Using Samples of Unequal Length in Generalized Method of Moments Estimation

47 Pages Posted: 9 Mar 2009 Last revised: 13 Dec 2011

See all articles by Anthony W. Lynch

Anthony W. Lynch

New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER)

Jessica A. Wachter

University of Pennsylvania - Finance Department; National Bureau of Economic Research (NBER)

Multiple version iconThere are 3 versions of this paper

Date Written: June 27, 2011

Abstract

Many applications in financial economics use data series with different starting or ending dates. This paper describes estimation methods, based on the generalized method of moments (GMM), which make use of all available data for each moment condition. We introduce two asymptotically equivalent estimators that are consistent, a symptotically normal, and more efficient asymptotically than standard GMM. We apply these methods to estimating predictive regressions in international data and show that the use of the full sample affects point estimates and standard errors for both assets with data available for the full period and assets with data available for a subset of the period. Monte Carlo experiments demonstrate that reductions hold for small-sample standard errors as well as asymptotic ones.

Suggested Citation

Lynch, Anthony W. and Wachter, Jessica A., Using Samples of Unequal Length in Generalized Method of Moments Estimation (June 27, 2011). NYU Working Paper No. FIN-08-018, Available at SSRN: https://ssrn.com/abstract=1354506

Anthony W. Lynch (Contact Author)

New York University (NYU) - Department of Finance ( email )

Stern School of Business
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National Bureau of Economic Research (NBER) ( email )

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Jessica A. Wachter

University of Pennsylvania - Finance Department ( email )

The Wharton School
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National Bureau of Economic Research (NBER)

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United States

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