Relación de largo plazo entre competencia bancaria y crecimiento económico: un enfoque internacional clasificado por nivel de ingreso

• Tomas Gómez Rodríguez ^[1] ; Humberto Ríos Bolívar ^[2] ; Adriana Zambrano Reyes ^[1]
  1. [1] Universidad Autónoma del Estado de Hidalgo

     Universidad Autónoma del Estado de Hidalgo

     México

     
  2. [2] Instituto Politécnico Nacional

     Instituto Politécnico Nacional

     México

     
• Localización: Contaduría y administración, ISSN 0186-1042, ISSN-e 2448-8410, Vol. 67, Nº. 3, 2022
• Idioma: español
• Títulos paralelos:
  • Long-run relationship between bank competition and economic growth: An international approach classified by income level
• Enlaces
  • Texto completo (pdf)
• Resumen
  • español

    La competencia en el sector bancario podría jugar un papel crítico en el crecimiento económico de los países a largo plazo. Por tanto, para analizar esta relación se utilizan tres medidas diferentes de competencia: el índice de Lerner, el índice de Boone y el índice de concentración. Como variable dependiente se utilizó el Producto Interno Bruto per cápita por paridad de poder de compra. Para cada variable se utilizan tres muestras las cuales se clasifican en ingreso: alto, medio y bajo; siguiendo el trabajo de Dayé, Housa y Reding (2016). Para la estimación se emplearon los métodos de: Mínimos Cuadrados Ordinarios Completamente Modificados y el método de Mínimos Cuadrados Ordinarios Dinámicos. Los resultados indican que las muestras de alto ingreso y bajo ingreso para la variable índice de concentración bancario, así como la muestra de ingresos bajos para la variable índice de Boone muestran evidencia que apoya el enfoque de poder de mercado.

  • English

    Competition in the banking sector could play a critical role in the long-term economic growth of countries.

    Therefore, three different measures of competition are used to analyze this relationship: the Lerner index, the Boone index and the concentration index. Gross Domestic Product per capita by purchasing power parity was used as the dependent variable. For each variable, three samples are utilized which are classified into high, middle and low income; following the work of Dayé, Housa and Reding (2016). For the estimation, the following methods were used: Fully Modified Ordinary Least Squares and the Dynamic Ordinary Least Squares method. The results indicate that the high-income and low-income samples for the bank concentration index variable, as well as the low-income sample for the Boone index variable show evidence supporting the market power approach

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