IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v52y2020ics1062940818300366.html
   My bibliography  Save this article

Endogenous network efficiency, macroeconomy, and competition: Evidence from the Portuguese banking industry

Author

Listed:
  • Alves, André Bernardo
  • Wanke, Peter
  • Antunes, Jorge
  • Chen, Zhongfei

Abstract

Although performance analysis has become a vital part of the banking industry, research on the efficiency of Portuguese banking remains scarce and focused on discussing rankings to the detriment of unveiling its productive structure relative to its competition. This issue is of utmost importance considering the relevant transformations in the Portuguese economy over the last ten years. In this study, we developed a network productive structure comprising two paradigms (the production and intermediation approaches, respectively) to assess how market competition and other macro-economic variables impact bank efficiency and their feedback effects in Portugal. Unlike previous research, an integrated multi-layer perceptron (MLP)/hidden Markov model (HMM) was used for the first time to unveil endogeneity among banking competition, macro-economic variables, and the efficiency levels of the production and intermediation approaches in banking. The findings illustrate the pattern of interaction among these variables and verify that the production efficiency is the cornerstone of endogeneity in Portuguese banks. Policy makers will find the results helpful.

Suggested Citation

  • Alves, André Bernardo & Wanke, Peter & Antunes, Jorge & Chen, Zhongfei, 2020. "Endogenous network efficiency, macroeconomy, and competition: Evidence from the Portuguese banking industry," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
  • Handle: RePEc:eee:ecofin:v:52:y:2020:i:c:s1062940818300366
    DOI: 10.1016/j.najef.2019.101114
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940818300366
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.najef.2019.101114?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity and intermediate products: A frontier approach," Economics Letters, Elsevier, vol. 50(1), pages 65-70, January.
    2. Burkhard Raunig & Johann Scharler & Friedrich Sindermann, 2017. "Do Banks Lend Less in Uncertain Times?," Economica, London School of Economics and Political Science, vol. 84(336), pages 682-711, October.
    3. Athanasoglou, Panayiotis P. & Brissimis, Sophocles N. & Delis, Matthaios D., 2008. "Bank-specific, industry-specific and macroeconomic determinants of bank profitability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(2), pages 121-136, April.
    4. Mullen, Katharine M. & Ardia, David & Gil, David L. & Windover, Donald & Cline, James, 2011. "DEoptim: An R Package for Global Optimization by Differential Evolution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i06).
    5. João Rebelo & Victor Mendes, 2000. "Malmquist indices of productivity change in Portuguese banking: The deregulation period," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 6(3), pages 531-543, August.
    6. Sunil Kumar & Rachita Gulati, 2014. "Deregulation and Efficiency of Indian Banks," India Studies in Business and Economics, Springer, edition 127, number 978-81-322-1545-5, November.
    7. Tzeremes, Nickolaos G., 2015. "Efficiency dynamics in Indian banking: A conditional directional distance approach," European Journal of Operational Research, Elsevier, vol. 240(3), pages 807-818.
    8. Chuang-Min Chao & Ming-Miin Yu & Yun-Ting Lee & Bo Hsiao, 2017. "Measurement of Banking Performance in a Dynamic Multiactivity Network Structure: Evidence from Banks in Taiwan," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(4), pages 786-805, April.
    9. Canhoto, Ana & Dermine, Jean, 2003. "A note on banking efficiency in Portugal, New vs. Old banks," Journal of Banking & Finance, Elsevier, vol. 27(11), pages 2087-2098, November.
    10. Khan, Habib Hussain & Kutan, Ali M. & Naz, Iram & Qureshi, Fiza, 2017. "Efficiency, growth and market power in the banking industry: New approach to efficient structure hypothesis," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 531-545.
    11. Portela, Maria Conceicao A. Silva & Thanassoulis, Emmanuel, 2007. "Comparative efficiency analysis of Portuguese bank branches," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1275-1288, March.
    12. Tser-Yieth Chen, 2001. "An estimation of X-inefficiency in Taiwan's banks," Applied Financial Economics, Taylor & Francis Journals, vol. 11(3), pages 237-242.
    13. Victor Mendes & Joao Rebelo, 1999. "Productive efficiency, technological change and productivity in Portuguese banking," Applied Financial Economics, Taylor & Francis Journals, vol. 9(5), pages 513-521.
    14. Barbara Casu & Philip Molyneux, 2003. "A comparative study of efficiency in European banking," Applied Economics, Taylor & Francis Journals, vol. 35(17), pages 1865-1876.
    15. Emili Tortosa-Ausina, 2002. "Bank Cost Efficiency and Output Specification," Journal of Productivity Analysis, Springer, vol. 18(3), pages 199-222, November.
    16. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    17. Berger, Allen N. & Humphrey, David B., 1997. "Efficiency of financial institutions: International survey and directions for future research," European Journal of Operational Research, Elsevier, vol. 98(2), pages 175-212, April.
    18. Ariss, Rima Turk, 2010. "Competitive conditions in Islamic and conventional banking: A global perspective," Review of Financial Economics, Elsevier, vol. 19(3), pages 101-108, August.
    19. Luciano Amaral, 2015. "Measuring competition in Portuguese commercial banking during the Golden Age (1960-1973)," Business History, Taylor & Francis Journals, vol. 57(8), pages 1192-1218, November.
    20. Daniel Santin & Francisco Delgado & Aurelia Valino, 2004. "The measurement of technical efficiency: a neural network approach," Applied Economics, Taylor & Francis Journals, vol. 36(6), pages 627-635.
    21. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    22. Phan, Hien Thu & Anwar, Sajid & Alexander, W. Robert J. & Phan, Hanh Thi My, 2019. "Competition, efficiency and stability: An empirical study of East Asian commercial banks," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    23. repec:kap:iaecre:v:6:y:2000:i:3:p:531-543 is not listed on IDEAS
    24. Avkiran, Necmi K., 2009. "Removing the impact of environment with units-invariant efficient frontier analysis: An illustrative case study with intertemporal panel data," Omega, Elsevier, vol. 37(3), pages 535-544, June.
    25. Delis, Manthos D. & Tsionas, Efthymios G., 2009. "The joint estimation of bank-level market power and efficiency," Journal of Banking & Finance, Elsevier, vol. 33(10), pages 1842-1850, October.
    26. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    27. Lorenzo Castelli & Raffaele Pesenti & Walter Ukovich, 2010. "A classification of DEA models when the internal structure of the Decision Making Units is considered," Annals of Operations Research, Springer, vol. 173(1), pages 207-235, January.
    28. Misiunas, Nicholas & Oztekin, Asil & Chen, Yao & Chandra, Kavitha, 2016. "DEANN: A healthcare analytic methodology of data envelopment analysis and artificial neural networks for the prediction of organ recipient functional status," Omega, Elsevier, vol. 58(C), pages 46-54.
    29. Hidemichi Fujii & Shunsuke Managi & Roman Matousek & Aarti Rughoo, 2018. "Bank efficiency, productivity, and convergence in EU countries: a weighted Russell directional distance model," The European Journal of Finance, Taylor & Francis Journals, vol. 24(2), pages 135-156, January.
    30. Maria S. Basílio & Maria Clara P. Pires & José Filipe Pires Reis, 2016. "Portuguese banks’ performance: comparing efficiency with their Spanish counterparts," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 6(1), pages 27-44, April.
    31. Tan, Yong, 2016. "The impacts of risk and competition on bank profitability in China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 85-110.
    32. Drake, Leigh & Hall, Maximilian J.B. & Simper, Richard, 2006. "The impact of macroeconomic and regulatory factors on bank efficiency: A non-parametric analysis of Hong Kong's banking system," Journal of Banking & Finance, Elsevier, vol. 30(5), pages 1443-1466, May.
    33. Rolf Färe & Gerald Whittaker, 1995. "An Intermediate Input Model Of Dairy Production Using Complex Survey Data," Journal of Agricultural Economics, Wiley Blackwell, vol. 46(2), pages 201-213, May.
    34. Boaz Golany & Steven Hackman & Ury Passy, 2006. "An efficiency measurement framework for multi-stage production systems," Annals of Operations Research, Springer, vol. 145(1), pages 51-68, July.
    35. Pasiouras, Fotios, 2008. "Estimating the technical and scale efficiency of Greek commercial banks: The impact of credit risk, off-balance sheet activities, and international operations," Research in International Business and Finance, Elsevier, vol. 22(3), pages 301-318, September.
    36. Nicholas Apergis & Michael L. Polemis, 2016. "Competition and efficiency in the MENA banking region: a non-structural DEA approach," Applied Economics, Taylor & Francis Journals, vol. 48(54), pages 5276-5291, November.
    37. Avkiran, Necmi K., 2009. "Opening the black box of efficiency analysis: An illustration with UAE banks," Omega, Elsevier, vol. 37(4), pages 930-941, August.
    38. Barbara Casu & Claudia Girardone, 2004. "Financial conglomeration: efficiency, productivity and strategic drive," Applied Financial Economics, Taylor & Francis Journals, vol. 14(10), pages 687-696.
    39. Diallo, Boubacar, 2018. "Bank efficiency and industry growth during financial crises," Economic Modelling, Elsevier, vol. 68(C), pages 11-22.
    40. Barros, Fatima & Modesto, Leonor, 1999. "Portuguese banking sector: a mixed oligopoly?," International Journal of Industrial Organization, Elsevier, vol. 17(6), pages 869-886, August.
    41. Barbara Casu & Claudia Girardone, 2006. "Bank Competition, Concentration And Efficiency In The Single European Market," Manchester School, University of Manchester, vol. 74(4), pages 441-468, July.
    42. Fotios Pasiouras, 2008. "International evidence on the impact of regulations and supervision on banks’ technical efficiency: an application of two-stage data envelopment analysis," Review of Quantitative Finance and Accounting, Springer, vol. 30(2), pages 187-223, February.
    43. Sufian, Fadzlan, 2009. "Determinants of bank efficiency during unstable macroeconomic environment: Empirical evidence from Malaysia," Research in International Business and Finance, Elsevier, vol. 23(1), pages 54-77, January.
    44. Isik, Ihsan & Hassan, M. Kabir, 2002. "Technical, scale and allocative efficiencies of Turkish banking industry," Journal of Banking & Finance, Elsevier, vol. 26(4), pages 719-766, April.
    45. Thi My Phan, Hanh & Daly, Kevin & Akhter, Selim, 2016. "Bank efficiency in emerging Asian countries," Research in International Business and Finance, Elsevier, vol. 38(C), pages 517-530.
    46. Sturm, Jan-Egbert & Williams, Barry, 2004. "Foreign bank entry, deregulation and bank efficiency: Lessons from the Australian experience," Journal of Banking & Finance, Elsevier, vol. 28(7), pages 1775-1799, July.
    47. Havrylchyk, Olena, 2006. "Efficiency of the Polish banking industry: Foreign versus domestic banks," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 1975-1996, July.
    48. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    49. Degl'Innocenti, Marta & Kourtzidis, Stavros A. & Sevic, Zeljko & Tzeremes, Nickolaos G., 2017. "Investigating bank efficiency in transition economies: A window-based weight assurance region approach," Economic Modelling, Elsevier, vol. 67(C), pages 23-33.
    50. Chen, Zhongfei & Matousek, Roman & Wanke, Peter, 2018. "Chinese bank efficiency during the global financial crisis: A combined approach using satisficing DEA and Support Vector Machines☆," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 71-86.
    51. Rim Ben Selma Mokni & Houssem Rachdi, 2014. "Assessing the bank profitability in the MENA region: A comparative analysis between conventional and Islamic bank," International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing, vol. 7(3), pages 305-332, August.
    52. Barros, Carlos P. & Chen, Zhongfei & Liang, Qi Bin & Peypoch, Nicolas, 2011. "Technical efficiency in the Chinese banking sector," Economic Modelling, Elsevier, vol. 28(5), pages 2083-2089, September.
    53. A. P. Lerner, 1934. "The Concept of Monopoly and the Measurement of Monopoly Power," Review of Economic Studies, Oxford University Press, vol. 1(3), pages 157-175.
    54. Kao, Chiang, 2014. "Efficiency decomposition for general multi-stage systems in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 232(1), pages 117-124.
    55. Chen, Zhongfei & Wanke, Peter & Tsionas, Mike G., 2018. "Assessing the strategic fit of potential M&As in Chinese banking: A novel Bayesian stochastic frontier approach," Economic Modelling, Elsevier, vol. 73(C), pages 254-263.
    56. Fethi, Meryem Duygun & Pasiouras, Fotios, 2010. "Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey," European Journal of Operational Research, Elsevier, vol. 204(2), pages 189-198, July.
    57. Sealey, Calvin W, Jr & Lindley, James T, 1977. "Inputs, Outputs, and a Theory of Production and Cost at Depository Financial Institutions," Journal of Finance, American Finance Association, vol. 32(4), pages 1251-1266, September.
    58. Evans, Paul & Karras, Georgios, 1996. "Private and government consumption with liquidity constraints," Journal of International Money and Finance, Elsevier, vol. 15(2), pages 255-266, April.
    59. Maudos, Joaquin & de Guevara, Juan Fernandez, 2007. "The cost of market power in banking: Social welfare loss vs. cost inefficiency," Journal of Banking & Finance, Elsevier, vol. 31(7), pages 2103-2125, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yong Tan & Peter Wanke & Jorge Antunes & Ali Emrouznejad, 2021. "Unveiling endogeneity between competition and efficiency in Chinese banks: a two-stage network DEA and regression analysis," Annals of Operations Research, Springer, vol. 306(1), pages 131-171, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yong Tan & Peter Wanke & Jorge Antunes & Ali Emrouznejad, 2021. "Unveiling endogeneity between competition and efficiency in Chinese banks: a two-stage network DEA and regression analysis," Annals of Operations Research, Springer, vol. 306(1), pages 131-171, November.
    2. Fethi, Meryem Duygun & Pasiouras, Fotios, 2010. "Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey," European Journal of Operational Research, Elsevier, vol. 204(2), pages 189-198, July.
    3. Fotios Pasiouras & Aggeliki Liadaki & Constantin Zopounidis, 2008. "Bank efficiency and share performance: evidence from Greece," Applied Financial Economics, Taylor & Francis Journals, vol. 18(14), pages 1121-1130.
    4. Wanke, Peter & Tsionas, Mike G. & Chen, Zhongfei & Moreira Antunes, Jorge Junio, 2020. "Dynamic network DEA and SFA models for accounting and financial indicators with an analysis of super-efficiency in stochastic frontiers: An efficiency comparison in OECD banking," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 456-468.
    5. Sailesh Tanna & Fotios Pasiouras & Matthias Nnadi, 2011. "The Effect of Board Size and Composition on the Efficiency of UK Banks," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 18(3), pages 441-462, November.
    6. Alexandre Momparler & Carlos Lassala & Domingo Ribeiro, 2013. "Efficiency in banking services: a comparative analysis of Internet-primary and branching banks in the US," Service Business, Springer;Pan-Pacific Business Association, vol. 7(4), pages 641-663, December.
    7. Pasiouras, Fotios, 2008. "Estimating the technical and scale efficiency of Greek commercial banks: The impact of credit risk, off-balance sheet activities, and international operations," Research in International Business and Finance, Elsevier, vol. 22(3), pages 301-318, September.
    8. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    9. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    10. Johann Burgstaller, 2020. "Retail‐bank efficiency: Nonstandard goals and environmental determinants," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 91(2), pages 269-301, June.
    11. Hall, Maximilian J.B. & Kenjegalieva, Karligash A. & Simper, Richard, 2012. "Environmental factors affecting Hong Kong banking: A post-Asian financial crisis efficiency analysis," Global Finance Journal, Elsevier, vol. 23(3), pages 184-201.
    12. Christopoulos, Apostolos G. & Dokas, Ioannis G. & Katsimardou, Sofia & Spyromitros, Eleftherios, 2020. "Assessing banking sectors’ efficiency of financially troubled Eurozone countries," Research in International Business and Finance, Elsevier, vol. 52(C).
    13. Francesco Aiello & Graziella Bonanno, 2018. "On The Sources Of Heterogeneity In Banking Efficiency Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 32(1), pages 194-225, February.
    14. Serhat Yüksel & Shahriyar Mukhtarov & Elvin Mammadov, 2016. "Comparing the Efficiency of Turkish and Azerbaijani Banks: An Application with Data Envelopment Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 6(3), pages 1059-1067.
    15. Natalya Zelenyuk & Valentin Zelenyuk, 2015. "Productivity Drivers of Efficiency in Banking: Importance of Model Specifications," CEPA Working Papers Series WP082015, School of Economics, University of Queensland, Australia.
    16. Natalya Zelenyuk & Valentin Zelenyuk, 2014. "Regional and Ownership Drivers of Bank Efficiency," CEPA Working Papers Series WP112014, School of Economics, University of Queensland, Australia.
    17. Sepideh Kaffash & Marianna Marra, 2017. "Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds," Annals of Operations Research, Springer, vol. 253(1), pages 307-344, June.
    18. Konara, Palitha & Tan, Yong & Johnes, Jill, 2019. "FDI and heterogeneity in bank efficiency: Evidence from emerging markets," Research in International Business and Finance, Elsevier, vol. 49(C), pages 100-113.
    19. Zha, Yong & Liang, Nannan & Wu, Maoguo & Bian, Yiwen, 2016. "Efficiency evaluation of banks in China: A dynamic two-stage slacks-based measure approach," Omega, Elsevier, vol. 60(C), pages 60-72.
    20. Avkiran, Necmi K., 2011. "Association of DEA super-efficiency estimates with financial ratios: Investigating the case for Chinese banks," Omega, Elsevier, vol. 39(3), pages 323-334, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:52:y:2020:i:c:s1062940818300366. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.