BANK TECHNICAL EFFICIENCY OF COUNTRY GROUPS: A META-REGRESSION ANALYSIS

Year 2024, , 13 - 23, 03.06.2024

Neylan Kaya

https://doi.org/10.17261/Pressacademia.2024.1898

Abstract

Purpose- This study endeavors to examine studies using Data Envelopment Analysis in calculating the banking sector efficiency across country groups and to determine the factors affecting their technical efficiency through meta-regression analysis.
Methodology- As of November 22, 2023, relevant works were systematically reviewed using Web of Science, Scopus, and Google Scholar. The literature review employed a comprehensive search encompassing all files with the keywords such as ‘‘technical efficiency (All Field) AND bank (All Field)’’. The research process adhered to the PRISMA guidelines. This study reviewed all studies published between 1932 and 2023 identifying 64599 studies in the initial scan by the author. The author independently scrutinized the titles, abstracts, keywords, text, and references of all manuscripts to mitigate selection bias and reveal whether eligibility criteria were met. Exclusions from the scope encompassed duplicate downloads, papers, books and book chapters, together with studies having low quality scores, no full-text versions, and those that are irrelevant to the subject.
Findings- The results of meta-regression analysis revealed that the data collection year of the studies and the income groups of the countries did not have an impact on the mean technical efficiency. The number of banks, number of observations, publication year, and number of countries were statistically significant on the mean technical efficiency estimate.
Conclusion- The study further standardized variables and methodological assumptions used in bank sector efficiency studies within country groups through meta-regression analysis. Empirical findings in the literature were combined. This study enhances accessibility to the existing body of knowledge for researchers in the field

Keywords

Banks, technical efficiency, Data Envelopment Analysis, Tobit Analysis, Meta-Regression Analysis

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