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

Banon Amelda, Erna Bernadetta Sitanggang
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引用次数: 1

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.
基于参数和非参数方法的印尼银行业绩效效率分析
本研究旨在使用参数和非参数方法衡量印尼银行业的效率绩效,通过基于每年时间序列的银行绩效效率稳定化来衡量,并确定哪些变量对效率值有影响。分析方法采用随机前沿分析(SFA)的横截面方法和参数方法,非参数方法采用数据开发分析(DEA)的CRS和VRS模型的中介方法。本研究的数据为2012-2016年证券交易所上市银行的财务报表,使用Stata 12对29个数据库进行处理。从三种效率测度的分析结果可知,横截面随机前沿分析的效率值对所有银行都显示出稳定和高效的条件。然而,非参数方法显示每家银行的效率水平不同,在DEA CRS模型下,并非所有银行都表现出有效绩效,平均每年只有26.90%的银行表现出有效绩效,而根据VRS模型,99.31%的银行表现出有效绩效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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