共线性
估计
工具变量
计量经济学
统计
计算
计算机科学
内生性
最小二乘函数近似
数学
算法
经济
估计员
管理
标识
DOI:10.1177/1536867x241233668
摘要
Stata’s two-stage least-squares (2SLS) computation procedures are sensitive to near collinearity among regressors, allowing situations in which reported results depend upon factors as irrelevant as the order of the data and variables. This article illustrates this claim with the public-use data of Oreopoulos (2006, American Economic Review 96: 152–175), where the instrumented coefficient estimate can be made to vary between 0.012 and 30.0 in one specification by permuting the order of the variables. Different methods for improving the accuracy of 2SLS estimates are reviewed, and a Stata command for collinearity-robust 2SLS estimation is provided.
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