Small Sample Properties of Generalized Method of Moments Based Wald Tests / Craig Burnside, Martin Eichenbaum.

Format:

Book

Author/Creator:

Burnside, Craig.

Contributor:

National Bureau of Economic Research.

Eichenbaum, Martin.

Series:

Technical Working Paper Series (National Bureau of Economic Research) no. t0155.

NBER technical working paper series no. t0155

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 1994.

Summary:

This paper assesses the small sample properties of Generalized Method of Moments (GMM) based Wald statistics. The analysis is conducted assuming that the data generating process corresponds to (i) a simple vector white noise process and (ii) an equilibrium business cycle model. Our key findings are that the small sample size of the Wald tests exceeds their asymptotic size, and that their size increases uniformly with the dimensionality of joint hypotheses. For tests involving even moderate numbers of moment restrictions, the small sample size of the tests greatly exceeds their asymptotic size. Relying on asymptotic distribution theory leads one to reject joint hypothesis tests far too often. We argue that the source of the problem is the difficulty of estimating the spectral density matrix of the GMM residuals, which is needed to conduct inference in a GMM environment. Imposing restrictions implied by the underlying economic model being investigated or the null hypothesis being tested on this spectral density matrix can lead to substantial improvements in the small sample properties of the Wald tests.

Notes:

Print version record

May 1994.