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Bootstrap bias-adjusted GMM estimators

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Author Info
Joaquim J.S. Ramalho ()

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Abstract

The ability of six alternative bootstrap methods to reduce the bias of GMM parameter estimates is examined in an instrumental variable framework using Monte Carlo analysis. Promising results were found for the two bootstrap estimators suggested in the paper.

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File URL: http://www.decon.uevora.pt/working_papers.php?id=147
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Publisher Info
Paper provided by University of Évora, Department of Economics (Portugal) in its series Economics Working Papers with number 10_2005.

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Length: 9 pages
Date of creation: 2005
Date of revision:
Handle: RePEc:evo:wpecon:10_2005

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Related research
Keywords: GMM; Bootstrap; Empirical Likelihood; Instrumental Variables; Monte Carlo;

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods

Cited by:
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  1. Jason Allen & Allan W. Gregory & Katsumi Shimotsu, 2008. "Empirical Likelihood Block Bootstrapping," Working Papers 08-18, Bank of Canada. [Downloadable!]
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This page was last updated on 2009-11-22.

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