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Is this adverse selection or something else to determine the non-performing loans? Dynamic panel evidence from South Asian countries

Author

Listed:
  • Md. Shahidul Islam

    (Department of Banking and Insurance, University of Dhaka)

  • Shin-Ichi Nishiyama

    (Graduate School of Economics, Kobe University)

Abstract

In the South Asian region, one of the major causes of higher non-performing loans (NPL) is the adverse selection of borrowers by the banks. Using the GMM estimator, we empirically studied the bank-specific, industry specific and macroeconomic specific determinants of non-performing loans of banks in the South Asian countries (Bangladesh, India, Nepal and Pakistan) for the period of 1997-2012 and found that the adverse selection hypothesis of Stiglitz and Weiss (1981) still effective. We found evidence for the bad luck, bad management, skimping and moral hazard hypotheses of Berger and DeYoung (1997) and their effect on the credit risk determination. Bank size, industry concentration, inflation and GDP growth rate all significantly affect the sample countries' non-performing loans. Empirical results show a moderate degree of persistence of NPL and a late-hit of the global financial crisis in the banking sector of the region.

Suggested Citation

  • Md. Shahidul Islam & Shin-Ichi Nishiyama, 2017. "Is this adverse selection or something else to determine the non-performing loans? Dynamic panel evidence from South Asian countries," Discussion Papers 1723, Graduate School of Economics, Kobe University.
  • Handle: RePEc:koe:wpaper:1723
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    References listed on IDEAS

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    1. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2003. "Instrumental variables and GMM: Estimation and testing," Stata Journal, StataCorp LP, vol. 3(1), pages 1-31, March.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    4. Castro, Vítor, 2013. "Macroeconomic determinants of the credit risk in the banking system: The case of the GIPSI," Economic Modelling, Elsevier, vol. 31(C), pages 672-683.
    5. Podpiera, Jiri & Weill, Laurent, 2008. "Bad luck or bad management? Emerging banking market experience," Journal of Financial Stability, Elsevier, vol. 4(2), pages 135-148, June.
    6. 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.
    7. Islam, Md. Shahidul & Nishiyama, Shin-Ichi, 2016. "The determinants of bank net interest margins: A panel evidence from South Asian countries," Research in International Business and Finance, Elsevier, vol. 37(C), pages 501-514.
    8. Md. Shahidul Islam & Shin-Ichi Nishiyama, 2016. "The Determinants of Bank Profitability: Dynamic Panel Evidence from South Asian Countries," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 6(3), pages 1-6.
    9. Innes, Robert D., 1990. "Limited liability and incentive contracting with ex-ante action choices," Journal of Economic Theory, Elsevier, vol. 52(1), pages 45-67, October.
    10. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 38(2), pages 112-134.
    11. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    12. Williams, Jonathan, 2004. "Determining management behaviour in European banking," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2427-2460, October.
    13. Bernanke, Ben S. & Gertler, Mark & Gilchrist, Simon, 1999. "The financial accelerator in a quantitative business cycle framework," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 21, pages 1341-1393, Elsevier.
    14. Louzis, Dimitrios P. & Vouldis, Angelos T. & Metaxas, Vasilios L., 2012. "Macroeconomic and bank-specific determinants of non-performing loans in Greece: A comparative study of mortgage, business and consumer loan portfolios," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1012-1027.
    15. Nobuhiro Kiyotaki & John Moore, 1997. "Credit Chains," ESE Discussion Papers 118, Edinburgh School of Economics, University of Edinburgh.
    16. Carey, Mark, 2002. "A guide to choosing absolute bank capital requirements," Journal of Banking & Finance, Elsevier, vol. 26(5), pages 929-951, May.
    17. Vicente Salas & Jesús Saurina, 2002. "Credit Risk in Two Institutional Regimes: Spanish Commercial and Savings Banks," Journal of Financial Services Research, Springer;Western Finance Association, vol. 22(3), pages 203-224, December.
    18. Bruna Skarica, 2014. "Determinants of non-performing loans in Central and Eastern European countries," Financial Theory and Practice, Institute of Public Finance, vol. 38(1), pages 37-59.
    19. Iftekhar Hasan & Larry D. Wall, 2004. "Determinants of the Loan Loss Allowance: Some Cross-Country Comparisons," The Financial Review, Eastern Finance Association, vol. 39(1), pages 129-152, February.
    20. Festic, Mejra & Kavkler, Alenka & Repina, Sebastijan, 2011. "The macroeconomic sources of systemic risk in the banking sectors of five new EU member states," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 310-322, February.
    21. Ahmed, Anwer S. & Takeda, Carolyn & Thomas, Shawn, 1999. "Bank loan loss provisions: a reexamination of capital management, earnings management and signaling effects," Journal of Accounting and Economics, Elsevier, vol. 28(1), pages 1-25, November.
    22. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
    23. Ali, Asghar & Daly, Kevin, 2010. "Macroeconomic determinants of credit risk: Recent evidence from a cross country study," International Review of Financial Analysis, Elsevier, vol. 19(3), pages 165-171, June.
    24. Rinaldi, Laura & Sanchis-Arellano, Alicia, 2006. "Household debt sustainability: what explains household non-performing loans? An empirical analysis," Working Paper Series 570, European Central Bank.
    25. Olga Bohachova, 2008. "The Impact of Macroeconomic Factors on Risks in the Banking Sector: A Cross-Country Empirical Assessment," IAW Discussion Papers 44, Institut für Angewandte Wirtschaftsforschung (IAW).
    26. Allen N. Berger & Robert DeYoung, "undated". "Problem Loans and Cost Efficiency in Commercial Banks," Finance and Economics Discussion Series 1997-08, Board of Governors of the Federal Reserve System (U.S.).
    27. Raphael A Espinoza & Ananthakrishnan Prasad, 2010. "Nonperforming Loans in the GCC Banking System and their Macroeconomic Effects," IMF Working Papers 10/224, International Monetary Fund.
    28. Townsend, Robert M., 1979. "Optimal contracts and competitive markets with costly state verification," Journal of Economic Theory, Elsevier, vol. 21(2), pages 265-293, October.
    29. Mark S. Carey, 2002. "A guide to choosing absolute bank capital requirements," International Finance Discussion Papers 726, Board of Governors of the Federal Reserve System (U.S.), revised 2002.
    30. Judson, Ruth A. & Owen, Ann L., 1999. "Estimating dynamic panel data models: a guide for macroeconomists," Economics Letters, Elsevier, vol. 65(1), pages 9-15, October.
    31. Angbazo, Lazarus, 1997. "Commercial bank net interest margins, default risk, interest-rate risk, and off-balance sheet banking," Journal of Banking & Finance, Elsevier, vol. 21(1), pages 55-87, January.
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    More about this item

    Keywords

    NPL; cost inefficiency; moral hazard; adverse selection;

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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