(Translated by https://www.hiragana.jp/)
Returns to scale at large banks in the US: A random coefficient stochastic frontier approach
IDEAS home Printed from https://ideas.repec.org/a/eee/jbfina/v39y2014icp135-145.html
   My bibliography  Save this article

Returns to scale at large banks in the US: A random coefficient stochastic frontier approach

Author

Listed:
  • Feng, Guohua
  • Zhang, Xiaohui

Abstract

This paper investigates the returns to scale of large banks in the US over the period 1997–2010. This investigation is performed by estimating a random coefficient stochastic distance frontier model in the spirit of Tsionas (2002) and Greene (2005, 2008). The primary advantage of this model is that its coefficients can vary across banks, thereby allowing for unobserved technology heterogeneity among large banks in the US We find that failure to consider unobserved technology heterogeneity results in a misleading ranking of banks and mismeasured returns to scale. Our results show that the majority of large banks in the US exhibit constant returns to scale. In addition, our results suggest that banks of the same size can have different levels of returns to scale and there is no clear pattern among large banks in the US concerning the relationship between asset size and returns to scale, due to the presence of technology heterogeneity.

Suggested Citation

  • Feng, Guohua & Zhang, Xiaohui, 2014. "Returns to scale at large banks in the US: A random coefficient stochastic frontier approach," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 135-145.
    • Handle: RePEc:eee:jbfina:v:39:y:2014:i:c:p:135-145
    DOI: 10.1016/j.jbankfin.2013.10.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378426613004135
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbankfin.2013.10.012?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. Canales, Rodrigo & Nanda, Ramana, 2012. "A darker side to decentralized banks: Market power and credit rationing in SME lending," Journal of Financial Economics, Elsevier, vol. 105(2), pages 353-366.
    2. 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.
    3. 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.
    4. Jalal Akhavein & W. Scott Frame & Lawrence J. White, 2005. "The Diffusion of Financial Innovations: An Examination of the Adoption of Small Business Credit Scoring by Large Banking Organizations," The Journal of Business, University of Chicago Press, vol. 78(2), pages 577-596, March.
    5. Feng, Guohua & Serletis, Apostolos, 2010. "Efficiency, technical change, and returns to scale in large US banks: Panel data evidence from an output distance function satisfying theoretical regularity," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 127-138, January.
    6. Garth Saloner & Andrea Shepard, 1995. "Adoption of Technologies with Network Effects: An Empirical Examination of the Adoption of Teller Machines," RAND Journal of Economics, The RAND Corporation, vol. 26(3), pages 479-501, Autumn.
    7. Berger, Allen N. & Miller, Nathan H. & Petersen, Mitchell A. & Rajan, Raghuram G. & Stein, Jeremy C., 2005. "Does function follow organizational form? Evidence from the lending practices of large and small banks," Journal of Financial Economics, Elsevier, vol. 76(2), pages 237-269, May.
    8. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    9. Zhang, Xibin & Brooks, Robert D. & King, Maxwell L., 2009. "A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation," Journal of Econometrics, Elsevier, vol. 153(1), pages 21-32, November.
    10. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
    11. Daniel, Donnie L & Longbrake, William A & Murphy, Neil B, 1973. "The Effect of Technology on Bank Economies of Scale for Demand Deposits," Journal of Finance, American Finance Association, vol. 28(1), pages 131-146, March.
    12. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    13. Berger, Allen N. & Hunter, William C. & Timme, Stephen G., 1993. "The efficiency of financial institutions: A review and preview of research past, present and future," Journal of Banking & Finance, Elsevier, vol. 17(2-3), pages 221-249, April.
    14. Berger, Allen N. & Demsetz, Rebecca S. & Strahan, Philip E., 1999. "The consolidation of the financial services industry: Causes, consequences, and implications for the future," Journal of Banking & Finance, Elsevier, vol. 23(2-4), pages 135-194, February.
    15. Luis Orea, 2002. "Parametric Decomposition of a Generalized Malmquist Productivity Index," Journal of Productivity Analysis, Springer, vol. 18(1), pages 5-22, July.
    16. Diewert, W. E., 1973. "Functional forms for profit and transformation functions," Journal of Economic Theory, Elsevier, vol. 6(3), pages 284-316, June.
    17. Rossi, Clifford V., 1998. "Mortgage Banking Cost Structure: Resolving an Enigma," Journal of Economics and Business, Elsevier, vol. 50(2), pages 219-234, March.
    18. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    19. Murray, John D & White, Robert W, 1983. "Economies of Scale and Economies of Scope in Multiproduct Financial Institutions: A Study of British Columbia Credit Unions," Journal of Finance, American Finance Association, vol. 38(3), pages 887-902, June.
    20. Cole, Rebel A. & Goldberg, Lawrence G. & White, Lawrence J., 2004. "Cookie Cutter vs. Character: The Micro Structure of Small Business Lending by Large and Small Banks," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(2), pages 227-251, June.
    21. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
    22. W. Diewert & Kevin Fox, 2010. "Malmquist and Törnqvist productivity indexes: returns to scale and technical progress with imperfect competition," Journal of Economics, Springer, vol. 101(1), pages 73-95, September.
    23. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    24. Feng, Guohua & Zhang, Xiaohui, 2012. "Productivity and efficiency at large and community banks in the US: A Bayesian true random effects stochastic distance frontier analysis," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1883-1895.
    25. 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.
    26. 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.
    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. Hien Thu Pham & Shino Takayama, 2017. "Revisiting the “Missing Middle”: Productivity Analysis," Discussion Papers Series 580, School of Economics, University of Queensland, Australia.
    2. Hien Thu Pham & Nhan Buu Phan & Shino Takayama, 2020. "Productivity, Efficiency and Firm Size Distribution: Evidence from Vietnam," Discussion Papers Series 617, School of Economics, University of Queensland, Australia.
    3. Ferrara, Giancarlo & Kounetas, Konstantinos E., 2024. "US banks efficiency after global financial crisis: Transient and persistent decomposition," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    4. Robert McKeown, 2017. "Where Are The Economies Of Scale In Canadian Banking?," Working Paper 1380, Economics Department, Queen's University.
    5. Guohua Feng & Chuan Wang & Apostolos Serletis, 2018. "Shadow prices of $$\hbox {CO}_{2}$$ CO 2 emissions at US electric utilities: a random-coefficient, random-directional-vector directional output distance function approach," Empirical Economics, Springer, vol. 54(1), pages 231-258, February.
    6. Dia, Enzo & Jiang, Lunan & Menna, Lorenzo & Zhang, Lin, 2023. "Interest margins, lending rates and bank productivity among Chinese provinces," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 104-127.
    7. Spierdijka, Laura & Zaourasa, Michalis, 2018. "Measuring banks’ market power in the presence of economies of scale: A scale-corrected Lerner index," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 40-48.
    8. Guohua Feng & Bin Peng & Xiaohui Zhang, 2017. "Productivity and efficiency at bank holding companies in the U.S.: a time-varying heterogeneity approach," Journal of Productivity Analysis, Springer, vol. 48(2), pages 179-192, December.
    9. Cortés-García, J. Salvador & Pérez-Rodríguez, Jorge V., 2024. "Heterogeneity and time-varying efficiency in the Ecuadorian banking sector. An output distance stochastic frontier approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 93(C), pages 164-175.
    10. Mamatzakis, Emmanuel & Zhang, Xiaoxiang & Wang, Chaoke, 2016. "Invisible hand discipline from informed trading: Does market discipline from trading affect bank capital structure?," MPRA Paper 76215, University Library of Munich, Germany.
    11. Mamatzakis, Emmanuel & matousek, roman & vu, anh, 2019. "The interplay between problem loans and Japanese bank productivity," MPRA Paper 92960, University Library of Munich, Germany.
    12. Seyed Mehdian & Rasoul Rezvanian & Ovidiu Stoica, 2019. "The Effect Of The 2008 Global Financial Crisis On The Efficiency Of Large U.S. Commercial Banks," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 24, pages 11-27, December.
    13. Cheng, Ming-Yen & Wang, Shouxia & Xia, Lucy & Zhang, Xibin, 2024. "Testing specification of distribution in stochastic frontier analysis," Journal of Econometrics, Elsevier, vol. 239(2).
    14. Robert McKeown, 2017. "Costs, Size And Returns To Scale Among Canadian And U.s. Commercial Banks," Working Paper 1382, Economics Department, Queen's University.
    15. Guohua Feng & Todd Jewell, 2021. "Productivity and efficiency at english football clubs: a random coefficient approach," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(5), pages 571-604, November.
    16. Hien Thu Pham & Shino Takayama, 2017. "Firm Size Distribution, Production Efficiency, and Returns to Scale: A Stochastic Frontier Approach," Discussion Papers Series 581, School of Economics, University of Queensland, Australia.
    17. Dia, Enzo & VanHoose, David, 2019. "Real resource utilization in banking, economies of scope, and the relationship between retail loans and deposits," Economics Letters, Elsevier, vol. 177(C), pages 39-42.
    18. Galán, Jorge & Ramos, Sofía B. & Veiga, Helena, 2015. "An analysis of the dynamics of efficiency of mutual funds," DES - Working Papers. Statistics and Econometrics. WS ws1517, Universidad Carlos III de Madrid. Departamento de Estadística.
    19. Anthony J. Glass & Karligash Kenjegalieva, 2024. "Returns to scale, spillovers and persistence: A network perspective of U.S. bank size," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 2049-2076, April.
    20. Kien C. Tran & Mike G. Tsionas & Emmanuel Mamatzakis, 2020. "Why fully efficient banks matter? A nonparametric stochastic frontier approach in the presence of fully efficient banks," Empirical Economics, Springer, vol. 58(6), pages 2733-2760, June.
    21. Ji Wu & Shirong Zhao, 2024. "Returns to scale in cost, revenue, and profit for European banks: New results from nonparametric local linear methods," The Financial Review, Eastern Finance Association, vol. 59(2), pages 487-517, May.

    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. Guohua Feng & Bin Peng & Xiaohui Zhang, 2017. "Productivity and efficiency at bank holding companies in the U.S.: a time-varying heterogeneity approach," Journal of Productivity Analysis, Springer, vol. 48(2), pages 179-192, December.
    2. Feng, Guohua & Zhang, Xiaohui, 2012. "Productivity and efficiency at large and community banks in the US: A Bayesian true random effects stochastic distance frontier analysis," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1883-1895.
    3. Guohua Feng & Chuan Wang & Xibin Zhang, 2019. "Estimation of inefficiency in stochastic frontier models: a Bayesian kernel approach," Journal of Productivity Analysis, Springer, vol. 51(1), pages 1-19, February.
    4. Tai-Hsin Huang & Yi-Huang Chiu & Chih-Ying Mao, 2021. "Imposing Regularity Conditions to Measure Banks’ Productivity Changes in Taiwan Using a Stochastic Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(2), pages 273-303, June.
    5. Guohua Feng & Todd Jewell, 2021. "Productivity and efficiency at english football clubs: a random coefficient approach," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(5), pages 571-604, November.
    6. Guohua Feng & Chuan Wang, 2021. "Determinants of profitability of community banks in the USA: a cost-frontier-based decomposition approach," Empirical Economics, Springer, vol. 60(6), pages 2969-2992, June.
    7. Feng, Guohua & Serletis, Apostolos, 2010. "Efficiency, technical change, and returns to scale in large US banks: Panel data evidence from an output distance function satisfying theoretical regularity," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 127-138, January.
    8. Diego Restrepo-Tobón & Subal Kumbhakar & Kai Sun, 2015. "Obelix vs. Asterix: Size of US commercial banks and its regulatory challenge," Journal of Regulatory Economics, Springer, vol. 48(2), pages 125-168, October.
    9. Athanasoglou, Panayiotis P. & Georgiou, Evangelia A. & Staikouras, Christos C., 2009. "Assessing output and productivity growth in the banking industry," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(4), pages 1317-1340, November.
    10. Allen N. Berger & Astrid A. Dick & Lawrence G. Goldberg & Lawrence J. White, 2007. "Competition from Large, Multimarket Firms and the Performance of Small, Single‐Market Firms: Evidence from the Banking Industry," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(2‐3), pages 331-368, March.
    11. Kilian Huber, 2021. "Are Bigger Banks Better? Firm-Level Evidence from Germany," Journal of Political Economy, University of Chicago Press, vol. 129(7), pages 2023-2066.
    12. Robert DeYoung & William Hunter & Gregory Udell, 2004. "The Past, Present, and Probable Future for Community Banks," Journal of Financial Services Research, Springer;Western Finance Association, vol. 25(2), pages 85-133, April.
    13. Sarmiento, Miguel & Galán, Jorge E., 2014. "Heterogeneous effects of risk-taking on bank efficiency : a stochastic frontier model with random coefficients," DES - Working Papers. Statistics and Econometrics. WS ws142013, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. Emir Malikov & Subal C. Kumbhakar & Mike G. Tsionas, 2016. "A Cost System Approach to the Stochastic Directional Technology Distance Function with Undesirable Outputs: The Case of us Banks in 2001–2010," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1407-1429, November.
    15. 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.
    16. Feng, Guohua & Wang, Chuan, 2018. "Why European banks are less profitable than U.S. banks: A decomposition approach," Journal of Banking & Finance, Elsevier, vol. 90(C), pages 1-16.
    17. Sufian, Fadzlan, 2011. "Banks total factor productivity change in a developing economy: Does ownership and origins matter?," Journal of Asian Economics, Elsevier, vol. 22(1), pages 84-98, February.
    18. Wilson, John O.S. & Casu, Barbara & Girardone, Claudia & Molyneux, Philip, 2010. "Emerging themes in banking: Recent literature and directions for future research," The British Accounting Review, Elsevier, vol. 42(3), pages 153-169.
    19. DeYoung, Robert & Glennon, Dennis & Nigro, Peter, 2008. "Borrower-lender distance, credit scoring, and loan performance: Evidence from informational-opaque small business borrowers," Journal of Financial Intermediation, Elsevier, vol. 17(1), pages 113-143, January.
    20. Jan Kluge & Sarah Lappöhn & Kerstin Plank, 2023. "Predictors of TFP growth in European countries," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 50(1), pages 109-140, February.

    More about this item

    Keywords

    Returns to scale; Random coefficient stochastic distance frontier model; Bayesian estimation;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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

    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:eee:jbfina:v:39:y:2014:i:c:p:135-145. See general information about how to correct material in RePEc.

    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/jbf .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.