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Published in: Journal of Quantitative Economics 1/2017

26-05-2016 | Original Article

Benchmarking Banking Efficiency Using a Meta-Profit Function

Authors: Ihsen Abid, Mohamed Goaied

Published in: Journal of Quantitative Economics | Issue 1/2017

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Abstract

This paper applies the meta-frontier approach to investigate the profit efficiency level of the banking sector in the MENA region. This approach enables the assessment of the banking efficiency while considering technological gap between the investigated countries and the whole banking industry. We integrate the country-specific conditions in the designed model (macro-financial, macro-economic, regulatory and banking characteristics). Empirical results were obtained through a dataset of seven countries, namely Tunisia, Morocco, Algeria, Egypt, Jordan, Lebanon and Turkey, over the period from 1991 to 2011. The analysis supports the view that profit efficiency varies from one country to another, and the technological gap plays an important role in explaining the ability of the banking sector in one country to compete with others. The results of the efficiency scores corrected by technological and environmental heterogeneities led us to conclude that Jordanian banks were the most efficient while the Lebanese banks enjoyed a very advantageous banking technology. This work eventually emphasizes relevant recommendations to improve the performance of the banking sector.

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Appendix
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Footnotes
1
Berger and Humphrey (1997) present a survey on the efficiency literature and among the 130 studies, only fourteen employed a profit efficiency perspective.
 
2
Among the exceptions: Berg et al. (1993), Fecher and Pestieau (1993), Vander-Vennet (1994), Berg et al. (1995), Bergendahl (1995), Allen and Rai (1996), Ruthenberg and Elias (1996), Pastor et al. (1997) and Vander-Vennet (1999).
 
3
These variables are further defined in the DATA section.
 
4
For more details, See Battese and Coelli (1992), Coelli (1996) and Coelli et al. (1999).
 
5
The estimation of the meta-frontier function is based on data generation mechanisms from each of the N group of countries. Therefore, the meta-frontier is entirely based on the N group frontiers, which calls for minimizing the squared distance to the frontier, because we want the meta-frontier to envelope tightly around the N group frontiers. However, we consider the absolute deviation, which would result in a less tight envelope.
 
6
There are no listed banks in Algeria; so, the choice of banks is done in order of ranking in terms of assets (Total \(\hbox {Assets} > 1000\) mil USD last available year).
 
7
The Translog form is a better choice for our model. Berger and Mester (1997) compared the Translog form to the alternative Fourier flexible form. In spite of the last additional flexibility, the difference in results between the two methods appears to be negligible. Moreover, Swank (1996) found evidence that supports the stability of the diversified Translog model of a set of comparable data for the Dutch banking sector.
 
8
To evaluate the efficiency of the banking sectors of the countries in the sample with the meta-frontier, we perform first the likelihood ratio test (LR) to detect if there is a difference in technology and environments between countries. Then we construct the meta-frontier if the LR test indicates a significant difference. Finally, we estimate the ratio of technology and environmental gap and the efficiency scores. The LR test statistic for the null hypothesis that national frontiers are the same for all countries is calculated after estimating the stochastic frontier by combining data from all countries. The hypothesis is rejected at 1 %. This allows us to conclude that the specific frontiers of groups are heterogeneous: banks in different countries operate under different technologies and environments. The statistical software SHAZAM 10.0 is used to estimate the parameters of the meta-frontier.
 
9
This judgment is supported by previous findings in the literature (Bikker 2002; Dietsch and Lozano-Vivas 2000).
 
10
Across national frontiers, we found that Turkish banks were on average more efficient in terms of profit and the banking sector of Lebanon had the lowest profit efficiency score. Through the meta-frontier, we found that Jordanian banks were the most efficient in terms of profit but Algerian banks were the least efficient in terms of profit than banks in other countries.
 
11
Battese et al. (2004) obtained a similar negative relationship between efficiency and TGR; the Jakarta region had the lowest average score of technical efficiency and the highest mean TGR among the five regions studied, while the reverse is true for the region of East Java.
 
12
This form of rigidity appears to be persuasive because the quasi-fixed inputs are present in virtually all sectors of an economy (Ouellette and Vierstraete 2004). Factors such as large adjustment costs, regulations, information and transaction costs and indivisibility of some inputs are the main source of the quasi-fixity. Specifically, a central part of deposits and physical capital are often considered as quasi-fixed with the banking sector, for example, by Flannery (1982), Humphrey (1993), Berger et al. (1993), Noulas et al. (1990) and Hunter and Timme (1995).
 
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Metadata
Title
Benchmarking Banking Efficiency Using a Meta-Profit Function
Authors
Ihsen Abid
Mohamed Goaied
Publication date
26-05-2016
Publisher
Springer India
Published in
Journal of Quantitative Economics / Issue 1/2017
Print ISSN: 0971-1554
Electronic ISSN: 2364-1045
DOI
https://doi.org/10.1007/s40953-016-0043-6

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