Estimating the efficiency from Brazilian banks: a bootstrapped Data Envelopment Analysis (DEA)
Périco, Ana Elisa; Santana, Naja Brandão; Rebelatto, Daisy Aparecida do N.
http://dx.doi.org/10.1590/0103-6513.185714
Production, vol.26, n3, p.551-561, 2016
Abstract
The Brazilian banking sector went through several changes in its structure over the past few years. Such changes are related to fusions and acquisitions, as well as the largest market opening to foreign banks. The objective of this paper is to analyze, by applying the bootstrap DEA, the efficiency of banks in Brazil in 2010-2013. The methodology was applied to 30 largest banking organizations in a financial intermediation approach. In that model, the resources entering a bank in the form of deposits and total assets are classified as inputs and besides these manual labor is also considered as a resource capable of generating results. For the output variable, credit operations represent the most appropriate alternative, considering the role of the bank as a financial intermediary. In this work, the matter of the best classification among retail banks and banks specialized in credit has little relevance. The low relevance in this type of comparison is a result of analysis by segments (segments were analyzed separately). The results presented here point to an average level of efficiency for the large Brazilian banks in the period. This scenario requires efforts to reduce expenses but also to increase revenues.
Keywords
Bank efficiency, Data Envelopment Analysis (DEA), Financial intermediation, Bootstrap
References
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Fukuyama, H., & Matousek, R. (2011). Efficiency of Turkish banking: two-stage network system. Variable returns to scale model. Journal of International Financial Markets, Institutions and Money, 21(1), 75-91. http://dx.doi.org/10.1016/j.intfin.2010.08.004.
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Mandl, C. (2012, September 3). Com juros em queda, bancos perseguem ganhos de eficiência. Valor Econômico: Caderno de Finanças. Retrieved in 23 October 2013, from http://www.valor.com.br/financas/2814064/com-juros-em-queda-bancos-perseguem-ganhos-de-eficiencia/#comments
Paradi, C. P., Rouatt, S., & Zhu, H. (2011). Two-stage evaluation of bank branch efficiency using Data Envelopment Analysis. Omega, 39(1), 99-109. http://dx.doi.org/10.1016/j.omega.2010.04.002.
Pastor, J. T., Lovell, C. A. K., & Tulkens, H. (2006). Evaluating the financial performance of bank branches. Annals of Operations Research, Louvain-la-Neuve, 145(1), 321-337. http://dx.doi.org/10.1007/s10479-006-0038-3.
Périco, A. E., Rebelatto, D. A. N., & Santana, N. B. (2008). Eficiência bancária: os maiores bancos são os mais eficientes? Uma análise por envoltória de dados. Gestão & Produção, 15(2), 421-431. http://dx.doi.org/10.1590/S0104-530X2008000200016.
Portela, M., & Thanassoulis, E. (2007). Comparative efficiency analysis of Portuguese bank branches. European Journal of Operational Research, 177(2), 1275-1288. http://dx.doi.org/10.1016/j.ejor.2006.01.007.
Sealey, C. Jr, & Lindley, J. T. (1977). Inputs, outputs and a theory of production and cost at depository financial Institutions. The Journal of Finance, 32(4), 1251-1266. http://dx.doi.org/10.1111/j.1540-6261.1977.tb03324.x.
Simar, L., & Wilson, P. (2000). A general methodology for bootstrapping in nonparametric frontier models. Journal of Applied Statistics, 27(6), 779-802. http://dx.doi.org/10.1080/02664760050081951.
Simar, L., & Wilson, P. W. (1998). Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models. Management Science, 44(1), 49-61. http://dx.doi.org/10.1287/mnsc.44.1.49.
Stavarek, D. (2005). Estimation of Factors Influencing Efficiency of Banks in New Member States before Joining the European Union. Ekonomicky Casopis, 53, 593-610.
Xue, M., & Harker, P. T. (1999). Overcoming the inherent dependency of DEA efficiency scores: a bootstrap approach (Working Paper, 99-17). The Wharton Financial Institutions Center.
Banker, R. D., & Natarajan, R. (2004). Statistical tests based on DEA efficiency scores. In W. Cooper, L. Seiford, & J. Zhu (Eds.), Handbook on data envelopment analysis (pp. 265-298). New York: Kluwer Academic Publishers.
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078-1092. http://dx.doi.org/10.1287/mnsc.30.9.1078.
Berger, A. N., & Humphrey, D. B. (1992). Measurement and efficiency issues in commercial banking. In Z. Griliches, Output measurement in the service sectors (pp. 175-212). Chicago: University of Chicago Press.
Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: international survey and directions for future research. European Journal of Operational Research, 98(2), 175-212. http://dx.doi.org/10.1016/S0377-2217(96)00342-6.
Charnes, A., Cooper, W., Lewin, A. Y., & Seiford, L. M. (1994). Data envelopment analysis: theory, methodology, and application. Boston: Kluwer Academic Publishers.
Departamento Intersindical de Estatística e Estudos Socioeconômicos – DIEESE. (2013). Um novo cenário para o setor financeiro no Brasil (Nota Técnica, 123, pp. 1-15). São Paulo: DIEESE. Retrieved in 23 October 2013, from http://www.dieese.org.br/notatecnica/2013/notaTec123CenarioSetorFinanceiro.pdf
Dong, F., & Featherstone, A. (2004). Technical and scale efficiencies for Chinese rural credit cooperatives: a bootstrapping approach in data envelopment analysis (Working Paper, 04 WP-366). Iowa: Center for Agricultural and Rural Development. 26 p. Retrieved in 23 October 2013, from http://www.researchgate.net/publication/24085100_Technical_and_Scale_Efficiencies_for_Chinese_Rural_Credit_Cooperatives_A_Bootstrapping_Approach_in_Data_Envelopment_Analysis
Drake, L., & Hall, M. J. B. (2003). Efficiency in Japanese banking: an empirical analysis. Journal of Banking & Finance, 27(5), 891-917. http://dx.doi.org/10.1016/S0378-4266(02)00240-6.
Dyson, R. G., & Shale, E. A. (2010). Data envelopment analysis, operational research and uncertainty. The Journal of the Operational Research Society, 61(1), 25-34. http://dx.doi.org/10.1057/jors.2009.145.
Efron, B. (1987). Better bootstrap confidence intervals. Journal of the American Statistical Association, 82(397), 171-185. http://dx.doi.org/10.1080/01621459.1987.10478410.
Fukuyama, H., & Matousek, R. (2011). Efficiency of Turkish banking: two-stage network system. Variable returns to scale model. Journal of International Financial Markets, Institutions and Money, 21(1), 75-91. http://dx.doi.org/10.1016/j.intfin.2010.08.004.
Gaganis, C., Liadaki, A., Doumpos, M., & Zopounidis, C. (2009). Estimating and analyzing the efficiency and productivity of bank branches: evidence from Greece. Managerial Finance, 35(2), 202-218. http://dx.doi.org/10.1108/03074350910923518.
Giokas, D. (2008). Assessing the efficiency in operations of a large Greek bank branch network adopting different economic behaviors. Economic Modelling, 25(3), 559-574. http://dx.doi.org/10.1016/j.econmod.2007.10.007.
Halkos, G. E., & Salamouris, D. S. (2004). Efficiency measurement of the Greek commercial banks with the use of financial ratios: a data envelopment analysis approach. Management Accounting Research, 15(2), 201-224. http://dx.doi.org/10.1016/j.mar.2004.02.001.
Halkos, G. E., & Tzeremes, N. G. (2013). Estimating the degree of operating efficiency gains from a potential bank merger and acquisition: A DEA bootstrapped approach. Journal of Banking & Finance, 37(5), 1658-1668. http://dx.doi.org/10.1016/j.jbankfin.2012.12.009.
Löthgren, M., & Tambour, M. (1999). Testing scale efficiency in DEA models: a bootstrapping approach. Applied Economics, 31(10), 1231-1237. http://dx.doi.org/10.1080/000368499323445.
Macedo, M. A. S., & Barbosa, A. C. M. (2009). Eficiência no sistema bancário Brasileiro: uma análise do desempenho de bancos de varejo, atacado, middle-market e financiamento utilizando DEA. Revista de Informação Contábil, 3, 1-24.
Mandl, C. (2012, September 3). Com juros em queda, bancos perseguem ganhos de eficiência. Valor Econômico: Caderno de Finanças. Retrieved in 23 October 2013, from http://www.valor.com.br/financas/2814064/com-juros-em-queda-bancos-perseguem-ganhos-de-eficiencia/#comments
Paradi, C. P., Rouatt, S., & Zhu, H. (2011). Two-stage evaluation of bank branch efficiency using Data Envelopment Analysis. Omega, 39(1), 99-109. http://dx.doi.org/10.1016/j.omega.2010.04.002.
Pastor, J. T., Lovell, C. A. K., & Tulkens, H. (2006). Evaluating the financial performance of bank branches. Annals of Operations Research, Louvain-la-Neuve, 145(1), 321-337. http://dx.doi.org/10.1007/s10479-006-0038-3.
Périco, A. E., Rebelatto, D. A. N., & Santana, N. B. (2008). Eficiência bancária: os maiores bancos são os mais eficientes? Uma análise por envoltória de dados. Gestão & Produção, 15(2), 421-431. http://dx.doi.org/10.1590/S0104-530X2008000200016.
Portela, M., & Thanassoulis, E. (2007). Comparative efficiency analysis of Portuguese bank branches. European Journal of Operational Research, 177(2), 1275-1288. http://dx.doi.org/10.1016/j.ejor.2006.01.007.
Sealey, C. Jr, & Lindley, J. T. (1977). Inputs, outputs and a theory of production and cost at depository financial Institutions. The Journal of Finance, 32(4), 1251-1266. http://dx.doi.org/10.1111/j.1540-6261.1977.tb03324.x.
Simar, L., & Wilson, P. (2000). A general methodology for bootstrapping in nonparametric frontier models. Journal of Applied Statistics, 27(6), 779-802. http://dx.doi.org/10.1080/02664760050081951.
Simar, L., & Wilson, P. W. (1998). Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models. Management Science, 44(1), 49-61. http://dx.doi.org/10.1287/mnsc.44.1.49.
Stavarek, D. (2005). Estimation of Factors Influencing Efficiency of Banks in New Member States before Joining the European Union. Ekonomicky Casopis, 53, 593-610.
Xue, M., & Harker, P. T. (1999). Overcoming the inherent dependency of DEA efficiency scores: a bootstrap approach (Working Paper, 99-17). The Wharton Financial Institutions Center.
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