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Generalized Methods of Trimmed Moments

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  • Cizek, P.

    (Tilburg University, Center for Economic Research)

Abstract

High breakdown-point regression estimators protect against large errors and data contamination. We adapt and generalize the concept of trimming used by many of these robust estimators so that it can be employed in the context of the generalized method of moments. The proposed generalized method of trimmed moments (GMTM) offers a globally robust estimation approach (contrary to existing only locally robust estimators) applicable in econometric models identified and estimated using moment conditions. We derive the consistency and asymptotic distribution of GMTM in a general setting, propose a robust test of overidentifying conditions, and demonstrate the application of GMTM in the instrumental variable regression. We also compare the finite-sample performance of GMTM and existing estimators by means of Monte Carlo simulation.

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Bibliographic Info

Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2009-25.

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Date of creation: 2009
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Handle: RePEc:dgr:kubcen:200925

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Keywords: asymptotic normality; generalized method of moments; instrumental variables regression; robust estimation; trimming;

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