IDEAS home Printed from https://ideas.repec.org/a/spr/jqecon/v22y2024i2d10.1007_s40953-024-00389-8.html
   My bibliography  Save this article

Dynamics of Operational Efficiency in Credit Lending and Recovery of Stressed Assets: An Alternative Approach with Undesirable By-Products

Author

Listed:
  • Gargi Sanati

    (National Institute of Bank Management)

  • Anup Kumar Bhandari

    (Indian Institute of Technology Madras)

Abstract

Our study estimates the operational efficiency of Indian banks during 2009–2010 to 2017–2018, considering advances, and recovery of stressed assets as desirable outputs, while NPAs and slippages are undesirable by-products. Our first stage DEA analyses conclude that public sector banks have significant scope to improve their lending and recovery efficiency, while also reducing their stressed assets. Our analyses also reveal that banks are more efficient in managing credit risks for shorter-term loan portfolios and secured loans, while positive economic externalities are more prominent in determining the efficiency of banks in priority sector lending. We also observe that a competitive scenario within the banking sector, overall macroeconomic growth, and low cost of funds play vital roles in improving banks' operational efficiency and reducing credit risk. Our findings suggest that liquid assets might be more beneficial than illiquid collaterals in improving the recovery of stressed assets.

Suggested Citation

  • Gargi Sanati & Anup Kumar Bhandari, 2024. "Dynamics of Operational Efficiency in Credit Lending and Recovery of Stressed Assets: An Alternative Approach with Undesirable By-Products," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 22(2), pages 365-394, June.
    • Handle: RePEc:spr:jqecon:v:22:y:2024:i:2:d:10.1007_s40953-024-00389-8
    DOI: 10.1007/s40953-024-00389-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40953-024-00389-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40953-024-00389-8?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. repec:bla:ecnote:v:33:y:2004:i:2:p:183-208 is not listed on IDEAS
    2. Marko Kosak & Jure Poljsak, 2010. "Loss given default determinants in a commercial bank lending: an emerging market case study," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 28(1), pages 61-88.
    3. 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.
    4. Khieu, Hinh D. & Mullineaux, Donald J. & Yi, Ha-Chin, 2012. "The determinants of bank loan recovery rates," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 923-933.
    5. Abhiman Das & Saibal Ghosh, 2006. "Financial deregulation and efficiency: An empirical analysis of Indian banks during the post reform period," Review of Financial Economics, John Wiley & Sons, vol. 15(3), pages 193-221.
    6. Hoff, Ayoe, 2007. "Second stage DEA: Comparison of approaches for modelling the DEA score," European Journal of Operational Research, Elsevier, vol. 181(1), pages 425-435, August.
    7. Stefano Caselli & Stefano Gatti & Francesca Querci, 2008. "The Sensitivity of the Loss Given Default Rate to Systematic Risk: New Empirical Evidence on Bank Loans," Journal of Financial Services Research, Springer;Western Finance Association, vol. 34(1), pages 1-34, August.
    8. Dermine, J. & de Carvalho, C. Neto, 2006. "Bank loan losses-given-default: A case study," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1219-1243, April.
    9. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    10. Rajiv D. Banker & Ram Natarajan, 2008. "Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis," Operations Research, INFORMS, vol. 56(1), pages 48-58, February.
    11. 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.
    12. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    13. Acharya, Viral V. & Bharath, Sreedhar T. & Srinivasan, Anand, 2007. "Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries," Journal of Financial Economics, Elsevier, vol. 85(3), pages 787-821, September.
    14. Luenberger, David G., 1992. "Benefit functions and duality," Journal of Mathematical Economics, Elsevier, vol. 21(5), pages 461-481.
    15. Mohammad Shahid Zaman & Anup Kumar Bhandari, 2020. "Financial deregulation, competition and cost efficiency of Indian commercial banks: is there any convergence?," Indian Economic Review, Springer, vol. 55(2), pages 283-312, December.
    16. repec:czx:journl:v:18:y:2011:i:28:id:183 is not listed on IDEAS
    17. Pınar Kaya Samut & Reyhan Cafrı, 2016. "Analysis of the Efficiency Determinants of Health Systems in OECD Countries by DEA and Panel Tobit," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 129(1), pages 113-132, October.
    18. Grunert, Jens & Weber, Martin, 2009. "Recovery rates of commercial lending: Empirical evidence for German companies," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 505-513, March.
    19. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    20. Rolf Färe & Shawna Grosskopf, 2000. "Theory and Application of Directional Distance Functions," Journal of Productivity Analysis, Springer, vol. 13(2), pages 93-103, March.
    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. Veronese da Silva, Aline & Costa, Marcelo Azevedo & Lopes-Ahn, Ana Lúcia, 2022. "Accounting multiple environmental variables in DEA energy transmission benchmarking modelling: The 2019 Brazilian case," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    2. H Fukuyama & W L Weber, 2009. "Estimating indirect allocative inefficiency and productivity change," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(11), pages 1594-1608, November.
    3. Zaman, Mohammad Shahid & Valiyattoor, Vipin & Bhandari, Anup Kumar, 2022. "Dynamics of total factor productivity growth: An empirical analysis of Indian commercial banks," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    4. Salas-Velasco, Manuel, 2018. "Production efficiency measurement and its determinants across OECD countries: The role of business sophistication and innovation," Economic Analysis and Policy, Elsevier, vol. 57(C), pages 60-73.
    5. Subhash C. Ray, 2014. "Data Envelopment Analysis: An Overview," Working papers 2014-33, University of Connecticut, Department of Economics.
    6. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    7. Youchao Tan & Udaya Shetty & Ali Diabat & T. Pakkala, 2015. "Aggregate directional distance formulation of DEA with integer variables," Annals of Operations Research, Springer, vol. 235(1), pages 741-756, December.
    8. Tsolas, Ioannis E., 2014. "Precious metal mutual fund performance appraisal using DEA modeling," Resources Policy, Elsevier, vol. 39(C), pages 54-60.
    9. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
    10. Carlos Barros & Hercules Haralambides & Mohamed Hussain & Nicolas Perpoch, 2011. "Seaport Efficiency and Productivity Growth," Chapters, in: Kevin Cullinane (ed.), International Handbook of Maritime Economics, chapter 17, Edward Elgar Publishing.
    11. Chen Kaihua & Kou Mingting, 2014. "Staged efficiency and its determinants of regional innovation systems: a two-step analytical procedure," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(2), pages 627-657, March.
    12. Subhash C. Ray, 2018. "Data Envelopment Analysis with Alternative Returns to Scale," Working papers 2018-20, University of Connecticut, Department of Economics.
    13. Touati-Tliba, Mohamed, 2024. "Comparative performance of Algeria's education districts: The Influence of colonial legacy through cultural capital," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    14. Daniel Santín & Gabriela Sicilia, 2015. "Measuring the efficiency of public schools in Uruguay: main drivers and policy implications," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 24(1), pages 1-28, December.
    15. Adler, Nicole & Ülkü, Tolga & Yazhemsky, Ekaterina, 2013. "Small regional airport sustainability: Lessons from benchmarking," Journal of Air Transport Management, Elsevier, vol. 33(C), pages 22-31.
    16. Picazo-Tadeo, Andrés J. & Beltrán-Esteve, Mercedes & Gómez-Limón, José A., 2012. "Assessing eco-efficiency with directional distance functions," European Journal of Operational Research, Elsevier, vol. 220(3), pages 798-809.
    17. Magdalena Kapelko & Alfons Oude Lansink & Spiro E Stefanou, 2015. "Effect of Food Regulation on the Spanish Food Processing Industry: A Dynamic Productivity Analysis," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-16, June.
    18. Kumar Mandal, Sabuj & Madheswaran, S., 2010. "Environmental efficiency of the Indian cement industry: An interstate analysis," Energy Policy, Elsevier, vol. 38(2), pages 1108-1118, February.
    19. Ricardo F. Díaz & Blanca Sanchez-Robles, 2020. "Non-Parametric Analysis of Efficiency: An Application to the Pharmaceutical Industry," Mathematics, MDPI, vol. 8(9), pages 1-27, September.
    20. Barros, Carlos Pestana & Peypoch, Nicolas, 2008. "Technical efficiency of thermoelectric power plants," Energy Economics, Elsevier, vol. 30(6), pages 3118-3127, November.

    More about this item

    Keywords

    Financing Policy; Financial Risk and Risk Management; Banks’ Ownership Structure; Stressed Assets; Slippage;
    All these keywords.

    JEL classification:

    • 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
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G38 - Financial Economics - - Corporate Finance and Governance - - - Government Policy and Regulation
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior

    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:spr:jqecon:v:22:y:2024:i:2:d:10.1007_s40953-024-00389-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.