Halkos, George and Tzeremes, Nickolaos (2010): Measuring the effect of virtual mergers on banks’ efficiency levels:A non parametric analysis.

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Abstract
This study illustrates how the recent developments in efficiency analysis and statistical inference can be applied when evaluating banks’ performance issues from a potential merger. By using a sample of 29 Greek commercial banks the paper provides a six step procedure in order to evaluate whether a potential bank merger can exhibit economies of scale and characterized as favorable.
Item Type:  MPRA Paper 

Original Title:  Measuring the effect of virtual mergers on banks’ efficiency levels:A non parametric analysis 
Language:  English 
Keywords:  Data Envelopment Analysis; Bootstrap techniques; Virtual Mergers; Bank efficiency. 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C14  Semiparametric and Nonparametric Methods: General C  Mathematical and Quantitative Methods > C6  Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C61  Optimization Techniques; Programming Models; Dynamic Analysis C  Mathematical and Quantitative Methods > C6  Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C67  InputOutput Models G  Financial Economics > G2  Financial Institutions and Services > G21  Banks; Depository Institutions; Micro Finance Institutions; Mortgages C  Mathematical and Quantitative Methods > C6  Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C60  General 
Item ID:  23696 
Depositing User:  Nickolaos Tzeremes 
Date Deposited:  10. Jul 2010 01:16 
Last Modified:  13. Feb 2013 23:18 
References:  Andersen, P., Petersen. NC (1993) A procedure for ranking efficient units in data envelopment analysis. Management Science 39 12611264. Athanassopoulos, A.D., 1997. Service quality and operating efficiency synergies for management control in the provision of financial services: evidence from Greek bank branches. European Journal of Operational Research 98, 301–314. Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science 30(9):1078–1092. Baumol, W.J., Panzar, J.C. and Willig R.D., (1982). Contestable Markets and the Theory of Industry Structure. San Diego: Harcourt Brace Jovanovich. Bell, F. and Murphy, N. (1968) Economies of scale and division of labor in commercial banking. National Banking Review, 5, 131139. Benston, G. (1965) Branch banking and economies of scale. Journal of Finance, 20, 312331. Berg, A., Forsund, F., Jansen, E., (1991). Technical efficiency in Norwegian banks: a non parametric approach to efficiency measurement. Journal of Productivity Analysis 2, 127–142. Berg, S.A., Forsund, F.R., Hjalmarsson, L., Souminen, M., (1993). Banking efficiency in the Nordic countries. Journal of Banking and Finance 17 (2/3), 371–388. Berger, N.A. and Lorreta, J.M., (1997). Inside the black box: What explains differences in the efficiencies of financial institutions? Journal of Banking & Finance 21 895947. Charnes A, Cooper WW, Rhodes E (1978) Measuring efficiency of decision making units. European Journal of Operational Research 3:429–444. Chiou, Y.H. and Chen, Y.C., (2009). The analysis of Taiwanese bank efficiency: Incorporating both external environment risk and internal risk, Economic Modelling 26, 456–463. Cooper WW, Seiford LM, Tone K (2007) Data envelopment analysis: A comprehensive text with models, applications, references and DEASolver software. Springer, New York. Cooper WW, Seiford LM, Tone K (2007) Data Envelopment Analysis: A comprehensive text with models, applications, references and DEAsolver software, Springer, New York. Derpins D, Simar L, Tulkens H. (1984). Measuring labor efficiency in post offices. In: Marchand M, Pestieau P, Tulkens H (eds) The performance of public enterprises: concepts and measurement. NorthHolland, Amstredam, pp 243–267. Drake, L., Weyman Jones, T.G., (1992). Technical and scale efficiency in UK building societies. Applied Financial Economics 2, 1–9. Dyson, R.G. and Shale, E.A. (2010). Data envelopment analysis, operational research and Uncertainty, Journal of the Operational Research Society, 61, pp. 25—34. Efron, B. (1979). Bootstrap methods: another look at the jackknife, Annals of Statistics 7:116. Farrell, M.J. (1957). The measurement of productive efficiency’, Journal of the Royal Statistical Society Series A, 120, pp. 253–281. Ferrier, G., Lovell, C., (1990). Measuring cost efficiency in banking: econometric and linear programming evidence. Journal of Econometrics 46, 229–245. Fucuyama, H., (1993). Technical and scale efficiency of Japanese commercial banks: a non parametric approach. Applied Economics 25, 1101–1112. Giokas, D.I. (2008). Assessing the efficiency in operations of a large Greek bank branch network adopting different economic behaviors, Economic Modelling 25 559–574. Greenberg, R., Nunamaker, T., (1987). A generalized multiple criteria model for control and evaluation of nonprofit organizations. Financial Accounting Management 3 (4), 331–342. Halkos, NG. and Tzeremes NG. (2010). The effect of foreign ownership on SMEs performance: An efficiency analysis perspective. Journal of Productivity Analysis. DOI 10.1007/s1112301001742. Halkos, G. and Salamouris, D. (2004). Efficiency measurement of the Greek commercial banks with the use of financial ratios: a data envelopment analysis approach. Management Accounting Research 15, 201224. Hellenic Bank Association (2007) Greek Banking System Data. Available from: http://www.hba.gr/English/Index_en.asp?Menu=5. Nunamaker, T.R., (1985). Using data envelopment analysis to measure the efficiency of nonprofit organizations: a critical evaluation. Managerial and Decision Economics 6 (1), 50–58. Pasiouras F., Gaganis C. and Zopounidis C (2006). The impact of bank regulations, supervision, market structure, and bank characteristics on individual bank ratings: A crosscountry analysis. Review of Quantitative Finance and Accounting 27(4): 403438. Pasiouras F. (2008a). Estimating the technical and scale efficiency of Greek commercial banks: The impact of credit risk, offbalance sheet activities, and international operations. Research in International Business and Finance 22(3): 301318. Pasiouras F. (2008b). International evidence on the impact of regulations and supervision on banks’ technical efficiency: an application of twostage data envelopment analysis Review of Quantitative Finance and Accounting 30(2): 187223. Schaffnit, C., Rosen, D., Paradi, J.C., (1997). Best practice analysis of bank branches: an application of DEA in a large Canadian bank. European Journal of Operational Research 2(16), 269289. Simar L, Wilson P (2008) Statistical interference in nonparametric frontier models: recent developments and perspectives. In: Fried H. Lovell CAK, Schmidt S (eds). The measurement of productive efficiency and productivity change, Oxford University Press, New York. Simar L, Wilson PW. (1998). Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models. Management Science 44: 49–61. Simar L, Wilson, P.W. (1999). Estimating and Bootstrapping Malmquist Indices. European Journal of Operational Research 115, pp.459– 471. Simar L, Wilson PW (2000). A general methodology for bootstrapping in nonparametric frontier models. Journal of Applied Statistics 27(6): 779 802. Simar L, Wilson PW (2002). Nonparametric tests of returns to scale. European Journal of Operational Research, pp.115– 132. 
URI:  http://mpra.ub.unimuenchen.de/id/eprint/23696 