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Pre-evaluating technical efficiency gains from possible mergers and acquisitions: evidence from Japanese regional banks

Review of Quantitative Finance and Accounting volume 46, pages 47–77 (2016)Cite this article

Abstract

This study focuses on bank mergers and acquisitions (M&As) and applies a DEA based procedure that allows us to pre-evaluate technical efficiency gains from possible M&As in the Japanese regional banking sector. This approach provides a strategic tool for policy-makers to pre-evaluate possible M&As decisions based on performance criteria that are measured in terms of technical efficiency gains. The results clearly show that possible M&As formed by the smaller banks performed better compared with the possible M&As formed by the larger banks. Moreover, our findings imply that small regional banks will have possible efficiency gains when they merge with neighboring banks, whereas larger banks appear to have efficiency gains from merging with distant banks.

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Notes

  1. We consider here only the VRS case; however the constant returns to scale (CRS) case can be obtained by dropping the constraint in (3) requiring \(\gamma s\)to sum to one (Charnes et al. 1978).

  2. The bootstrap approach is the only practical method for estimating confidence intervals, for correcting the bias of DEA estimator, for hypothesis testing and for sub-sampling techniques (Simar and Wilson 2011). However, Dyson and Shale (2010) suggest that the homogeneity assumption of efficiency across the input output space could be unrealistic.

  3. For a DEA application using bootstrap techniques investigating banking efficiency and stock market performance see Hadad et al. (2011).

  4. Since we are not using input (output) prices we assume that the inputs and outputs used across the banks are homogeneous in nature and generally the homogeneity assumption between banks holds (Dyson et al. 2001). However, when prices of inputs (outputs) are used then the homogeneity assumption can be violated and alternative DEA formulations must be applied (Sahoo and Tone 2013).

  5. For the case of Taiwanese banks, Yu and Van Luu (2003) suggest that if the banks want to obtain efficiency gains from scale economies, they should choose the subadditivity expansion path and therefore they need to merge with other banks, rather than to expand their network by opening more branches.

  6. Since we are using panel data for the period 2000–2008, we define all the possible PMAs based on the findings of the year 2000 (base year in our case). The number of possible pairs can be found as: \(n!/\left( {n - k} \right)!k!\).

  7. In such a way we are able to compare the PMA under examination to the other incumbents (banks) competing in the same market (Evanoff and Örs 2008) but at the same time with the banks that form the specific PMA, obtain therefore robust results.

  8. However, it must be mentioned that there is still a weakness regarding the application of a nonparametric regression in a second stage analysis. That is the assumption of a 'separability' condition between the external variable (the distance in our case) and the estimated efficiencies (Simar and Wilson 2011).

  9. We will explain later how we calculate regional distances between the merged entities.

  10. See Barros et al. (2012) for a discussion on the bank production process.

  11. For the calculation of the DEA estimates we have used the software package FEAR (Wilson 2008).

  12. We also assume that an PMA can only occur between two banks. Our procedure can also be applied for an PMA formed from more than two banks but in real life the merger of three banks in the same period is not a usual phenomenon.

  13. Due to the enormous quantity of results obtained it is not possible to present them all in this paper. All analytical results obtained are available upon request.

  14. In our case the DTEG limit is objective and is set to zero since according to Cooper et al. (2007) only a DTEG value >0 indicates efficiency gains.

  15. According to Bivand et al. (2008, p. 237) areal entities are referred to polygon entities with defined boundaries. In our case these boundaries are not defined by the researcher but instead they are administrative boundaries.

  16. In order to compute the local linear estimator we have used the ‘np’ software package introduced by Hayfield and Racine (2008).

References

  • Aggarwal R (1994) Characteristics of Japanese finance: a review and introduction. Glob Financ J 5:141–167

    Article  Google Scholar 

  • Aggarwal R, Dow SM (2012) Dividends and strength of Japanese business group affiliation. J Econ Bus 64:214–230

    Article  Google Scholar 

  • Aggarwal R, Akhigbe A, McNulty J (2006) Are differences in acquiring bank profit efficiency priced in financial markets? J Financ Serv Res 30:265–286

    Article  Google Scholar 

  • Albert J (2009) Bayesian computation with R. Springer, NewYork

    Book  Google Scholar 

  • Al-Khasawneh JA (2013) Pairwise X-efficiency combinations of merging banks: analysis of the fifth merger wave. Rev Quant Financ Acc 41:1–28

    Article  Google Scholar 

  • Altunbas Y, Marques D (2008) Mergers and acquisitions and bank performance in Europe: the role of strategic similarities. J Econ Bus 60:204–222

    Article  Google Scholar 

  • Amel D, Barnes C, Panetta F, Salleo C (2004) Consolidation and efficiency in the financial sector: a review of the international evidence. J Bank Financ 28:2493–2519

    Article  Google Scholar 

  • Assaf A, Barros C, Matousek R (2011) Productivity growth and efficiency of Shinkin banks: evidence from bootstrap and Bayesian approaches. J Bank Financ 35:331–342

    Article  Google Scholar 

  • Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manage Sci 30:1078–1092

    Article  Google Scholar 

  • Barros CP, Managi S, Matousek R (2012) The technical efficiency of the Japanese banks: non-radial directional performance measurement with undesirable output. Omega 40:1–8

    Article  Google Scholar 

  • Beccalli E, Frantz P (2009) M&A operations and performance in banking. J Financ Serv Res 36:203–226

    Article  Google Scholar 

  • Berger AN, Humphrey DB (1997) Efficiency of financial institutions: international survey and directions for future research. Eur J Oper Res 98:175–212

    Article  Google Scholar 

  • Bivand RS, Pebesma EJ, Gómez-Rubio V (2008) Applied spatial data analysis with R. Springer Science, New York

    Google Scholar 

  • Boussofiane A, Dyson RG, Thanassoulis E (1991) Applied data envelopment analysis. Eur J Oper Res 52:1–15

    Article  Google Scholar 

  • Caballero RJ, Hoshi T, Kashyap AK (2008) Zombie lending and depressed restructuring in Japan. Am Econ Rev 98:1943–1977

    Article  Google Scholar 

  • Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2:429–444

    Article  Google Scholar 

  • Coelli TJ, Rap DSP, O’Donnell CJ, Battese GE (2005) An introduction to efficiency and productivity analysis, 2nd edn. Springer, NewYork

    Google Scholar 

  • Cooper WW, Seiford LM, Tone K (2007) Data envelopment analysis: a comprehensive text with models, applications, references and DEA-Solver software. Springer, New York

    Google Scholar 

  • Craig BR, Dinger V (2009) Bank mergers and the dynamics of deposit interest rates. J Financ Serv Res 36:111–133

    Article  Google Scholar 

  • Debreu G (1951) The coefficient of resource utilization. Econometrics 19:273–292

    Article  Google Scholar 

  • Degryse H, Ongena S (2004) The impact of technology and regulation on the geographical scope of banking. Oxf Rev Econ Policy 20:571–590

    Article  Google Scholar 

  • DeYoung R, Evanoff DD, Molyneux P (2009) Mergers and acquisitions of financial institutions: a review of the post-2000 literature. J Financ Serv Res 36:87–110

    Article  Google Scholar 

  • Diaz B, Olalla MG, Azofra SS (2004) Bank acquisitions and performance: evidence from a panel of European credit entities. J Econ Bus 56:377–404

    Article  Google Scholar 

  • Drake L, Hall MJB, Simper R (2009) Bank modeling methodologies: a comparative nonparametricanalysis of efficiency in the Japanese banking sector. J Int Financ Mark Inst Money 19:1–15

    Article  Google Scholar 

  • Dyson RG, Shale EA (2010) Data envelopment analysis, operational research and uncertainty. J Oper Res Soc 61:25–34

    Article  Google Scholar 

  • Dyson RG, Allen R, Camanho AS, Podinovski VV, Sarrico CS, Shale EA (2001) Pitfalls and protocols in DEA. Eur J Oper Res 132:245–259

    Article  Google Scholar 

  • Evanoff DD, Örs E (2008) The competitive dynamics of geographic deregulation in banking: implications for productive efficiency. J Money Credit Bank 40:897–928

    Article  Google Scholar 

  • Färe R (1986) Addition and efficiency. Q J Econ 4:861–865

    Article  Google Scholar 

  • Färe R, Grosskopf S, Lovell CAK (1994) Production frontiers. Cambridge University Press, Cambridge

    Google Scholar 

  • Färe R, Fukuyama H, Weber WL (2010) A Mergers and acquisitions index in data envelopment analysis: an application to Japanese Shinkin banks in Kyushu. Int J Inf Syst Soc Change 1:1–18

    Article  Google Scholar 

  • Farrell MJ (1957) The measurement of productive efficiency. J R Stat Soc Ser A 120:253–281

    Article  Google Scholar 

  • Fukao M (2002) Financial sector profitability and double-gearing, NBER, Working paper 9368

  • Fukuyama H, Weber WL (2010) A slacks-based inefficiency measure for a two-stage system with bad outputs. Omega 38:398–409

    Article  Google Scholar 

  • Goto N, Uchida K (2012) How do banks resolve firms’ financial distress? Evidence from Japan. Rev Quant Financ Acc 38:455–478

    Article  Google Scholar 

  • Hadad MD, Hall MJB, Kenjegalieva KA, Santoso W, Simper R (2011) Banking efficiency and stock market performance: an analysis of listed Indonesian banks. Rev Quant Financ Acc 37:1–20

    Article  Google Scholar 

  • Halkos GE, Tzeremes NG (2013) Estimating the degree of operating efficiency gains from a potential bank merger and acquisition: a DEA bootstrapped approach. J Bank Financ 37:1658–1668

    Article  Google Scholar 

  • Hall P, Racine JS, Li Q (2004) Cross-validation and the estimation of conditional probability densities. J Am Stat Assoc 99:1015–1026

    Article  Google Scholar 

  • Harada K, Ito T (2011) Did mergers help Japanese mega-banks avoid failure? Analysis of the distance to default of banks. J Jpn Int Econ 25:1–22

    Article  Google Scholar 

  • Hayfield T, Racine JS (2008) Nonparametric econometrics: the np package. J Stat Softw 27. http://www.jstatsoft.org/v27/i05

  • Hirota S, Tsutsui Y (1999) Do banks diversify portfolio risk? A test of the risk–cost hypothesis. Jpn World Econ 11:29–39

    Article  Google Scholar 

  • Hoshi T (2006) Economics of the living dead. Jpn Econ Rev 57:30–49

  • Hoshino Y, Turnbull SJ (2012) Further study on the performance of mergers among credit associations in Japan. Rev Pac Basin Financ Mark Policies 5:395–416

    Article  Google Scholar 

  • Hosono K, Sakai K, Tsuru K (2007) Consolidation of banks in Japan: causes and consequences. NBER Working Paper No. W13399

  • Huizinga HP, Nelissen JHM, Vander Vennet R (2001) Efficiency effects of bank mergers and acquisitions in Europe. Tinbergen Institute Discussion Paper 088/3. Rotterdam

  • Hwang SN, Chang TY (2003) Using data envelopment analysis to measure hotel managerial efficiency change in Taiwan. Tour Manag 24:357–369

    Article  Google Scholar 

  • Illueca M, Pastor JM, Tortosa-Ausina E (2009) The effects of geographic expansion on the productivity of Spanish savings banks. J Prod Anal 32:119–143

    Article  Google Scholar 

  • Kashyap AK (1999) What should regulators do about merger policy? J Bank Financ 23:623–627

  • Kneip A, Park B, Simar L (1998) A note on the convergence of nonparametric DEA efficiency measures. Econ Theory 14:783–793

    Article  Google Scholar 

  • Kneip A, Simar L, Wilson PW (2008) Asymptotics and consistent bootstraps for DEA estimators in non-parametric frontier models. Econ Theory 24:1663–1697

    Article  Google Scholar 

  • Kneip A, Simar L, Wilson PW (2011) A computationally efficient, consistent bootstrap for inference with non-parametric DEA estimators. Comput Econ 38:483–515

    Article  Google Scholar 

  • Koopmans TC (1951) An analysis of production as an efficient combination of activities. In: Koopmans TC (ed) Activity analysis of production and allocation. Wiley, New York, pp 33–97

    Google Scholar 

  • Lin D, Barth J, Jahera J, Yost K (2013) Cross-border bank mergers and acquisitions: what factors pull and push banks together? Rev Pac Basin Financ Mark Policies 4:1–23

    Google Scholar 

  • Liu H, Wilson JOS (2013) Competition and risk in Japanese banking. Eur J Financ 19:1–18

    Article  Google Scholar 

  • Matutes C, Padilla AJ (1994) Shared ATM networks and banking competition. Eur Econ Rev 38:1113–1138

    Article  Google Scholar 

  • Montgomery H, Shimizutani S (2009) The effectiveness of bank recapitalization policies in Japan. Japan World Econ 21:1–25

    Article  Google Scholar 

  • Morita H (2003) Analysis of economies of scope by data envelopment analysis: comparison of efficient frontiers. Int Trans Oper Res 10:393–402

    Article  Google Scholar 

  • Nadaraya EA (1965) On nonparametric estimates of density functions and regression curves. Theory Appl Prob 10:186–190

    Article  Google Scholar 

  • Novo-Peteiro JA (2009) Bank mergers in spatially differentiated markets. J Econ Bus 61:90–96

    Article  Google Scholar 

  • Okada T (2007) Consequences of bank mergers, Ginko gappei no kouka, in Japanese, mimeo

  • Onji K, Vera D, Corbett J (2012) Capital injection, restructuring targets and personnel management: the case of Japanese regional banks. J Jpn Int Econ 26:495–517

    Article  Google Scholar 

  • Peek J, Rosengren ES (2005) Unnatural selection: perverse incentives and the misallocation of credit in Japan. Am Econ Rev 95:1144–1166

    Article  Google Scholar 

  • Prior D (1996) Technical efficiency and scope economies in hospitals. Appl Econ 28:1295–1301

    Article  Google Scholar 

  • Racine JS (2008) Nonparametric econometrics. Found Trend Econ 3:1–88

    Article  Google Scholar 

  • Sahoo BK, Tone K (2013) Non-parametric measurement of economies of scale and scope in non-competitive environment with price uncertainty. Omega 41:97–111

    Article  Google Scholar 

  • Sealey C, Lindley J (1977) Inputs, outputs, and a theory of production and cost at depository financial institutions. J Financ 32:1251–1266

    Article  Google Scholar 

  • Silverman BW (1986) Density estimation for statistics and data analysis. Chapman and Hall, London

    Book  Google Scholar 

  • Simar L, Wilson PW (1998) Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models. Manage Sci 44:49–61

    Article  Google Scholar 

  • Simar L, Wilson PW (1999a) Of course we can bootstrap DEA scores. But does it mean anything? Logic trumps wishful thinking. J Prod Anal 11:93–97

    Article  Google Scholar 

  • Simar L, Wilson PW (1999b) Some problems with the Ferrier Hirschberg bootstrap idea. J Prod Anal 11:67–80

    Article  Google Scholar 

  • Simar L, Wilson PW (2000a) A general methodology for bootstrapping in non-parametric frontier models. J Appl Stat 27:779–802

    Article  Google Scholar 

  • Simar L, Wilson PW (2000b) Statistical inference in nonparametric frontier models: the state of the art. J Prod Anal 13:49–78

    Article  Google Scholar 

  • Simar L, Wilson PW (2007) Estimation and inference in two-stage, semi-parametric models of productive processes. J Econ 136:31–64

    Article  Google Scholar 

  • Simar L, Wilson PW (2008) Statistical inference in nonparametric frontier models: recent developments and perspectives. In: Fried H, Lovell CAK, Schmidt S (eds) The measurement of productive efficiency, 2nd edn. Oxford University Press, Oxford, pp 421–521 (Chapter 4)

    Google Scholar 

  • Simar L, Wilson PW (2011) Two-stage DEA: caveat emptor. J Prod Anal 36:205–218

    Article  Google Scholar 

  • Simar L, Vanhems A, Wilson PW (2012) Statistical inference for DEA estimators of directional distances. Eur J Oper Res 220:853–864

    Article  Google Scholar 

  • Slama MB, Saidane D, Fedhila H (2012) How to identify targets in the M&A banking operations? Case of cross-border strategies in Europe by line of activity. Rev Quant Financ Acc 38:209–240

    Article  Google Scholar 

  • Watson GS (1964) Smooth regression analysis. Sankhya Ser A 26:359–372

    Google Scholar 

  • Wheelock DC, Wilson PW (2010) Are credit unions too small? Working Paper, Federal Reserve Bank of St Louis

  • Wilson PW (2008) FEAR 1.0: a software package for frontier efficiency analysis with R. Socio Econ Plan Sci 42:247–254

    Article  Google Scholar 

  • Yamori N, Harimaya K, Kondo K (2003) Are banks affiliated with bank holding companies more efficient than independent banks? The recent experience regarding Japanese Regional BHCs. Asia-Pac Financ Mark 10:359–376

    Article  Google Scholar 

  • Yu P, Van Luu B (2003) Banking mergers: the impact of financial liberalization on the Taiwanese banking industry. Rev Quant Financ Acc 20:385–413

    Article  Google Scholar 

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Acknowledgments

We would like to thank the Editor (Professor Cheng-Few Lee) and three anonymous reviewers for the comments provided in relation to an earlier version of our paper. Any remaining errors are solely the authors’ responsibility.

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Authors and Affiliations

  1. Laboratory of Operations Research, Department of Economics, University of Thessaly, Korai 43, 38333, Vólos, Greece

    George E. Halkos & Nickolaos G. Tzeremes

  2. Kent Business School, Kent University, Canterbury, Kent, CT2 7PE, UK

    Roman Matousek

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  1. George E. Halkos
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  2. Roman Matousek
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Correspondence to Roman Matousek.

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Halkos, G.E., Matousek, R. & Tzeremes, N.G. Pre-evaluating technical efficiency gains from possible mergers and acquisitions: evidence from Japanese regional banks. Rev Quant Finan Acc 46, 47–77 (2016). https://doi.org/10.1007/s11156-014-0461-5

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  • DOI: https://doi.org/10.1007/s11156-014-0461-5

Keywords

  • Banks efficiency
  • Data Envelopment Analysis, Japan
  • Mergers and acquisitions

JEL Classification

  • C14
  • C60
  • G20
  • G34