A comparison of nonparametric efficiency estimators: DEA, FDH, DEAC, FDHC, order-m and quantile (original) (raw)
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Financial statistical journal, 2024
This work aims to analyze the efficiency of Brazilian financial institutions until the COVID-19 pandemic period, from production and profitability perspectives. To accomplish this, the data envelopment analysis (DEA) techniques, specifically the CCR and BCC models, are applied to 213 Brazilian financial institutions in four methodological stages. The first step involved conducting a literature review of similar studies. The second step consisted of gathering financial information for each bank through the website of the Central Bank of Brazil. The third step involved selecting the variables to be used in the models. The fourth step was outlier detection using the jackstrap method. Subsequently, the mentioned efficiency models were applied, and the most efficient banks were identified based on each perspective. The results identified heterogeneous groups of efficient banks based on different market segments, with a focus on the efficiency of large banks and public banks when considering the production-oriented perspective. It is also observed that new digital banks are among the banks considered efficient. These findings are valuable for the scientific literature investigating the sustainability of financial institutions, as well as for decision-makers seeking to make more efficient investment allocations and for banking supervisory authorities in formulating risk regulatory policies.
This paper uses an output oriented Data Envelopment Analysis (DEA) measure of technical efficiency to assess the technical efficiencies of the Brazilian banking system. Four approaches to estimation are compared in order to assess the significance of factors affecting inefficiency. These are nonparametric Analysis of Covariance, maximum likelihood using a family of exponential distributions, maximum likelihood using a family of truncated normal distributions, and the normal Tobit model. The sole focus of the paper is on a combined measure of output and the data analyzed refers to the year 2001. The factors of interest in the analysis and likely to affect efficiency are bank nature (multiple and commercial), bank type (credit, business, bursary and retail), bank size (large, medium, small and micro), bank control (private and public), bank origin (domestic and foreign), and non-performing loans. The latter is a measure of bank risk. All quantitative variables, including non-performing loans, are measured on a per employee basis. The best fits to the data are provided by the exponential family and the nonparametric Analysis of Covariance. The significance of a factor however 1 varies according to the model fit although it can be said that there is some agreements between the best models. A highly significant association in all models fitted is observed only for nonperforming loans. The nonparametric Analysis of Covariance is more consistent with the inefficiency median responses observed for the qualitative factors. The findings of the analysis reinforce the significant association of the level of bank inefficiency, measured by DEA residuals, with the risk of bank failure.
International Journal of Business, Economics and Management, 2016
Objective: This paper provides a survey of efficiency in banks using Data Envelopment Analysis (DEA) in developed and developing countries. Methods: There are two ways were used; the first one is analyse previous reviews, and the other one is systemic search from ProQuest, Emerald, Scopus and Science Direct. The search conducted to identify efficiency in banks in developed and developing countries. Originality: This study contributes in the existing literature in measuring efficiency in banks using DEA as a non-parametric technique. Results: Studies that was survey showed that the score of allocative efficiency was more than technical and cost efficiencies. Also, Studies showed that the scores of cost efficiency were more than the scores of profit efficiency. Conclusion: This paper shows that most of these studies were conducted in developed countries context, Also many studies were in developing countries. But, very few studies were conducted in the context of banking industry in Arab countries.
Efficiency Estimation of the Banking Industry in Bangladesh: A Non-Parametric Data Driven Approach
2017
Examining the banking sector efficiency is vital for ensuring a financial system as banks act as transmission channel of monetary policy. This paper aims to estimate the overall, pure technical and scale efficiencies of the banking industry of Bangladesh by using a non-parametric data driven technique, Data Envelopment Analysis (DEA,) on data of 36 commercial banks. This paper also applies a general idea of using bilateral comparison in DEA to compare the performances of state and private banks in Bangladesh. The overall technical efficiency of banks in Bangladesh ranges from 76.6% to 91.3% depending on different model specifications. The results of bilateral comparison reveal that private banks (PCBs) outperform state banks (SCBs). With the revised samples, after detecting the possible outliers, the findings also validate the argument that the PCBs outperform SCBs. The estimated scale efficiency revealed that banks in Bangladesh have ample room to increase their efficiency, especia...
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.
Determinants of bank efficiency: evidence from the Latin American banking industry
Applied economic analysis, 2019
Purpose-The purpose of this paper is to analyze a variety of factors that can explain the differences in commercial bank efficiency among 17 countries in Latin America (LatAm). Design/methodology/approach-In a first stage, data envelopment analysis (DEA) and conditional efficiency analysis techniques are used to assess the relative efficiency level of 409 banks for the 2014-2016 period. The conditional efficiency approach considers environmental variables (that are beyond the manager's control), which could influence the shape and the level of the boundary of the attainable set. In the second stage, the resulting conditional efficiency scores are correlated with internal variables (those that are under the manager's control), which might affect the distribution of the inefficiencies. For this purpose, an econometric approach developed by Simar and Wilson (2007) is used. Findings-First stage scores reveal the heterogeneity of average efficiency within the region. Regarding the factors that may explain the differences in performance in the LatAm banking sector, the results allow us to state that certain internal variables such as bank size, the ratio of loans to total assets and the ratio of nonperforming loans show the expected relationship to efficiency, in line with much of the previous literature. Originality/value-This is the first time that conditional efficiency and Simar and Wilson (2007) approaches have been applied at the same time to analyse the LatAm banking industry.
Ssrn Electronic Journal, 2013
This paper analyzes technical efficiency of domestic commercial banks in Malaysia between 1995 and 2009 by using the Data Envelopment Analysis (DEA) window analysis. By this approach, the technical efficiency is analyzed sequentially with a certain window width (i.e. the number of years in a window) using a panel data of five domestic banks. The main idea is to capture the temporal impact on bank technical efficiency and see its short-run evolution from one window to another, in particular the pure technical efficiency (X-efficiency or managerial efficiency) and scale efficiency. By this, the study avoids the comparison of banks in different years as separate observations measured against each other, which can be unrealistic because of the significant technological diffusion in banking over the period under analysis. The results suggest that on average the domestic commercial banks have some degree of inefficiency, which is more so due to pure technical rather than scale effects. Thus, Malaysian commercial banks should gain more from reducing the input quantities used or increasing the output quantities produced. The commercial banks should not worry too much about not choosing the correct scale for production though the study found out that on average the banks have not fully exhausted economies of scale.
An enhanced DEA model for decomposition of technical efficiency in banking
Annals of Operations Research, 2011
Past studies about the application of data envelopment analysis (DEA) to banking performance often follow the concept of technical efficiency (TE) and/or the productivity defined by the TE. In this paper, we propose an enhanced DEA model, based on a modification of the directional distance function by simultaneously but disproportionately seeking the maximum expansion of each desirable output and contraction of each undesirable output for efficiency measurement, which allows us to decompose the TE into operating efficiency (OPE) and risk management efficiency (RME). The OPE characterizes the ability of a bank to expand the room for profits through its regular business activities, while the RME describes a bank's ability in risk management activities for sustaining operations. To illustrate the usefulness of the proposed model, a case study of Taiwan's domestic commercial banks is presented. The major findings are that operating inefficiency is the main source of technical inefficiency, although banks with a higher OPE generally also have a higher RME. Banks subordinate to financial holding companies are more efficient in both OPE and RME than stand-alone banks.
2009
approved: _____________________________________________________________________ Victor J. Tremblay In this paper, I estimate efficiency and productivity change in the U.S. banking industry. The data consist of annual observations of 25 banks from 2004 to 2008. The paper follows a two-stage procedure. In the first-stage, utilizing the non-parametric methodologies, input-oriented Data Envelopment Analysis (DEA) model and DEA based Malmquist indices are used to estimate the efficiency scores for each bank in the sample. Further, the productivity index is decomposed into technical efficiency and technological change components. In the second-stage, I use Tobit censored regression to determine the impact of ‘environmental’ factors on banks’ efficiency. The results of DEA suggest that U.S. banks experienced an average annual productivity growth of almost 9 percent over the sample period as well as that the dominant source of efficiency is technological change (TC) which shows 10.8 percent...
Data envelopment analysis: a tool for monitoring the relative efficiency of Lebanese banks
2008
This paper implements a Data Envelopment Analysis (DEA) approach to measure the relative performance of Lebanese banks over an 8-year period (1997 to 2004). It also demonstrates DEA as an effective monitoring tool for central banks to track banks' efficiencies to maintain a sustainable growing sector and to provide early warning signals for a potentially at risk bank. DEA input and output parameters are identified for the Lebanese banking sector as an intermediary player between savers and investors. For each bank, a DEA efficiency score is computed, decomposed into technical and scale efficiencies, and tracked on a yearly basis. During the period of this study, some banks failed and closed, and some merged and acquisitioned, hence characteristics of failed and merged banks are investigated with a close attention to their technical efficiency patterns. We conclude with a positive recommendation on the usage of DEA and highlight future research directions.