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Causal inference with observational data

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  • Austin Nichols

    (Urban Institute)

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.

Suggested Citation

  • Austin Nichols, 2007. "Causal inference with observational data," Stata Journal, StataCorp LP, vol. 7(4), pages 507-541, December.
  • Handle: RePEc:tsj:stataj:v:7:y:2007:i:4:p:507-541
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    References listed on IDEAS

    as
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