IDEAS home Printed from https://ideas.repec.org/a/kap/jproda/v52y2019i1d10.1007_s11123-019-00565-6.html
   My bibliography  Save this article

A dynamic stochastic frontier model with threshold effects: U.S. bank size and efficiency

Author

Listed:
  • Pavlos Almanidis

    (International Tax Services, Transfer Pricing, Ernst & Young LLP)

  • Mustafa U. Karakaplan

    (Governors State University)

  • Levent Kutlu

    () (University of Texas Rio Grande Valley)

Abstract

Common/Single frontier methodologies that are used to analyze bank efficiency and performance can be misleading because of the homogeneous technology assumption. Using the U.S. banking data over 1984-2010, our dynamic methodology identifies a few data-driven thresholds and distinct size groups. Under common frontier assumption, the largest banks appear to be 22% less efficient on average than how they are in our model. Also, in the common frontier model, smaller banks seem to be relatively more efficient compared to their larger counterparts. Hence, common policies or regulations may not be well-balanced about controlling the banks of different sizes on the spectrum.

Suggested Citation

  • Pavlos Almanidis & Mustafa U. Karakaplan & Levent Kutlu, 2019. "A dynamic stochastic frontier model with threshold effects: U.S. bank size and efficiency," Journal of Productivity Analysis, Springer, vol. 52(1), pages 69-84, December.
  • Handle: RePEc:kap:jproda:v:52:y:2019:i:1:d:10.1007_s11123-019-00565-6
    DOI: 10.1007/s11123-019-00565-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11123-019-00565-6
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    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. Vivas, Ana Lozano, 1997. "Profit efficiency for Spanish savings banks," European Journal of Operational Research, Elsevier, vol. 98(2), pages 381-394, April.
    2. Berger, Allen N. & Hasan, Iftekhar & Zhou, Mingming, 2009. "Bank ownership and efficiency in China: What will happen in the world's largest nation?," Journal of Banking & Finance, Elsevier, vol. 33(1), pages 113-130, January.
    3. Berger, Allen N. & Mester, Loretta J., 2003. "Explaining the dramatic changes in performance of US banks: technological change, deregulation, and dynamic changes in competition," Journal of Financial Intermediation, Elsevier, vol. 12(1), pages 57-95, January.
    4. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    5. O'Donnell, Christopher J. & Coelli, Timothy J., 2005. "A Bayesian approach to imposing curvature on distance functions," Journal of Econometrics, Elsevier, vol. 126(2), pages 493-523, June.
    6. Subal Kumbhakar & Dan Wang, 2007. "Economic reforms, efficiency and productivity in Chinese banking," Journal of Regulatory Economics, Springer, vol. 32(2), pages 105-129, October.
    7. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    8. Adams, Robert M & Berger, Allen N & Sickles, Robin C, 1999. "Semiparametric Approaches to Stochastic Panel Frontiers with Applications in the Banking Industry," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 349-358, July.
    9. Dong, Yizhe & Firth, Michael & Hou, Wenxuan & Yang, Weiwei, 2016. "Evaluating the performance of Chinese commercial banks: A comparative analysis of different types of banks," European Journal of Operational Research, Elsevier, vol. 252(1), pages 280-295.
    10. Elijah Brewer & Julapa Jagtiani, 2013. "How Much Did Banks Pay to Become Too-Big-To-Fail and to Become Systemically Important?," Journal of Financial Services Research, Springer;Western Finance Association, vol. 43(1), pages 1-35, February.
    11. Wheelock, David C & Wilson, Paul W, 1995. "Explaining Bank Failures: Deposit Insurance, Regulation, and Efficiency," The Review of Economics and Statistics, MIT Press, vol. 77(4), pages 689-700, November.
    12. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    13. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
    14. 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.
    15. Kaparakis, Emmanuel I & Miller, Stephen M & Noulas, Athanasios G, 1994. "Short-Run Cost Inefficiency of Commercial Banks: A Flexible Stochastic Frontier Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 26(4), pages 875-893, November.
    16. Wheelock, David C. & Wilson, Paul W., 2001. "New evidence on returns to scale and product mix among U.S. commercial banks," Journal of Monetary Economics, Elsevier, vol. 47(3), pages 653-674, June.
    17. Berger, Allen N. & Hasan, Iftekhar & Zhou, Mingming, 2010. "The effects of focus versus diversification on bank performance: Evidence from Chinese banks," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1417-1435, July.
    18. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    19. Allen N. Berger & Timothy H. Hannan, 1998. "The Efficiency Cost Of Market Power In The Banking Industry: A Test Of The "Quiet Life" And Related Hypotheses," The Review of Economics and Statistics, MIT Press, vol. 80(3), pages 454-465, August.
    20. Kraft, Evan & Tirtiroglu, Dogan, 1998. "Bank Efficiency in Croatia: A Stochastic-Frontier Analysis," Journal of Comparative Economics, Elsevier, vol. 26(2), pages 282-300, June.
    21. Seung Ahn & Robin Sickles, 2000. "Estimation of long-run inefficiency levels: a dynamic frontier approach," Econometric Reviews, Taylor & Francis Journals, vol. 19(4), pages 461-492.
    22. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    23. McAllister, Patrick H. & McManus, Douglas, 1993. "Resolving the scale efficiency puzzle in banking," Journal of Banking & Finance, Elsevier, vol. 17(2-3), pages 389-405, April.
    24. Hulusi Inanoglu & Mahmoud A. El-Gamal, 2005. "Inefficiency and heterogeneity in Turkish banking: 1990-2000," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 641-664.
    25. Brissimis, Sophocles N. & Delis, Manthos D. & Tsionas, Efthymios G., 2010. "Technical and allocative efficiency in European banking," European Journal of Operational Research, Elsevier, vol. 204(1), pages 153-163, July.
    26. Demirgüç-Kunt, Asli & Huizinga, Harry, 2013. "Are banks too big to fail or too big to save? International evidence from equity prices and CDS spreads," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 875-894.
    27. Delis, Manthos & Iosifidi, Maria & Tsionas, Mike G, 2017. "Endogenous bank risk and efficiency," European Journal of Operational Research, Elsevier, vol. 260(1), pages 376-387.
    28. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    29. Galán, Jorge E. & Veiga, Helena & Wiper, Michael P., 2015. "Dynamic effects in inefficiency: Evidence from the Colombian banking sector," European Journal of Operational Research, Elsevier, vol. 240(2), pages 562-571.
    30. Tim Coelli & Sergio Perelman, 2000. "Technical efficiency of European railways: a distance function approach," Applied Economics, Taylor & Francis Journals, vol. 32(15), pages 1967-1976.
    31. Battese, George E. & Corra, Greg S., 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 1-11, December.
    32. Ihsan Isik, 2007. "Bank ownership and productivity developments: evidence from Turkey," Studies in Economics and Finance, Emerald Group Publishing, vol. 24(2), pages 115-139, June.
    33. Lang, Gunter & Welzel, Peter, 1999. "Mergers among German Cooperative Banks: A Panel-Based Stochastic Frontier Analysis," Small Business Economics, Springer, vol. 13(4), pages 273-286, December.
    34. Meryem Duygun & Levent Kutlu & Robin C. Sickles, 2016. "Measuring productivity and efficiency: a Kalman filter approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 155-167, December.
    35. Mukherjee, Kankana & Ray, Subhash C. & Miller, Stephen M., 2001. "Productivity growth in large US commercial banks: The initial post-deregulation experience," Journal of Banking & Finance, Elsevier, vol. 25(5), pages 913-939, May.
    36. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    37. Baltensperger, Ernst, 1980. "Alternative approaches to the theory of the banking firm," Journal of Monetary Economics, Elsevier, vol. 6(1), pages 1-37, January.
    38. Patrik T. Hultberg & M. Ishaq Nadiri & Robin C. Sickles, 2004. "Cross-country catch-up in the manufacturing sector: Impacts of heterogeneity on convergence and technology adoption," Empirical Economics, Springer, vol. 29(4), pages 753-768, December.
    39. Lin, Xiaochi & Zhang, Yi, 2009. "Bank ownership reform and bank performance in China," Journal of Banking & Finance, Elsevier, vol. 33(1), pages 20-29, January.
    40. Coelli, Tim & Perelman, Sergio, 1999. "A comparison of parametric and non-parametric distance functions: With application to European railways," European Journal of Operational Research, Elsevier, vol. 117(2), pages 326-339, September.
    41. Patrick Slovik, 2012. "Systemically Important Banks and Capital Regulation Challenges," OECD Economics Department Working Papers 916, OECD Publishing.
    42. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    43. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    44. Chang, Tzu-Pu & Hu, Jin-Li & Chou, Ray Yeutien & Sun, Lei, 2012. "The sources of bank productivity growth in China during 2002–2009: A disaggregation view," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1997-2006.
    45. 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.
    46. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    47. Tsionas, Mike G., 2017. "Microfoundations for stochastic frontiers," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1165-1170.
    48. Sickles, Robin C., 2005. "Panel estimators and the identification of firm-specific efficiency levels in parametric, semiparametric and nonparametric settings," Journal of Econometrics, Elsevier, vol. 126(2), pages 305-334, June.
    49. Pavlos Almanidis, 2013. "Accounting for heterogeneous technologies in the banking industry: a time-varying stochastic frontier model with threshold effects," Journal of Productivity Analysis, Springer, vol. 39(2), pages 191-205, April.
    50. Kutlu, Levent, 2012. "US banking efficiency, 1984–1995," Economics Letters, Elsevier, vol. 117(1), pages 53-56.
    51. Paradi, Joseph C. & Zhu, Haiyan & Edelstein, Barak, 2012. "Identifying managerial groups in a large Canadian bank branch network with a DEA approach," European Journal of Operational Research, Elsevier, vol. 219(1), pages 178-187.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Dynamic Stochastic Frontier; Bank Efficiency; Bank Heterogeneity;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

    Statistics

    Access and download statistics

    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:kap:jproda:v:52:y:2019:i:1:d:10.1007_s11123-019-00565-6. 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: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: http://www.springer.com .

    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 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.

    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.