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

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.

Bank efficiency analysis of financial innovations: dea model application for the institutional concept

“…These approaches are called nonparametric research methods and are based on the specification of the exact functional form of the production frontier. SFA, DFA, TFA, OLS and other methods were compared in a series of studies, among others Resti (1997), Caudill (2002, Amelda and Sitanggang (2018). Another group of methods under the second approach includes non-parametric methods such as data envelopment analysis (DEA) applied by Obeid and Brychko (2017), Henriques et al (2018), Shah et al (2019); free disposal hull (FDH) used in Bardhan et al (1996), Wang et al (2019).…”