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Using Samples of Unequal Length in Generalized Method of Moments Estimation

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  • Lynch, Anthony W.
  • Wachter, Jessica A.

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.

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Bibliographic Info

Article provided by Cambridge University Press in its journal Journal of Financial and Quantitative Analysis.

Volume (Year): 48 (2013)
Issue (Month): 01 (February)
Pages: 277-307

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Handle: RePEc:cup:jfinqa:v:48:y:2013:i:01:p:277-307_00

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Cited by:
  1. Jonathan Fletcher & Patricia Ntozi-Obwale, 2009. "Exploring the Conditional Performance of U.K. Unit Trusts," Journal of Financial Services Research, Springer, vol. 36(1), pages 21-44, August.
  2. Anthony W. Lynch & Oliver Randall, 2011. "Why Surplus Consumption in the Habit Model May be Less Persistent than You Think," NBER Working Papers 16950, National Bureau of Economic Research, Inc.
  3. Efstathios Avdis & Jessica A. Wachter, 2013. "Maximum likelihood estimation of the equity premium," NBER Working Papers 19684, National Bureau of Economic Research, Inc.

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