scholarly journals An assessment of relative efficiency of banks in Sri Lanka

2012 ◽  
Vol 9 (3) ◽  
pp. 357-372
Author(s):  
Lalith Seelanatha ◽  
Weerasinghe Hilary Elmo Silva

This paper examines how the financial reforms introduced throughout last 30 year period have improved the managerial efficiency of firms in the banking industry in Sri Lanka. Using non-parametric data envelopment analysis (DEA), this study estimated relative efficiency of banking firms in Sri Lanka using a sample of data collected from 20 year cross section (1989-2008). The study found that the banks in Sri Lanka have recorded relatively higher level of efficiency. Both managerial decisions and scale of operation have been equally contributed to the recorded inefficiency. We found that large banks were relatively more efficient than small banks. However, medium size banks were recorded relatively lower levels of efficiency which were mainly contributed by the managerial factor.

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1522
Author(s):  
Ricardo F. Díaz ◽  
Blanca Sanchez-Robles

Increases in the cost of research, specialization and reductions in public expenditure in health are changing the economic environment for the pharmaceutical industry. Gains in productivity and efficiency are increasingly important in order for firms to succeed in this environment. We analyze empirically the performance of efficiency in the pharmaceutical industry over the period 2010–2018. We work with microdata from a large sample of European firms of different characteristics regarding size, main activity, country of origin and other idiosyncratic features. We compute efficiency scores for the firms in the sample on a yearly basis by means of non-parametric data envelopment analysis (DEA) techniques. Basic results show a moderate average level of efficiency for the firms which encompass the sample. Efficiency is higher for companies which engage in manufacturing and distribution than for firms focusing on research and development (R&D) activities. Large firms display higher levels of efficiency than medium-size and small firms. Our estimates point to a decreasing pattern of average efficiency over the years 2010–2018. Furthermore, we explore the potential correlation of efficiency with particular aspects of the firms’ performance. Profit margins and financial solvency are positively correlated with efficiency, whereas employee costs display a negative correlation. Institutional aspects of the countries of origin also influence efficiency levels.


2021 ◽  
Vol 11 (3) ◽  
pp. 427
Author(s):  
Ari Christianti

Banking efficiency is very important in supporting the success of macro policies specifically, maintaining the sustainability of development that affects economic growth and social welfare. This study discusses the efficiency of commercial banks for the 2015-2019 period using data from the 10 largest commercial banks in Indonesia. The methodology used is non-parametric, Data Envelopment Analysis, to analyze technical efficiency. The results showed that 7 banks had a maximum efficiency level consistently during the study period and there were still 3 banks that did not reach the maximum efficiency but during certain periods or periods. Based on the results of the DEA, inefficient banks in a certain period can achieve maximum efficiency by reducing inputs such as labor costs, net fixed assets, and the number of deposits. This might be attributed that the competition in the banking industry and because not all inputs could be controlled by management, some large banks cannot maintain their level of efficiency consistently.


Author(s):  
Supran Kumar Sharma ◽  
Raina Dalip

Purpose – The purpose of this paper is to attempt to measure the performance of the Indian banking sector in terms of efficiency and productivity levels and their determinants during the post-reform period. Design/methodology/approach – The present study is a novel attempt as it has used pooled data for a duration of 15 years (i.e. 1997/1998-2010/2011) from 59 selected banks for estimating the Hicks-Moorsteen (HM) total factor productivity (TFP) index. Findings – Poor technical efficiency has experienced with scale efficiency change exerting dominant factors; whereas relatively better productivity growth has been experienced by the banks with major contributions from technical change components. The study found relatively underestimated efficiency and productivity levels by traditional data envelopment analysis-based Malmquist index. Additionally, the study brings into account the results for external and environmental determining factors contributing to the TFP growth. Originality/value – Using HMTFP indices has helped to eliminate certain drawbacks of data envelopment and provided the more elaborative decomposition of productivity growth along with their components so as to have lucid and multidimensional insights about the performance of the Indian banking industry after the initiation of financial reforms.


Author(s):  
Daniel Stavárek ◽  
Iveta Řepková

This paper estimates the efficiency of the Czech commercial banks in the period 2001–2010 using the non-parametric Data Envelopment Analysis. We simultaneously use two alternative specifications – CCR model and BCR model – that differ in returns to scale assumption. Differences in estimated efficiency scores of individual banks are quite large up to 70 percentage points. Largest banks perform significantly worse than mid-size and small banks. This efficiency gap decreases if variable returns to scale are considered in the estimation. The average efficiency in the banking sector remained nearly unchanged during the analysed period. Although each year is estimated separately one can observe a deterioration of average efficiency during the recent crisis period.


2017 ◽  
Vol 18 (5) ◽  
pp. 833-851 ◽  
Author(s):  
Chih-Ching YANG

The increase in non-performing loans around the world has had quite a negative impact on many nations’ banking systems. To address these problems, many creative regulatory solutions and well-designed risk techniques have been utilized in the hope of reducing non-performing loans to an acceptable level. The purpose of this study is to apply a newly developed data envelopment analysis model to suggest the most efficient plan (called Plan 4) to reduce non-performing loans that can maximize the efficiency of the entire banking industry’s control over the bad debts. For comparison purpose, three other reduction plans are also represented. The four plans are presented using data from Taiwan’s banking industry. The empirical results show that among the plans presented, Plan 4 shows the most effective allocation of the industry-wide reduction target. The plan focuses on a finite number of banks, helping identify the key units to improve industry-wide efficiency. The findings implicitly suggest that the regulator should devise more incentive measures to encourage target banks to perform the non-performing loan reduction task. Our results also suggest that for the regulator, forcing banks to cut their non-performing loans by the same ratio will not help improve the relative efficiency of the industry.


2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output


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