IDEAS home Printed from https://ideas.repec.org/a/nrb/journl/v30y2018i2p35.html
   My bibliography  Save this article

Technical Efficiency of Nepalese Banking Sector

Author

Listed:
  • Kishor Hakuduwal, Ph.D.

    (Bhaktapur Multiple Campus, Faculty of Management, Tribhuvan University)

Abstract

The paper estimates and assesses the technical efficiency at individual and aggregate levels and categorizes groups of banks at various ranges of efficiency. The commercial and development banks established before 2005 in Nepal has been considered as the population of the study and 20 banks are selected using systematic random sampling. The 180 observations of nine year’s panel data from FY 2006/07 to FY 2014/15 has been used. Stochastic Frontier Approach is used taking three input variables i.e. capital, deposit and human resource cost, and one output variable i.e. loans and advance of sampled banks for analysis. The study found that the average technical efficiency (TE) by nature of banks provide commercial banks as the more efficient than development banks. The joint venture banks are the most efficient than other categories of banks. The average efficiency of banks established inside the Kathmandu valley (Head Office located inside Kathmandu) is lower than the average efficiency of banks established outside the Kathmandu valley (Head Office located outside Kathmandu). Similarly, the banks established after 1995 are found more efficient than the banks established before 1995. The study has important implications for the policymakers to take corrective actions for improving the efficiency of the Nepalese banking sector with respect to human resource policy, deposit collection policy and loan management policy.

Suggested Citation

  • Kishor Hakuduwal, Ph.D., 2018. "Technical Efficiency of Nepalese Banking Sector," NRB Economic Review, Nepal Rastra Bank, Economic Research Department, vol. 30(2), pages 1-35, October.
  • Handle: RePEc:nrb:journl:v:30:y:2018:i:2:p:35
    as

    Download full text from publisher

    File URL: https://www.nrb.org.np/contents/uploads/2019/12/vol30-2_art3.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aditi Bhattacharyya & Sudeshna Pal, 2013. "Financial reforms and technical efficiency in Indian commercial banking: A generalized stochastic frontier analysis," Review of Financial Economics, John Wiley & Sons, vol. 22(3), pages 109-117, September.
    2. Berger, Allen N. & DeYoung, Robert, 1997. "Problem loans and cost efficiency in commercial banks," Journal of Banking & Finance, Elsevier, vol. 21(6), pages 849-870, June.
    3. Sabin Bikram Panta & Devi Prasad Bedari, Ph.D., 2015. "Cost Efficiency of Nepali Commercial Banks in the Context of Regulatory Changes," NRB Economic Review, Nepal Rastra Bank, Research Department, vol. 27(2), pages 1-16, October.
    4. Abdus Samad, 2009. "Measurement Of Inefficiencies In Bangladesh Banking Industry Using Stochastic Frontier Production Function," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 3(1), pages 41-48.
    5. Bauer, Paul W. & Berger, Allen N. & Ferrier, Gary D. & Humphrey, David B., 1998. "Consistency Conditions for Regulatory Analysis of Financial Institutions: A Comparison of Frontier Efficiency Methods," Journal of Economics and Business, Elsevier, vol. 50(2), pages 85-114, March.
    6. S S Rajan & K L N Reddy & V N Pandit, 2011. "Efficiency and Productivity Growth in Indian Banking," Working Papers id:4359, eSocialSciences.
    7. Luintel, Kul B. & Selim, Sheikh & Bajracharya, Pushkar, 2017. "Liberalization, bankers’ motivation and productivity: A simple model with an application," Economic Modelling, Elsevier, vol. 61(C), pages 102-112.
    8. Luo, Xueming, 2003. "Evaluating the profitability and marketability efficiency of large banks: An application of data envelopment analysis," Journal of Business Research, Elsevier, vol. 56(8), pages 627-635, August.
    9. 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.
    10. Mester, Loretta J., 1993. "Efficiency in the savings and loan industry," Journal of Banking & Finance, Elsevier, vol. 17(2-3), pages 267-286, April.
    11. S. S. Rajan & K. L. N. Reddy & V. N. Pandit, 2011. "Efficiency And Productivity Growth In Indian Banking," Working papers 199, Centre for Development Economics, Delhi School of Economics.
    12. Md Zobaer Hasan & Anton Abdulbasah Kamil & Adli Mustafa & Md Azizul Baten, 2012. "A Cobb Douglas Stochastic Frontier Model on Measuring Domestic Bank Efficiency in Malaysia," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-5, August.
    13. Ihsan Isik & M. Kabir Hassan, 2002. "Cost and Profit Efficiency of the Turkish Banking Industry: An Empirical Investigation," The Financial Review, Eastern Finance Association, vol. 37(2), pages 257-279, May.
    14. Bhattacharyya, Aditi & Pal, Sudeshna, 2013. "Financial reforms and technical efficiency in Indian commercial banking: A generalized stochastic frontier analysis," Review of Financial Economics, Elsevier, vol. 22(3), pages 109-117.
    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. 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.
    17. Sabin Bikram Panta & Devi Prasad Bedari, Ph.D., 2015. "Cost Efficiency of Nepali Commercial Banks in the Context of Regulatory Changes," NRB Economic Review, Nepal Rastra Bank, Economic Research Department, vol. 27(2), pages 75-90, October.
    18. Shujie Yao & Chunxia Jiang & Genfu Feng & Dirk Willenbockel, 2007. "WTO challenges and efficiency of Chinese banks," Applied Economics, Taylor & Francis Journals, vol. 39(5), pages 629-643.
    19. Karan S. Thagunna & Shashank Poudel, 2013. "Measuring Bank Performance of Nepali Banks: A Data Envelopment Analysis (DEA) Perspective," International Journal of Economics and Financial Issues, Econjournals, vol. 3(1), pages 54-65.
    20. 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.
    21. 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.
    Full references (including those not matched with items on IDEAS)

    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. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    2. Manlagñit, Maria Chelo V., 2011. "Cost efficiency, determinants, and risk preferences in banking: A case of stochastic frontier analysis in the Philippines," Journal of Asian Economics, Elsevier, vol. 22(1), pages 23-35, February.
    3. Williams, Jonathan, 2004. "Determining management behaviour in European banking," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2427-2460, October.
    4. Saeed, Momna & Izzeldin, Marwan, 2016. "Examining the relationship between default risk and efficiency in Islamic and conventional banks," Journal of Economic Behavior & Organization, Elsevier, vol. 132(S), pages 127-154.
    5. Jiang, Chunxia & Yao, Shujie & Zhang, Zongyi, 2009. "The effects of governance changes on bank efficiency in China: A stochastic distance function approach," China Economic Review, Elsevier, vol. 20(4), pages 717-731, December.
    6. Zuzana Iršová & Tomáš Havránek, 2010. "Measuring Bank Efficiency: A Meta-Regression Analysis," Prague Economic Papers, Prague University of Economics and Business, vol. 2010(4), pages 307-328.
    7. Marko Košak & Peter Zajc & Jelena Zorić, 2009. "Bank efficiency differences in the new EU member states," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 9(2), pages 67-90, December.
    8. Kwan, Simon H., 2006. "The X-efficiency of commercial banks in Hong Kong," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1127-1147, April.
    9. 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.
    10. Altunbas, Yener & Liu, Ming-Hau & Molyneux, Philip & Seth, Rama, 2000. "Efficiency and risk in Japanese banking," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1605-1628, October.
    11. Silva, Thiago Christiano & Tabak, Benjamin Miranda & Cajueiro, Daniel Oliveira & Dias, Marina Villas Boas, 2018. "Adequacy of deterministic and parametric frontiers to analyze the efficiency of Indian commercial banks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1016-1025.
    12. 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.
    13. Manlagnit, Maria Chelo V., 2015. "Basel regulations and banks’ efficiency: The case of the Philippines," Journal of Asian Economics, Elsevier, vol. 39(C), pages 72-85.
    14. Guohua Feng & Apostolos Serletis, 2009. "Efficiency and productivity of the US banking industry, 1998-2005: evidence from the Fourier cost function satisfying global regularity conditions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 105-138.
    15. Zuzana Irsova & Tomas Havranek, 2011. "Bank Efficiency in Transitional Countries: Sensitivity to Stochastic Frontier Design," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 18(2), pages 230-270, December.
    16. Berger, Allen N. & Mester, Loretta J., 1997. "Inside the black box: What explains differences in the efficiencies of financial institutions?," Journal of Banking & Finance, Elsevier, vol. 21(7), pages 895-947, July.
    17. Altunbas, Y. & Gardener, E. P. M. & Molyneux, P. & Moore, B., 2001. "Efficiency in European banking," European Economic Review, Elsevier, vol. 45(10), pages 1931-1955, December.
    18. Goddard, John & Molyneux, Philip & Williams, Jonathan, 2014. "Dealing with cross-firm heterogeneity in bank efficiency estimates: Some evidence from Latin America," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 130-142.
    19. Kutlu, Levent & Mamatzakis, Emmanuel & Tsionas, Mike G., 2022. "A principal–agent approach for estimating firm efficiency: Revealing bank managerial behavior," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    20. Prakash, Navendu & Singh, Shveta & Sharma, Seema, 2021. "Technological diffusion, banking efficiency and Solow's paradox: A frontier-based parametric and non-parametric analysis," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 534-551.

    More about this item

    Keywords

    Technical Efficiency; Stochastic Frontier Approach; Panel Data; Nepalese Banking Sector;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • 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:nrb:journl:v:30:y:2018:i:2:p:35. 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: Publication Division NRB (email available below). General contact details of provider: https://edirc.repec.org/data/nrbgvnp.html .

    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.