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Causal inference with observational data

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Author Info
Austin Nichols () (Urban Institute)

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Abstract

Problems with inferring causal relationships from nonexperimental data are briefly reviewed, and four broad classes of methods designed to allow estimation of and inference about causal parameters are described: panel regression, matching or reweighting, instrumental variables, and regression discontinuity. Practical examples are offered, and discussion focuses on checking required assumptions to the extent possible. Copyright 2007 by StataCorp LP.

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Publisher Info
Article provided by StataCorp LP in its journal Stata Journal.

Volume (Year): 7 (2007)
Issue (Month): 4 (December)
Pages: 507-541
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Handle: RePEc:tsj:stataj:v:7:y:2007:i:4:p:507-541

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Related research
Keywords: xtreg; psmatch2; nnmatch; ivreg; ivreg2; ivregress; rd; lpoly; xtoverid; ranktest; causal inference; match; matching; reweighting; propensity score; panel; instrumental variables; excluded instrument; weak identification; regression; discontinuity; local polynomial;

Cited by:
(explanations, 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.)

  1. Owen, Ann L., 2008. "Grades, gender, and encouragement: A regression discontinuity analysis," MPRA Paper 11586, University Library of Munich, Germany. [Downloadable!]
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This page was last updated on 2009-11-22.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.