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Profit efficiency in the European Union banking industry: a directional technology distance function approach

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Abstract

We employ the directional technology distance function approach and present estimates of profit efficiency in the 25 European Union (EU) member states over the period 1998–2008. This method decomposes profit efficiency into its technical and allocative components. We investigate potential efficiency differences across the old EU region and the new EU member states, across countries and across banks of different size. Our results indicate a significant level of profit inefficiency for the EU region, which is predominantly attributed to allocative inefficiency. Our findings also suggest that banks operating in the old EU region are, on average, more profit efficient than credit institutions in the new EU member states. Overall, we observe considerable variation of efficiency scores across countries and different patterns in efficiency change over time, as well as a negative relationship between bank size and efficiency.

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Notes

  1. DEA models based on Shephard distance functions have been used extensively in EU banking studies (see for example, Pastor et al. 1997; Casu and Molyneux 2003; Lozano-Vivas et al. 2001, 2002; Grigorian and Manole 2002; Casu and Girardone 2006). To our knowledge, Devaney and Weber (2002) were the first to use a directional technology distance function approach to estimate profit efficiency for U.S. banks and Koutsomanoli-Filippaki et al. (2009a, b) for CEE banks.

  2. Studies that have investigated efficiency in the European banking industry, and particularly focus on cross-country comparisons, include Allen and Rai (1996), Altunbas et al. (2001), Lozano-Vivas et al. (2001, 2002), De Guevara and Maudos (2002), Maudos et al. (2002), Vander Vennet (2002), Casu and Molyneux (2003), Casu and Girardone (2004), and Koutsomanoli-Filippaki et al. (2009a, b).

  3. According to Molyneux et al. (1996) “greater efficiency might be expected to lead to improved financial products and services, a higher volume of funds intermediated, greater and more appropriate innovations, a generally more responsive financial system, and improved risk-taking capabilities if efficiency profit gains are channelled into improved capital adequacy positions”.

  4. It is assumed that the technology satisfies the axioms listed in Färe and Primont (2003), among which are convexity and free or strong disposability of outputs and inputs.

  5. The Shephard output distance function optimizes over output quantities, but not inputs. Hence if the directional vector g is set at (0, y) then the directional (output) distance function is equal to the reciprocal of the Shephard output distance function minus one. Similarly, the Shephard input distance function optimizes over input quantities but not outputs and if we set g = (x, 0) then the directional (input) distance function is equal to one minus the reciprocal of the Shephard input distance function.

  6. Note that the normalization in (6) means that this profit inefficiency measure is independent of units of measurement and is also well defined even if observed profit is zero or negative. The choice of normalization is not arbitrary; rather it coincides with the value of the Lagrangean multiplier associated with constrained profit maximization as defined in (8) below.

  7. This database reports published financial statements from banks worldwide, homogenized into a global format, which are comparable across countries and therefore suitable for a cross-country study.

  8. For each year the respective figures for the number of banks are: 2,270 (1998); 2,414 (1999); 2,508 (2000); 2,867 (2001); 2,829 (2002); 2,851 (2003); 2,176 (2004); 3,021 (2005); 3,004 (2006); 2914 (2007); 2733 (2008). The additions to the sample are not necessarily new market entrants, but rather successful banks that are added to the database over time. Exits from the sample are due primarily to either mergers with other banks or bank failures.

  9. Note that our efficiency estimates are based on unconsolidated data and thus are bank-specific and do not take explicitly into account the way the production is organized at the conglomerate level. However, Berger et al. (2000) argue that despite the fact that it is not possible to determine the extent to which transfer pricing, shared inputs, and other intra-organizational arrangements might impact efficiency assessments, most evidence suggests that this potential bias is not significant.

  10. A variety of approaches have been proposed in the literature for the definition of bank inputs and outputs; yet, there is little agreement among economists as what unequivocally constitutes an acceptable definition, mainly as a result of the nature and functions of financial intermediaries. See Berger and Humphrey (1997) for a review of studies on financial institution efficiency and the various methods used to define inputs and outputs in financial services.

  11. It was not possible to use the number of employees as a measure of labor for each bank due to incomplete data on the number of employees in the BankScope database. However, we have used this information to construct the labor price data as explained below.

  12. Note that recent studies (e.g. Clark and Siems 2002; Isik and Hassan 2003; Casu and Girardone 2005) introduce off-balance-sheet activities as an additional output, as arguably these activities may have an effect on bank performance measures. However, the IBCA database does not provide detailed information on off-balance sheet activity and hence the inclusion of this variable would result in a significant reduction of our sample. In addition, Becalli et al. (2006) argue that the great variability in accounting practices across countries, especially with respect to the treatment of off-balance-sheet activities, may introduce a remarkable sample bias if off-balance-sheet data are used in cross country studies.

  13. As pointed out by an anonymous referee, caution needs to be exercised with the use of the physical capital input in banking, as the value of fixed assets included in bank balance sheets may be underestimated when physical resources are leased and not owned. These variations in the ownership-leasing mix coupled with differences in accounting practices for fixed assets across countries will also have some effect on price measures defined in relation to fixed assets. This may in part explain the significant variation in the price of capital across countries observed in Table 1.

  14. (Hughes and Moon 1995) and Hughes et al. (1996) tested and rejected the assumption of risk neutrality for banks. And risk taking behavior is more than likely to have increased as more intense competition in the enlarged EU market put a big squeeze on bank profit margins.

  15. German banks as well as banks from Luxembourg are more thinly capitalized holding on average about half of the equity needed to support their assets compared to other EU banks.

  16. This is consistent with the higher interest margin observed in EU-10 countries compared to EU-15 banking systems as discussed above.

  17. Through an intense process of restructuring and growth in the enlarged market, EU-10 banks adopted strategies aimed at improving efficiency, expanding output and increasing the range of services offered (Goddard et al. 2001).

  18. These countries, with the exception of Germany, also exhibit the largest dispersion in profit efficiency scores as measured by the coefficient of variation over the sample period 1998–2008. In particular, according to our estimates, Latvia has experienced a substantial drop in profit efficiency post 2005.

  19. Following an anonymous referee’s suggestion and given that our sample is dominated by small and medium sized German banks, we recalculated average profit inefficiency for banks of different size-classes excluding German banks from our sample in order to assess whether the over-performance of small banks is due to the institutional/regulatory structure of Germany and not because of their small size. Overall, our conclusions remain valid and average inefficiency estimates for small and medium-sized banks remain broadly unchanged. Nevertheless, when excluding German banks, average profit inefficiency for large banks increases.

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Authors and Affiliations

  1. Council of Economic Advisors, Hellenic Ministry of Finance, 5–7 Nikis St., Syntagma Square, 10180, Athens, Greece

    Anastasia Koutsomanoli-Filippaki

  2. The University of Auckland Business School, Auckland, New Zealand

    Dimitris Margaritis

  3. Athens University of Business and Economics, Athens, Greece

    Christos Staikouras

Authors
  1. Anastasia Koutsomanoli-Filippaki
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  2. Dimitris Margaritis
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  3. Christos Staikouras
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Correspondence to Anastasia Koutsomanoli-Filippaki.

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Koutsomanoli-Filippaki, A., Margaritis, D. & Staikouras, C. Profit efficiency in the European Union banking industry: a directional technology distance function approach. J Prod Anal 37, 277–293 (2012). https://doi.org/10.1007/s11123-011-0261-z

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