Nearly collinear robust procedures for 2SLS estimation

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.

Publication Details

Journal
AgEcon Search (University of Minnesota, USA)
Published
2025-01-01
DOI
https://doi.org/10.22004/ag.econ.361265
Primary Topic
Monetary Policy and Economic Impact
Type
article
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article

Nearly collinear robust procedures for 2SLS estimation

AgEcon Search (University of Minnesota, USA)
Monetary Policy and Economic Impact
article

Nearly collinear robust procedures for 2SLS estimation

article en

Abstract

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.

AgEcon Search (University of Minnesota, USA)
Openalex Percentile: Top 44%
Monetary Policy and Economic Impact
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Nearly collinear robust procedures for 2SLS estimation · AgEcon Search (University of Minnesota, USA) (2025) | TGRS Research Map | TGRS