EconPapers    
Economics at your fingertips  
 

Two-stage least squares as minimum distance

Frank Windmeijer ()

Econometrics Journal, 2019, vol. 22, issue 1, 1-9

Abstract: SummaryThe two-stage least-squares (2SLS) instrumental-variables (IV) estimator for the parameters in linear models with a single endogenous variable is shown to be identical to an optimal minimum-distance (MD) estimator based on the individual instrument-specific IV estimators. The 2SLS estimator is a linear combination of the individual estimators, with the weights determined by their variances and covariances under conditional homoskedasticity. It is further shown that the Sargan test statistic for overidentifying restrictions is the same as the MD criterion test statistic. This provides an intuitive interpretation of the Sargan test. The equivalence results also apply to the efficient two-step generalized method of moments and robust optimal MD estimators and criterion functions, allowing for general forms of heteroskedasticity. It is further shown how these results extend to the linear overidentified IV model with multiple endogenous variables.

Keywords: Instrumental variables; Minimum distance; Overidentification test; Two-stage least squares (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1111/ectj.12115 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Two-Stage Least Squares as Minimum Distance (2018) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:emjrnl:v:22:y:2019:i:1:p:1-9.

Access Statistics for this article

Econometrics Journal is currently edited by Jaap Abbring, Victor Chernozhukov, Michael Jansson and Dennis Kristensen

More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().

 
Page updated 2019-08-21
Handle: RePEc:oup:emjrnl:v:22:y:2019:i:1:p:1-9.