Endogeneity in panel data regressions: methodological guidance for corporate finance researchers
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Redalyc
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| Formato: | Artículo científico |
| Lenguaje: | en |
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Fundação Escola de Comércio Álvares Penteado
2020
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| _version_ | 1876452757799436288 |
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| author | Lucas A. B. C. Barros |
| author_facet | Lucas A. B. C. Barros |
| contents | Endogeneity in panel data regressions: methodological guidance for corporate finance researchers Lucas A. B. C. Barros Daniel Reed Bergmann F. Henrique Castro Alexandre Di Miceli da Silveira Administración y Contabilidad GMM Panel Data Econometrics Corporate Finance Purpose To describe the use of specific lags (and/or temporal differences) of the original regressors as instrumental variables in a succinct and practical way, showing, by means of a theoretical discussion illustrated by an original simulation exercise, how combining these with adequate modeling of firm and time fixed effects can address not only the dynamic endogeneity problem, but also those derived from the presence of omitted variables, measurement errors, and simultaneity between dependent and independent variables.Design/methodology/approach Monte Carlo simulationFindings The traditional OLS, RE, and FE estimators may be inconsistent in the presence of endogeneity problems that are quite plausible in the context of corporate finance. On the other hand, the estimation methods for panel data based on GMM that use assumptions of sequential exogeneity of the regressors present alternatives that are capable of effectively overcoming all the problems listed (provided these assumptions are valid) even if the researcher does not have good instrumental variables that are external to the modelOriginality/value The paper discusses and illustrates a greater number of endogeneity problems, showing how they are addressed by different estimators for panel data, using less technical and more accessible language for researchers not yet initiated in the intricacies of estimating dynamic models for panel data. 2020 artículo científico 1806-4892 https://www.redalyc.org/articulo.oa?id=94768442003 https://www.redalyc.org/journal/947/94768442003/ https://www.redalyc.org/journal/947/94768442003/html/ https://www.redalyc.org/journal/947/94768442003/94768442003.epub https://www.redalyc.org/journal/947/94768442003/movil 10.7819/rbgn.v22i0.4059 en http://www.redalyc.org/revista.oa?id=947 Revista Brasileira de Gestão de Negócios - RBGN application/pdf Fundação Escola de Comércio Álvares Penteado Revista Brasileira de Gestão de Negócios - RBGN (Brasil) Num.1 Vol.22 |
| format | Artículo científico |
| id | redalyc_94768442003 |
| institution | Redalyc |
| language | en |
| publishDate | 2020 |
| publisher | Fundação Escola de Comércio Álvares Penteado |
| spellingShingle | Endogeneity in panel data regressions: methodological guidance for corporate finance researchers Lucas A. B. C. Barros Administración y Contabilidad GMM Panel Data Econometrics Corporate Finance Endogeneity in panel data regressions: methodological guidance for corporate finance researchers Lucas A. B. C. Barros Daniel Reed Bergmann F. Henrique Castro Alexandre Di Miceli da Silveira Administración y Contabilidad GMM Panel Data Econometrics Corporate Finance Purpose To describe the use of specific lags (and/or temporal differences) of the original regressors as instrumental variables in a succinct and practical way, showing, by means of a theoretical discussion illustrated by an original simulation exercise, how combining these with adequate modeling of firm and time fixed effects can address not only the dynamic endogeneity problem, but also those derived from the presence of omitted variables, measurement errors, and simultaneity between dependent and independent variables.Design/methodology/approach Monte Carlo simulationFindings The traditional OLS, RE, and FE estimators may be inconsistent in the presence of endogeneity problems that are quite plausible in the context of corporate finance. On the other hand, the estimation methods for panel data based on GMM that use assumptions of sequential exogeneity of the regressors present alternatives that are capable of effectively overcoming all the problems listed (provided these assumptions are valid) even if the researcher does not have good instrumental variables that are external to the modelOriginality/value The paper discusses and illustrates a greater number of endogeneity problems, showing how they are addressed by different estimators for panel data, using less technical and more accessible language for researchers not yet initiated in the intricacies of estimating dynamic models for panel data. 2020 artículo científico 1806-4892 https://www.redalyc.org/articulo.oa?id=94768442003 https://www.redalyc.org/journal/947/94768442003/ https://www.redalyc.org/journal/947/94768442003/html/ https://www.redalyc.org/journal/947/94768442003/94768442003.epub https://www.redalyc.org/journal/947/94768442003/movil 10.7819/rbgn.v22i0.4059 en http://www.redalyc.org/revista.oa?id=947 Revista Brasileira de Gestão de Negócios - RBGN application/pdf Fundação Escola de Comércio Álvares Penteado Revista Brasileira de Gestão de Negócios - RBGN (Brasil) Num.1 Vol.22 |
| title | Endogeneity in panel data regressions: methodological guidance for corporate finance researchers |
| topic | Administración y Contabilidad GMM Panel Data Econometrics Corporate Finance |
| url | https://www.redalyc.org/articulo.oa?id=94768442003 https://www.redalyc.org/journal/947/94768442003/ https://www.redalyc.org/journal/947/94768442003/html/ https://www.redalyc.org/journal/947/94768442003/94768442003.epub https://www.redalyc.org/journal/947/94768442003/movil |