Causal effect estimation and inference using Stata
Joseph V. Terza
Department of Economics
Indiana University–Purdue University Indianapolis
Indianapolis, IN
[email protected]
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Abstract. Terza (2016b, Health Services Research 51: 1109–1113) gives the
correct generic expression for the asymptotic standard errors of statistics
formed as sample means of nonlinear data transformations. In this article, I
assess the performance of the Stata margins command as a relatively
simple alternative for calculating such standard errors. I note that
margins is not available for all packaged nonlinear regression commands
in Stata and cannot be implemented in conjunction with user-defined-and-coded
nonlinear estimation protocols that do not make a predict command
available. When margins is available, however, I establish (using a
real-data example) that it produces standard errors that are asymptotically
equivalent to those obtained from the formulations in Terza (2016b) and the
appendix available with this article. This result favors using margins
(with its relative coding simplicity) when available. In all other cases, use
Mata to code the standard-error formulations in Terza (2016b). I discuss
examples, and I give corresponding Stata do-files in appendices.
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Joseph V. Terza
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margins, causal effect estimation, causal inference
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