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Using Samples of Unequal Length in Generalized Method of Moments Estimation

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Author Info
Anthony W. Lynch
Jessica A. Wachter

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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. These methods are extended to more general patterns of missing data, and are shown to be more efficient than estimators that ignore intervals of the data, and thus more efficient than standard GMM.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 14411.

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Date of creation: Oct 2008
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Handle: RePEc:nbr:nberwo:14411

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C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing

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  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. [Downloadable!] (restricted)
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