Causal effect estimation and inference using Stata

被引:2
|
作者
Terza, Joseph V. [1 ]
机构
[1] Indiana Univ Purdue Univ, Dept Econ, Indianapolis, IN 46202 USA
来源
STATA JOURNAL | 2017年 / 17卷 / 04期
关键词
st0506; margins; causal effect estimation; causal inference; STANDARD ERRORS; MODELS;
D O I
10.1177/1536867X1701700410
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
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.
引用
收藏
页码:939 / 961
页数:23
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