Craigwell, Roland C and Elliott, Wayne A (2011): Loan loss provisioning in the commercial banking system of Barbados: practices and determinants. Published in: International Research Journal of Finance and Economics No. 65 (2011): pp. 98-111.
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The purpose of this paper is to investigate the process of loan loss provisioning within the commercial banking system of Barbados. It uses questionnaires and interviews to ascertain how banks set their provisional standards and levels. In addition, the results from this approach reveal, for the first time in Barbados, the individual banks‟ procedures for loan loss provisioning. An evaluation of the impact of macroeconomic and bank specific factors on commercial banks‟ provisions utilising panel dynamic ordinary least squares is also undertaken. Both sets of factors are found to influence the level of provisions. In particular, loan loss provisions are heavily dependent upon the performance of the real economy and competition in international markets is shown to have serious implications for the banking sector in both the short and long run. Moreover, this study asserts that larger banks in Barbados are better able to screen loans and avoid defaults.
|Item Type:||MPRA Paper|
|Original Title:||Loan loss provisioning in the commercial banking system of Barbados: practices and determinants|
|Keywords:||Loan Loss Provisioning; Banking System; Loan Classification|
|Subjects:||M - Business Administration and Business Economics; Marketing; Accounting > M4 - Accounting and Auditing > M41 - Accounting
G - Financial Economics > G2 - Financial Institutions and Services > G28 - Government Policy and Regulation
G - Financial Economics > G2 - Financial Institutions and Services > G21 - Banks; Depository Institutions; Micro Finance Institutions; Mortgages
|Depositing User:||Roland Craigwell|
|Date Deposited:||15. Sep 2011 18:04|
|Last Modified:||12. Feb 2013 12:45|
Angklomkliew, S., George, J., and Packer, F. (Dec 2009) “Issues and Developments in Loan Loss Provisioning: The Case of Asia.” BIS Quarterly Review.
Balla, E. and McKenna, A., (2009). “Dynamic provisioning: a countercyclical tool for loan loss reserves.” Economic Quarterly, Federal Reserve Bank of Richmond, issue fall, pages 383-418.
Basel Committee on Banking Supervision (1999) “A New Capital Adequacy Framework.” Bank for International Settlements
Bikker, J.A. and Metzemakers, P.A.J., (2002). “Bank provisioning behaviour and procyclicality.” Research Series Supervision 50, Netherlands Central Bank, Directorate Supervision.
Bouvatier, V. and Lepetit, L., (2008). “Banks' procyclical behavior: Does provisioning matter?” Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 513-526, December.
Breitung, J. (2002), “Nonparametric Tests for Unit Roots and Cointegration.” Journal of Econometrics 108, 343-364.
Cortavarria, L. Kanaya, A., Song, I. and Dziobek, C.H, (2000) “Loan Review, Provisioning, and Macroeconomic Linkages.” IMF Working Papers 00/195, International Monetary Fund.
Floro, D, (2010) “Loan Loss Provisioning and the Business Cycle: Does Capital Matter? Evidence from Philippine Banks.” Bank for International Settlements.
Greenidge, K. and Grosvenor, T.,(2010), “Forecasting Non-Performing Loans in Barbados.” Business. Finance and Economics in Emerging Economies Vol 5 No.1 2010.
Im, K.S, Pesaran, M.H. and Shin, Y. (2003) “Testing for Unit Roots in Heterogeneous Panels.” Journal of Econometrics 115(1): 53-74.
Jiménez, G. and Saurina, J., (2006), “Credit cycles, credit risk, and prudential regulation” International Journal of Central Banking (2), 65-98.
Jokivuolle, E., and Peura, S. (2003). “Incorporating Collateral Value Uncertainty in Loss Given Default Estimates and Loan-to-value Ratios. European Financial Management.” 9(3), 299-314. Retrieved from E-Journals database.
Khemraj, T., and Pasha S. (2009) “The determinants of non-performing loans: an econometric case study of Guyana.” Presented at the Caribbean Centre for Banking and Finance Bi-annual Conference on Banking and Finance, St. Augustine, Trinidad.
Kao, C., (1999). “Spurious Regression and Residual-Based Tests for Cointegration in Panel Data.” Journal of Econometrics, 90, 1-44.
Kao, C., and Chiang, M. (2000) “On the estimation and inference of a cointegrated regression in panel data.” Advances in Econometrics 15, 179-222.
Laeven, L. and Majnoni, G., (2003). “Loan loss provisioning and economic slowdowns: too much, too late?” Journal of Financial Intermediation, Elsevier, vol. 12(2), April.
Laurin, A. and Majnoni, G. (2003) “Bank loan classification and provisioning practices in selected developed and emerging countries.” World Bank working paper series; no. 1, Report Number 26056
Levin, A., Lin, C. and Chu, S,. (2002) “Unit root tests in panel data:Asymptotic and finite-sample properties.” Journal of Economics 108: 1-24.
Mark, N., and Sul, D., (2003). “Cointegration Vector Estimation by Panel DOLS and Long-run money Demand.” Oxford Bulletin of Economics and Statistics 65(5), 655-80.
Pedroni, P., (1999). “Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors.” Oxford Bulletin of Economics and Statistics 61, 653-678.
Saikkonen, P. (1991), “Asymptotically Efficient Estimation of Cointegration Regressions.” Econometric Theory, 7, 1-21. Song, I. (2002). “Collateral in Loan Classification and provisioning.” IMF- Monetary and Exchange Affairs Department. EconLit with Full Text, EBSCOhost(accessed June 10,2010).
Stock, J., and Watson, M., (1993). “A Simple Estimator of Cointegrating Vectors in High Order Integrated Systems.” Econometrica,61, 783-820.
Wezel, T., (2010) “Dynamic Loan Loss Provisions in Uraguay: properties, Shock Absorption Capacity and Simulations Using Alternative Formulas.” IMF Working Papers, Vol., pp. 1-22, 2010.
White, H. (1980). “A Heteroskedasticity- Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity.” Econometrica, vol. 48, issue 4, 817-838.