NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

A Practitioner's Guide to Robust Covariance Matrix Estimation

Wouter J. Den Haan, Andrew T. Levin

NBER Technical Working Paper No. 197
Issued in June 1996
NBER Program(s):   EFG

This paper develops asymptotic distribution theory for generalized method of moments (GMM) estimators and test statistics when some of the parameters are well identified, but others are poorly identified because of weak instruments. The asymptotic theory entails applying empirical process theory to obtain a limiting representation of the (concentrated) objective function as a stochastic process. The general results are specialized to two leading cases, linear instrumental variables regression and GMM estimation of Euler equations obtained from the consumption-based capital asset pricing model with power utility. Numerical results of the latter model confirm that finite sample distributions can deviate substantially from normality, and indicate that these deviations are captured by the weak instruments asymptotic approximations.

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Document Object Identifier (DOI): 10.3386/t0197

Published: Handbook of Statistics 15. edited by G.S. Maddala and C.R. Rao, 1997

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