Methodological strategies for panel data: The case of typical banks in Argentina: the case of typical banks in Argentina

In this work we analyze the determinants of bank profitability in the case of Argentinian Typical banks through the period 2005-2018. Profitability is measured as return on assets (ROA) and the bank-specific determinants considered are Capital (Equity/Assets), Credit risk (Loan loss provisions/loans...

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Autores principales: Díaz, Margarita, Vargas, José M., Girela, Ignacio
Formato: Artículo publishedVersion
Lenguaje:Español
Publicado: CIMBAGE - IADCOM - Facultad de Ciencias Económicas - Universidad de Buenos Aires 2020
Materias:
Datos de Panel
Rentabilidad Bancaria
Determinantes de la rentabilidad
Panel Data
Bank-Profitability
Determinants of profitability
Acceso en línea:https://ojs.economicas.uba.ar/CIMBAGE/article/view/1950
https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=cimbage&d=1950_oai
Aporte de:
Repositorio Digital de la Universidad de Buenos Aires (UBA) de Universidad de Buenos Aires
id I28-R145-1950_oai
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institution Universidad de Buenos Aires
institution_str I-28
repository_str R-145
collection Repositorio Digital de la Universidad de Buenos Aires (UBA)
language Español
orig_language_str_mv spa
topic Datos de Panel
Rentabilidad Bancaria
Determinantes de la rentabilidad
Panel Data
Bank-Profitability
Determinants of profitability
spellingShingle Datos de Panel
Rentabilidad Bancaria
Determinantes de la rentabilidad
Panel Data
Bank-Profitability
Determinants of profitability
Díaz, Margarita
Vargas, José M.
Girela, Ignacio
Methodological strategies for panel data: The case of typical banks in Argentina: the case of typical banks in Argentina
topic_facet Datos de Panel
Rentabilidad Bancaria
Determinantes de la rentabilidad
Panel Data
Bank-Profitability
Determinants of profitability
description In this work we analyze the determinants of bank profitability in the case of Argentinian Typical banks through the period 2005-2018. Profitability is measured as return on assets (ROA) and the bank-specific determinants considered are Capital (Equity/Assets), Credit risk (Loan loss provisions/loans), Productivity (Gross total revenue/personnel), Operating expenses (Operating expenses/assets) and Size (logarithm of assets). Additionally, derived from the Herfindhal-Hirschman concentration index, the share of each bank of the system-total was considered as an industry-specific variable. As a first step a linear model was estimated by Ordinary Least Squares (OLS) allowing the early detection of outliers. In a second step, methods that take account of the hierarchical structure of the information were considered, such as Random Effects Model (RE) and Fixed Effects Model (FE), both with robust standard errors estimation and standard errors with the Driscoll and Kraay correction. In order to select the appropriate model, Hausman test of specific effects and tests to inquire into cross-sectional correlation were performed. Results indicate that a fixed Effects model with the Driscoll and Kraay correction of variances is the most appropriate model. The ratios that significantly and positively affect bank profitability are Capital, Productivity, Size and Herfindahl concentration; and negatively affecting Credit risk.
format Artículo
publishedVersion
author Díaz, Margarita
Vargas, José M.
Girela, Ignacio
author_facet Díaz, Margarita
Vargas, José M.
Girela, Ignacio
author_sort Díaz, Margarita
title Methodological strategies for panel data: The case of typical banks in Argentina: the case of typical banks in Argentina
title_short Methodological strategies for panel data: The case of typical banks in Argentina: the case of typical banks in Argentina
title_full Methodological strategies for panel data: The case of typical banks in Argentina: the case of typical banks in Argentina
title_fullStr Methodological strategies for panel data: The case of typical banks in Argentina: the case of typical banks in Argentina
title_full_unstemmed Methodological strategies for panel data: The case of typical banks in Argentina: the case of typical banks in Argentina
title_sort methodological strategies for panel data: the case of typical banks in argentina: the case of typical banks in argentina
publisher CIMBAGE - IADCOM - Facultad de Ciencias Económicas - Universidad de Buenos Aires
publishDate 2020
url https://ojs.economicas.uba.ar/CIMBAGE/article/view/1950
https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=cimbage&d=1950_oai
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spelling I28-R145-1950_oai2025-02-11 Díaz, Margarita Vargas, José M. Girela, Ignacio 2020-11-20 In this work we analyze the determinants of bank profitability in the case of Argentinian Typical banks through the period 2005-2018. Profitability is measured as return on assets (ROA) and the bank-specific determinants considered are Capital (Equity/Assets), Credit risk (Loan loss provisions/loans), Productivity (Gross total revenue/personnel), Operating expenses (Operating expenses/assets) and Size (logarithm of assets). Additionally, derived from the Herfindhal-Hirschman concentration index, the share of each bank of the system-total was considered as an industry-specific variable. As a first step a linear model was estimated by Ordinary Least Squares (OLS) allowing the early detection of outliers. In a second step, methods that take account of the hierarchical structure of the information were considered, such as Random Effects Model (RE) and Fixed Effects Model (FE), both with robust standard errors estimation and standard errors with the Driscoll and Kraay correction. In order to select the appropriate model, Hausman test of specific effects and tests to inquire into cross-sectional correlation were performed. Results indicate that a fixed Effects model with the Driscoll and Kraay correction of variances is the most appropriate model. The ratios that significantly and positively affect bank profitability are Capital, Productivity, Size and Herfindahl concentration; and negatively affecting Credit risk. En este trabajo se analizan el impacto de determinantes de la rentabilidad bancaria para los bancos considerados Típicos en Argentina en el período 2005-2018. La rentabilidad está medida a través del retorno sobre activo (ROA) y las variables predictoras derivadas de los estados financieros son: Capital (Patrimonio Neto/Activo), Riesgo Crediticio (Previsiones/Préstamos), Productividad (Ingresos Brutos/Dotación de Personal), Gastos de Gestión (Gastos Administrativos/Activo) y Tamaño (logaritmo del Activo). Adicionalmente se incorporó la variable externa Ándice de Concentración, derivado del Ándice de Herfindahl, que cuantifica la participación anual de cada banco en función del total del sistema. En una primera etapa se planteó un Modelo de Regresión Lineal que fue estimado utilizando Mínimos Cuadrados Ordinarios (OLS), lo que permitió detectar observaciones influyentes. En una segunda etapa se trabajó con los métodos que consideran la estructura jerárquica de la información, esto es: Modelo de Efectos Aleatorios, Modelo de Efectos Fijos con errores estándares robustos y con la corrección de Driscoll y Kraay. A fin de seleccionar el método de estimación apropiado, se realizaron las pruebas de Hausman, de efectos específicos y de correlación transversal entre bancos. Los resultados indican que un modelo de efectos fijos con la corrección de Driscoll y Kraay para las varianzas es el más apropiado para la estimación del modelo. Los ratios que afectan significativamente la rentabilidad, de manera positiva y con alto impacto son Capital, Productividad, Tamaño y el Ándice de Herfindahl, en tanto que, negativamente y en menor medida, Riesgo Crediticio. text/html application/pdf https://ojs.economicas.uba.ar/CIMBAGE/article/view/1950 spa CIMBAGE - IADCOM - Facultad de Ciencias Económicas - Universidad de Buenos Aires https://ojs.economicas.uba.ar/CIMBAGE/article/view/1950/2659 https://ojs.economicas.uba.ar/CIMBAGE/article/view/1950/2738 Derechos de autor 2020 Universidad de Buenos Aires Cuadernos del CIMBAGE; Vol. 2 No. 22 (2020): Cuadernos del CIMBAGE N°22 (December 2020); 51-67 Cuadernos del CIMBAGE; Vol. 2 Núm. 22 (2020): Cuadernos del CIMBAGE N°22 (Diciembre 2020); 51-67 1669-1830 1666-5112 Datos de Panel Rentabilidad Bancaria Determinantes de la rentabilidad Panel Data Bank-Profitability Determinants of profitability Methodological strategies for panel data: The case of typical banks in Argentina: the case of typical banks in Argentina Estrategias metodológicas para datos de panel. El caso de los bancos típicos en Argentina: El caso de los bancos típicos en Argentina info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=cimbage&d=1950_oai

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