Analysis of Banking Industry Performance Efficiency in Indonesia Using Parametric and Nonparametric Methods

Authors

  • Banon Amelda Bina Nusantara University
  • Erna Bernadetta Sitanggang Bina Nusantara University

DOI:

https://doi.org/10.21512/tw.v19i1.4760

Keywords:

performance, efficiency, Stochastic Frontier Analysis (SFA), Data Development Analysis (DEA)

Abstract

This research aimed to measure the efficiency performance of the banking industry in Indonesia by using parametric and nonparametric methods, as measured by the stabilization of bank performance efficiency based on the time series from year to year and to identify which variables to the value of efficiency. The analytical method applied the parametric method with cross section approach of Stochastic Frontier Analysis (SFA) while for nonparametric method used intermediation approach from Data Development Analysis (DEA) CRS and VRS model. The data of this research was the financial statements of banks listed on the stock exchange for the period 2012-2016 with 29 databanks processed with the help of Stata 12. From the results of the analysis using the three measures of efficiency, it is known that the efficiency value with Cross Section Stochastic Frontier Analysis shows a stable and high efficient conditions for all banks. While nonparametric methods show different efficiency levels for each bank, which with DEA CRS model not all banks show an efficient performance, only 26,90% on average each year banks have efficient performance, and 99,31% of banks perform efficiently according to VRS model.

 

Dimensions

Plum Analytics

Author Biographies

Banon Amelda, Bina Nusantara University

Accounting and Finance Department, Faculty of Economy and Communication

Erna Bernadetta Sitanggang, Bina Nusantara University

Accounting and Finance Department, Faculty of Economy and Communication

References

Bauer, W. P., Berger, N. A., Ferrier, D. G, & Humphrey, B. D. (1998). Consistency conditions for regulatory analysis of financial institutions: A comparison of Frontier Efficiency Methods. Journal of Economics and Busines, 50, 85-144.

Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale ineffeciencies in data envelopment analysis. Management Science, 30(9), 1078–1092.

Charnes, A., Cooper,W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429-444.

Coelli, T. J., Rao, D. S. P., O’Donnel, C. J., Battese, G. E. (2005). An introduction to efficiency and productivity analysis. USA: Springer.

Ferrier, D. G., & Lovell, C. A. K. (1990). Measuring cost efficiency in banking; Econometric and linear programming evidence. Journal of Econometrics, 46(2), 229–245.

Fiorentino, E., Karmann, A., & Koetter, M. (2006). The cost efficiency of German banks: A comparison of SFA and DEA. Retrieved on May 15th, 2017 from https://papers.ssrn.com.

Fries, S., & Taci, A. (2004). Cost efficiency of banks in transition: Evidence from 289 banks in 15 post-communist countries. European Bank for Reconstruction and Development Working Paper, 86, 1-29.

Hartono, E. (2009). Cost efficiency analysis of Indonesian banking industry using parametric method Stochastic Frontier Analysis. Master Thesis. Semarang: University of Diponegoro.

Hasan, I., & Hunter, W. C. (1996). Efficiency of Japanese multinational banks in the United States. Research in Finance, 14, 157-173.

Ji, Y. B., & Lee, C. (2010). Data envelopment analysis. The Stata Journal, 10(2), 267-280.

Muazaroh., Eduardus, T., Husnan, S., & Hanafi, M. M. (2012). Determinants of bank profit efficiency: Evidence from Indonesia. International Journal of Economics and Finance Studies, 4(2), 163-

Muljawan, D., Hafidz, J., Astuti, R. I., & Oktapiani, R. (2014). Determinants of Indonesia banking efficiency and its impact on credit interest calculation. Working Paper of Bank Indonesia.

Purwanto, R. (2011). Comparative analysis of efficiency of conventional commercial bank (Buk) and sharia (Bus) commercial bank in Indonesia with Data Envelopment Analysis (DEA) method

(period 2006-2010). Master Thesis. Semarang: University Diponegoro.

Rahmawati, R. (2011). Cost efficiency enhancement strategy in sharia commercial banks based on Stochastic Frontier Approach And Data Envelopment Analysis. Buletin Monetary and Banking Economy, 17(4), 457-480.

Rahmi, M. S. (2008). Analysis of efficiency of sharia business unit in Indonesia Data Envelopment Analysis Method (DEA) and Sthocastic Frontier Approach (SFA). Master Thesis. Bogor: Tazkia University College of Islamic Economic.

Republik Indonesia. (1998). Undang-undang no.10 tahun 1998 tentang perubahan atas unudangundang no. 7 thaun 1992 tentang perbankan. Tambahan Lembaran Negara Republik Indonesia, No. 3790. Sekretariat Negara. Jakarta.

Siregar, L. M., Mariana., and Umanto. (2015). Analysis of the efficiency of performance of commercial banks with data development methods analysis. Retrieved on April 18th, 2017.

Yassine, B., & Soumia, A. H. (2016). Assessing cost and profit efficiency by a joint application of parametric and non-parametric approaches: Evidence from the Algerian banking system.

EconWorld 2016 @ImperialCollage Proceedings. London, UK. Pp. 1-29.

Yekti, A., Darwanto, H. D., Jamhari., & Hartono, S. (2015). Technical efficiency of melon farming in Kulon Progo: A Stochastic Frontier Approach (SFA). International Journal of Computer Applications, 132(6), 975 - 8887.

Downloads

Published

2018-03-31

How to Cite

Amelda, B., & Sitanggang, E. B. (2018). Analysis of Banking Industry Performance Efficiency in Indonesia Using Parametric and Nonparametric Methods. Journal The Winners, 19(1), 53-67. https://doi.org/10.21512/tw.v19i1.4760
Abstract 1389  .
PDF downloaded 330  .