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Using Samples of Unequal Length in Generalized Method of Moments Estimation

Published online by Cambridge University Press:  08 February 2013

Anthony W. Lynch  and
Jessica A. Wachter
Anthony W. Lynch
Affiliation:
alynch@stern.nyu.edu, Stern School of Business, New York University, 44 W 4th St, New York, NY 10012;
Jessica A. Wachter
Affiliation:
jwachter@wharton.upenn.edu, Wharton School, University of Pennsylvania, 3620 Locust Walk, Philadelphia, PA 19104.
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Abstract

This paper describes estimation methods, based on the generalized method of moments (GMM), applicable in settings where time series have different starting or ending dates. We introduce two estimators that are more efficient asymptotically than standard GMM. We apply these to estimating predictive regressions in international data and show that the use of the full sample affects inference for assets with data available over the full period as well as for 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.

Type
Research Articles
Information
Journal of Financial and Quantitative Analysis , Volume 48 , Issue 1 , February 2013 , pp. 277 - 307
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2013 

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