are infeasible, researchers must resort to the use of observational data from surveys, censuses, and administrative records. Because assignment to the independent variables of observational data is usually nonrandom, the challenge of estimating causal effects with observational data can be formidable. In this chapter, we review the large literature produced primarily by statisticians and econometricians in the past two decades on the estimation of causal effects from observational data. We first review the now widely accepted counterfactual framework for the modeling of causal effects. After examining estimators, both old and new, that can be used to estimate causal effects from cross-sectional data, we present estimators that exploit the additional information furnished by longitudinal data. Because of the size and technical nature of the literature, we cannot offer a fully detailed and comprehensive presentation. Instead, we present only the main features of methods that are accessible and potentially of use to quantitatively oriented sociologists.
Published Version: http://dx.doi.org/10.1146/annurev.soc.25.1.659
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Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:3200609
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