Endogeneity in panel data regressions: methodological guidance for corporate finance researchers
Originality/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...
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| Published in | Revista brasileira de gestão de negócios Vol. 22; no. SI; pp. 437 - 461 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English Portuguese |
| Published |
São Paulo
Fundacao Escola de Comercio Alvares Penteado (FECAP)
01.01.2020
Centro Universitário FECAP, mantido pela Fundação Escola de Comericio Álvares Penteado (FECAP) Fundação Escola de Comércio Álvares Penteado |
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| Abstract | Originality/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. |
|---|---|
| AbstractList | Originality/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. 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 simulation Findings - 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 model Originality/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. Abstract 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 simulation Findings: 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 model Originality/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. 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 simulation Findings--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 model Originality/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. Keywords--Corporate Finance; Econometrics; Panel Data; GMM |
| Audience | Professional |
| Author | Bergmann, Daniel Reed Barros, Lucas A.B.C da Silveira, Alexandre Di Miceli Castro, F. Henrique |
| AuthorAffiliation | Alvares Penteado School of Business Universidade de São Paulo Fundação Getúlio Vargas |
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| Keywords | Panel Data Corporate Finance GMM econometria Finanças corporativas dados em painel Econometrics |
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| Snippet | Originality/value--The paper discusses and illustrates a greater number of endogeneity problems, showing how they are addressed by different estimators for... Purpose--To describe the use of specific lags (and/or temporal differences) of the original regressors as instrumental variables in a succinct and practical... Purpose - To describe the use of specific lags (and/or temporal differences) of the original regressors as instrumental variables in a succinct and practical... Abstract Purpose: To describe the use of specific lags (and/or temporal differences) of the original regressors as instrumental variables in a succinct and... Purpose –To describe the use of specific lags (and/or temporal differences) of the original regressors as instrumental variables in a succinct and practical... |
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| SubjectTerms | Bias Corporate finance Dependent variables econometrics Generalized method of moments gmm Independent variables Longitudinal studies MANAGEMENT Measurement Monte Carlo methods Monte Carlo simulation panel data Regression analysis Simulation Variables |
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| Title | Endogeneity in panel data regressions: methodological guidance for corporate finance researchers |
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