A Practitioner's Guide to Robust Covariance Matrix Estimation / Wouter J. Den Haan, Andrew T. Levin.

Format:

Book

Author/Creator:

Haan, Wouter J. Den.

Contributor:

National Bureau of Economic Research.

Levin, Andrew T.

Series:

Technical Working Paper Series (National Bureau of Economic Research) no. t0197.

NBER technical working paper series no. t0197

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 1996.

Summary:

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.

Notes:

Print version record

June 1996.