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

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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
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