Causal inference with observational data
Austin Nichols
Urban Institute
Washington, DC
austinnichols@gmail.com
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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.
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Austin Nichols
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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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