Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables
Autor(a) principal: | |
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Data de Publicação: | 2003 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/8395 |
Resumo: | It is now widely recognized that the most commonly used efficient two-step GMM estimator may have large bias in small samples. This problem has motivated the search for alternative estimators with better finite sample properties. Two classes of alternatives are considered in this paper. The first includes estimators which are asymptotically first-order equivalent to the GMM estimator, namely the continuous-updating, exponential tilting, and empirical likelihood estimators. Analytical and bootstrap bias-adjusted GMM estimators form the second class of alternatives. Two extensive Monte Carlo simulation studies are conducted in this paper for covariance structure and instrumental variable models. We conclude that all alternative estimators offer much reduced bias as compared to the GMM estimator, particularly the empirical likelihood and some of the bias-corrected GMM estimators analyzed. |
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Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental VariablesGMMContinuous UpdatingEmpirical LikelihoodExponential TiltingAnalytical and Bootstrap Bias-Adjusted EstimatorsCovariance Structure ModelsInstrumental VariablesMonte Carlo SimulationIt is now widely recognized that the most commonly used efficient two-step GMM estimator may have large bias in small samples. This problem has motivated the search for alternative estimators with better finite sample properties. Two classes of alternatives are considered in this paper. The first includes estimators which are asymptotically first-order equivalent to the GMM estimator, namely the continuous-updating, exponential tilting, and empirical likelihood estimators. Analytical and bootstrap bias-adjusted GMM estimators form the second class of alternatives. Two extensive Monte Carlo simulation studies are conducted in this paper for covariance structure and instrumental variable models. We conclude that all alternative estimators offer much reduced bias as compared to the GMM estimator, particularly the empirical likelihood and some of the bias-corrected GMM estimators analyzed.2013-04-03T11:28:50Z2013-04-032003-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/8395http://hdl.handle.net/10174/8395engRamalho, J.J.S. (2003), Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables, Documento de Trabalho nº 2003/09, Universidade de Évora, Departamento de Economia.34jsr@uevora.ptC13, C149_2003Department of Economics, University of ÉvoraRamalho, Joaquiminfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T18:49:19Zoai:dspace.uevora.pt:10174/8395Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:02:39.499414Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables |
title |
Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables |
spellingShingle |
Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables Ramalho, Joaquim GMM Continuous Updating Empirical Likelihood Exponential Tilting Analytical and Bootstrap Bias-Adjusted Estimators Covariance Structure Models Instrumental Variables Monte Carlo Simulation |
title_short |
Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables |
title_full |
Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables |
title_fullStr |
Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables |
title_full_unstemmed |
Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables |
title_sort |
Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables |
author |
Ramalho, Joaquim |
author_facet |
Ramalho, Joaquim |
author_role |
author |
dc.contributor.author.fl_str_mv |
Ramalho, Joaquim |
dc.subject.por.fl_str_mv |
GMM Continuous Updating Empirical Likelihood Exponential Tilting Analytical and Bootstrap Bias-Adjusted Estimators Covariance Structure Models Instrumental Variables Monte Carlo Simulation |
topic |
GMM Continuous Updating Empirical Likelihood Exponential Tilting Analytical and Bootstrap Bias-Adjusted Estimators Covariance Structure Models Instrumental Variables Monte Carlo Simulation |
description |
It is now widely recognized that the most commonly used efficient two-step GMM estimator may have large bias in small samples. This problem has motivated the search for alternative estimators with better finite sample properties. Two classes of alternatives are considered in this paper. The first includes estimators which are asymptotically first-order equivalent to the GMM estimator, namely the continuous-updating, exponential tilting, and empirical likelihood estimators. Analytical and bootstrap bias-adjusted GMM estimators form the second class of alternatives. Two extensive Monte Carlo simulation studies are conducted in this paper for covariance structure and instrumental variable models. We conclude that all alternative estimators offer much reduced bias as compared to the GMM estimator, particularly the empirical likelihood and some of the bias-corrected GMM estimators analyzed. |
publishDate |
2003 |
dc.date.none.fl_str_mv |
2003-01-01T00:00:00Z 2013-04-03T11:28:50Z 2013-04-03 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/8395 http://hdl.handle.net/10174/8395 |
url |
http://hdl.handle.net/10174/8395 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Ramalho, J.J.S. (2003), Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables, Documento de Trabalho nº 2003/09, Universidade de Évora, Departamento de Economia. 34 jsr@uevora.pt C13, C14 9_2003 Department of Economics, University of Évora |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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