A Robust Test for Weak Instruments

Datos Bibliográficos

ID19419085
AutoresJosé Luis Montiel Olea (0000-0002-1037-1628, Harvard University), Carolin Pflueger (0000-0002-3666-3178, University of British Columbia)
Año2013
Volumen31
Número3
Páginas358-369
Fecha de publicación2013-07-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaJournal of Business and Economic Statistics (JOURNAL)
Identificadores de la revistaISSN: 0735-0015 • E-ISSN: 1537-2707
EditorialInforma UK Limited (PUBLISHER • GB)
DOI10.1080/00401706.2013.806694
OpenAlexW2147146578
IdiomaEN
Citas recibidas191
Referencias citadas36

We develop a test for weak instruments in linear instrumental variables regression that is robust to heteroscedasticity, autocorrelation, and clustering. Our test statistic is a scaled nonrobust first-stage F statistic. Instruments are considered weak when the two-stage least squares or the limited information maximum likelihood Nagar bias is large relative to a benchmark. We apply our procedures to the estimation of the elasticity of intertemporal substitution, where our test cannot reject the null of weak instruments in a larger number of countries than the test proposed by Stock and Yogo in 2005 Stock, J. and Yogo, M. 2005. “Testing for Weak Instruments In Linear IV Regression,”. In Identification and Inference for Econometric Models: Essays in Honor of Thomas Rothenberg, Edited by: W, D., Andrews, ., J, and, H, . and Stock, . 80–108. Cambridge: Cambridge University Press. [Crossref] , [Google Scholar]. Supplementary materials for this article are available online

Autocorrelation · Econometrics · Economics · Geography · Heteroscedasticity · Inference · Instrumental variable · Ordinary least squares · Statistical hypothesis testing · Statistics · Test statistic · Complex Systems and Time Series Analysis · Computer Science · Financial Markets and Investment Strategies · Mathematics · Monetary Policy and Economic Impact · Artificial Intelligence