TY  - JOUR
AU  - Haan,Wouter J. Den
AU  - Levin,Andrew T.
TI  - A Practitioner's Guide to Robust Covariance Matrix Estimation
JF  - National Bureau of Economic Research Technical Working Paper Series
VL  - No. 197
PY  - 1996
Y2  - June 1996
UR  - http://www.nber.org/papers/t0197
L1  - http://www.nber.org/papers/t0197.pdf
N1  - Author contact info:
Andrew T.. Levin
Federal Reserve Board
Mail Stop 77
20th and C Street, NW
Washington, DC   20551
Tel: 202-452-3541
Fax: 202-452-2301
E-Mail: andrew.levin@frb.gov
AB  - 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.
ER  -