Causal inference with observational data

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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Year of publication:	2007
Authors:	Nichols, Austin
Published in:	Stata Journal. - StataCorp LP. - Vol. 7.2007, 4, p. 507-541
Publisher:	StataCorp LP
Subject:	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

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Extent:	text/html
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005583292