Efficiency of Financial Institutions: International Survey and Directions for Future Research (original) (raw)
Related papers
SSRN Electronic Journal, 2000
This paper examines the properties of the X-inefficiencies in U.S. bank holding companies derived from both stochastic and linear programming frontiers. This examination allows the robustness of results across methods to be compared. While we find that calculated programming inefficiency scores are two to three times larger than those estimated using a stochastic frontier, the patterns of the scores across banks and time are similar, and there is a relatively high correlation of the rankings of banks' efficiencies under the two methods. However, when we examine the "informativeness" of the efficiency measured by the two different techniques, we find some large differences. We find evidence that the stochastic frontier scores are more closely related to risk-taking behavior, managerial competence, and bank stock returns. Based on these findings, we conclude that while both methods produce informative efficiency scores, for this data set decision makers should put more weight on the stochastic frontier efficiency estimates.
Study of Efficiency Measures in the Banking Sector-Quantitative Analysis with Qualitative Inferences
SIBR, 2011
Achievement of Efficiency is considered to be an important factor for all entities , yet it is a tricky one, primarily because it is measured in relative and comparative terms. For the financial sector , it has tremendous importance, having material benefits and losses too. Therefore it becomes an important benchmark of achievement. This study is first part of a series of studies to be continued in the efficiency measurement in the financial sector in Pakistan. The current study measures efficiency of fourteen select banks in the financial sector of Pakistan and addresses the interpretation of efficiency. It uses the parametric OLS technique, using the definition of efficiency and the set of variables chosen from the CAMEL rating system of the regulators of financial institutions. It further applies the non parametric Data Envelopment Analysis Approach to the sample and assesses their relative efficiency in terms of inputs and outputs of the intermediation approach. It discusses the results in the context of the background of the variables of assessment and their relationship to efficiency of banks. The study aims at finding a better view of performance in the financial sector for more reliable results.
iaeme, 2013
The following research article discusses the technique to measure the technical efficiency of Decision Making Units(DMUs). Efficiency means to measure how well the DMUs are doing given the circumstance & inputs. Decision Making Units are similar enterprises ranging from publically held companies , Privately owned corporation, Banks, Non-profit organization, airports etc. There are many ways to calculate efficiency of DMUs. This research paper will focus on the Banking sector. Financial Ratios is one of leading methods to calculate efficiency of Banks. Liquidity, profitability, & leverage position of the enterprises are calculated to understand the ranking of various Banks. Data envelopment Analysis technique is the latest methodology to benchmark performance of Banks. Data envelopment Analysis is a non-parametric approach used through linear programming to decide efficiency of similar enterprises. The following research paper discusses the various studies conducted by authors using both financial ratios& DEA. The article also discusses research work carried out by authors on Data Envelopment Analysis, specifically.
Wseas Transactions On Business And Economics, 2023
This study's objective is to employ data envelopment analysis (DEA) and stochastic frontier analysis (SFA) to investigate the efficiency accomplishments of Indonesian commercial banking from 2018 to 2019. The first method of measuring efficiency employing a non-parametric data envelopment analysis (DEA) technique reveals that the average efficiency of 71 banks fell from 2018 (0.82) to 2019 (0.81). According to DEA findings, major banks outperform small banks on average. According to the approximated SFA Cobb-Douglas (CD) function, interest expenditure and labor expense have a positive and considerable influence on interest income. This occurs when deposit interest rates rise, banks gain interest revenue by raising lending rates, and banks increase non-interest income. According to the SFA of the Cobb-Douglas function, many banks are inefficient, particularly the first to 49th banks that arise from small banks. The Gamma value is near one (0.999), while the LR test yields a significant result of 36.14. The Cobb-Douglas SFA model is therefore applicable. The efficiency performance findings from the two models above reveal the same thing: large banks are more efficient than small banks.
Evaluating productive efficiency:comparative study of commercial banks in Gulf countries
2010
Financial institutes are an integral part of any modern economy. In the 1970s and 1980s, Gulf Cooperation Council (GCC) countries made significant progress in financial deepening and in building a modern financial infrastructure. This study aims to evaluate the performance (efficiency) of financial institutes (banking sector) in GCC countries. Since, the selected variables include negative data for some banks and positive for others, and the available evaluation methods are not helpful in this case, so we developed a Semi Oriented Radial Model to perform this evaluation. Furthermore, since the SORM evaluation result provides a limited information for any decision maker (bankers, investors, etc...), we proposed a second stage analysis using classification and regression (CR Thick Frontier Analysis (TFA) and Distribution-Free Analysis (DFA). The result shows that DEA and SFA are the most applicable methods in banking sector, but DEA is seem to be most popular between researchers. Howe...
Ranking influencing factors on relative efficiency of banking industry
Management Science Letters, 2013
Measuring the relative efficiency of banking industry has been one of the most interesting areas of research for the past few years. There are literally various techniques for measuring the relative performance of similar units such as banks including data envelopment analysis and stochastic frontier analysis. This paper presents an empirical investigation to measure the relative performance of some Iranian banks located in province of Alborz, Iran for two consecutive fiscal years of 2009 and 2010. The proposed study implements stochastic frontier analysis to measure the performance of these banks based on two set of criteria. In the first model, total loans devoted are considered as output and employees, total customers' investment, total fixed assets as well as no-interest deposits are considered as inputs of the model. For the second model, special banks' characteristics such as total economic value of branch, the ratio of fixed assets to total assets, educational backgrounds of employees as well as the level of automation in the system are considered as input parameters of the systems. The results indicate that most bank perform relatively well according to their efficiencies.