Small Sample Properties of Generalized Method of Moments Based Wald Tests

Craig Burnside and Martin Eichenbaum

No 155, NBER Technical Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: C12 C5 (search for similar items in EconPapers)
Date: 1994-05
Note: EFG
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Citations: View citations in EconPapers (14)

Published as Burnside, Craig and Martin Eichenbaum. "Small-Sample Properties Of GMM-Based Wald Tests," Journal of Business and Economic Statistics, 1996, v14(3,Jul), 294-308.

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Working Paper: Small sample properties of generalized method of moments based Wald tests (1994)
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