Using Samples of Unequal Length in Generalized Method of Moments Estimation

Anthony W. Lynch and Jessica Wachter ()

No 14411, NBER Working Papers from National Bureau of Economic Research, Inc

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, asymptotically 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.

JEL-codes: C32 G12 (search for similar items in EconPapers)
Date: 2008-10
New Economics Papers: this item is included in nep-ecm and nep-ets
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Published as Lynch, Anthony W. & Wachter, Jessica A., 2013. "Using Samples of Unequal Length in Generalized Method of Moments Estimation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(01), pages 277-307, February.

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Journal Article: Using Samples of Unequal Length in Generalized Method of Moments Estimation (2013)
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