Cost efficiency of the Chinese banking sector: A comparison of stochastic frontier analysis and data envelopment analysis

2014 ◽  
Vol 36 ◽  
pp. 298-308 ◽  
Author(s):  
Yizhe Dong ◽  
Robert Hamilton ◽  
Mark Tippett
Keyword(s):  
Data Envelopment Analysis ◽  
Cost Efficiency ◽  
Banking Sector ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Data Envelopment ◽  
Frontier Analysis ◽  
Chinese Banking

A comparative approach of stochastic frontier analysis and data envelopment analysis estimators: evidence from banking system

2020 ◽  
Vol 47 (7) ◽  
pp. 1787-1810
Author(s):  
Kekoura Sakouvogui
Keyword(s):  
Data Envelopment Analysis ◽  
Cost Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Data Envelopment ◽  
Content Type ◽  
Frontier Analysis ◽  
Efficiency Measures ◽  
Clustering Approach ◽  
Over Time

PurposeThe consistency of stochastic frontier analysis (SFA) and data envelopment analysis (DEA) cost efficiency measures using a sample of 650 commercial and domestic banks in the United States is investigated based on cluster analysis while accounting for the yearly variation in banks.Design/methodology/approachDue to the importance of efficiency measures for policy and managerial decision-making, the cost efficiency measures of SFA and DEA estimators are examined according to four criteria: levels, rankings, stability over time and stability over clustering groups. In this paper, we present two clustering methods, Gap Statistic and Dindex, that involve SFA and DEA cost efficiency measures. The clustering approach creates homogeneous groups of banks offering a similar mix of efficiency levels. Hence, each evaluated bank knows the cluster to which it belongs. Furthermore, this paper provides nonparametric statistical tests of SFA and DEA cost efficiency measures estimated with and without a clustering approach.FindingsThe results suggest that the clustering approach plays a considerable role in the rankings of US banks. Furthermore, the average SFA and DEA cost efficiency measures over time of the homogeneous US banks are substantially higher than those of the heterogeneous US banks.Originality/valueThis research is the first to provide comparative efficiency measures needed for desirable policy conclusions of heterogeneous and homogeneous US banks.

scholarly journals Labour efficiency in construction industry in Europe based on frontier methods: data envelopment analysis and stochastic frontier analysis

2017 ◽  
Vol 23 (6) ◽  
pp. 787-795 ◽  
Author(s):  
Joanicjusz NAZARKO ◽  
Ewa CHODAKOWSKA
Keyword(s):  
Data Envelopment Analysis ◽  
Construction Industry ◽  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Efficiency Analysis ◽  
European Countries ◽  
Personnel Cost ◽  
Data Envelopment ◽  
Frontier Analysis

The primary problems pertaining to productivity or – more precisely – efficiency are: how to define it and how to measure it. This article studies technical efficiency in Stochastic Frontier Analysis (SFA) – the input-oriented frontier model – in the construction industry and compares it with Data Envelopment Analysis (DEA) results. The models ex­plored in this paper were constructed on the basis of two outputs and personnel cost as an input. The research sample consisted of European countries. The aim was to determine whether there are substantial differences in estimation of ef­ficiency derived from those two alternative frontier approaches. The comparison of results according to the models may translate into higher reliability of the undertaken labour efficiency analysis in construction and its conclusions. Although the results are not characterized by high compatibility, the conducted analysis indicated the most attractive countries taking into account labour cost to profit and turnover ratios of enterprises. One of the determinants which should not be ignored when analysing the labour efficiency is the level of development of a country; however, it is not the sole factor affecting the efficiency of the sector.

scholarly journals The Cost Efficiency of the Brazilian Electricity Distribution Utilities: A Comparison of Bayesian SFA and DEA Models

2010 ◽  
Vol 2010 ◽  
pp. 1-20 ◽  
Author(s):  
Marcus Vinicius Pereira de Souza ◽  
Madiagne Diallo ◽  
Reinaldo Castro Souza ◽  
Tara Keshar Nanda Baidya
Keyword(s):  
Cost Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Fundamental Aspect ◽  
Data Envelopment ◽  
Electricity Distribution ◽  
Frontier Analysis ◽  
Dea Models ◽  
The Cost ◽  
Analysis Models

The purpose of this study is to evaluate the efficiency indices for 60 Brazilian electricity distribution utilities. These scores are obtained by DEA (Data Envelopment Analysis) and Bayesian Stochastic Frontier Analysis models, two techniques that can reduce the information asymmetry and improve the regulator's skill to compare the performance of the utilities, a fundamental aspect in incentive regulation schemes. In addition, this paper also addresses the problem of identifying outliers and influential observations in deterministic nonparametric DEA models.

scholarly journals THE EFFECTS OF COMPETITION ON EFFICIENCY: THE VIETNAMESE BANKING INDUSTRY EXPERIENCE

2017 ◽  
pp. 1-30 ◽  
Author(s):  
THANH PHAM THIEN NGUYEN ◽  
SON HONG NGHIEM
Keyword(s):  
Cost Efficiency ◽  
Banking Sector ◽  
Stochastic Frontier Analysis ◽  
Global Financial Crisis ◽  
Stochastic Frontier ◽  
Bank Efficiency ◽  
Frontier Analysis ◽  
The Cost ◽  
Efficiency Effects ◽  
Industry Experience

Given considerable changes in the Vietnamese banking environment brought about by significant reforms towards liberalization during the last two decades, this study investigates the evolution of competition and efficiency, compares the competition and efficiency of state-owned banks to joint-stock banks, and then tests the “quiet life” hypothesis in this industry over the period 2000–2014. This study employs the efficiency-adjusted Lerner index (i.e., market power) to capture competition, and the cost efficiency estimated by a Fourier-flexible function stochastic frontier analysis (SFA) to capture bank efficiency. This study firstly finds a slight improvement of competition and cost efficiency in the Vietnamese banking sector over the analysis period. Secondly, there are no significant differences in competition and cost efficiency level between state-owned and joint-stock banks. Thirdly, a positive causality running from competition to cost efficiency is documented, providing evidence of supporting the “quiet life” hypothesis. Finally, positive efficiency effects of the banks’ capital ratio and size are found, while insignificant impacts of the growth of GDP per capita and 2007 global financial crisis were observed. The results are strongly robust to a variety of tests. The findings suggest pro-competition, pro-capitalization and pro-size expansion policies in the Vietnamese banking sector if targeting at improving the cost efficiency of Vietnamese banks.

scholarly journals Efficiency in Vietnamese Banking: A Meta-Regression Analysis Approach

2021 ◽  
Vol 9 (3) ◽  
pp. 41
Author(s):  
Tin H. Ho ◽  
Dat T. Nguyen ◽  
Thanh Ngo ◽  
Tu D. Q. Le
Keyword(s):  
Regression Analysis ◽  
Banking Sector ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Data Envelopment ◽  
Truncated Regression ◽  
Frontier Analysis ◽  
Meta Regression ◽  
Meta Regression Analysis ◽  
Frontier Efficiency

This study explains the differences and variances in the efficiency scores of the Vietnamese banking sector retrieved from 27 studies published in refereed academic journals under the framework of meta-regression analysis. These scores are mainly based on frontier efficiency measurements, which essentially are Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) for Vietnamese banks over the period of 2007–2019. The meta-regression is estimated by using truncated regression to obtain bias-corrected scores. Our findings suggest that only the year of publication is positively correlated with efficiency, whilst the opposite is true for the data type, and sample size.

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