The vulnerability of Islamic bank’s credit risk to oil price shocks: evidence from Malaysia based on ARDL approach

Rahman, Syarifah and Masih, Mansur (2018): The vulnerability of Islamic bank’s credit risk to oil price shocks: evidence from Malaysia based on ARDL approach.

Abstract

Credit risk analysis is a key to a better financial risk management. This issue has been the primary focus of financial and banking industry since loans are the largest and most prominent source of credit risk. Unlike the conventional banking, there is a lack of empirical study on credit risk about Islamic banking. As such, further research regarding the vulnerability of the Islamic banking industry has become vital. Accordingly, this paper is aimed at determining and assessing the long run vulnerabilities of Malaysian Islamic banks in term of its response to the shocks of the price of crude oil. The fall in oil prices is believed to have an impact on loans’ repayment. Additionally, the selected key macroeconomic variables used in this study will be used as controlled variables so that the model will not be spurious. The autoregressive distributed lag (ARDL) methodology is employed to test this relationship, controlling for information in other financial and economic indicators. Based on the result of variance decompositions (VDCs) and impulse response function (IRF), it is found that, sufficient evidence of a long-run relationship exists between credit risk ratio in Islamic banking industry and the selected macroeconomic variables. The results tend to indicate that oil price shocks are an endogenous variable in the short-run dynamics, and the ranking provided byVDCs indicates that oil price shocks are least likely to have affected the Non-performing financing (NPF) ratio of Islamic banks as it is ranked at 6th place.

• Item Type: MPRA Paper
• Language: English
• Keywords: Islamic banks, Non-performing financing (NPF), oil price, ARDL, VDC, Malaysia
• Subjects: C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics; G - Financial Economics > G1 - General Financial Markets > G15 - International Financial Markets; G - Financial Economics > G2 - Financial Institutions and Services > G21 - Banks ; Depository Institutions ; Micro Finance Institutions ; Mortgages

References

Adebola, S. S., W. S. W. Yusoff, and J. Dahlan. (2011). An Ardl Approach to The Determinants of Non-Performing Loans In Islamic Banking System In Malaysia. Kuwait Chapter of Arabian Journal of Business and Management Review, 1(2), 20-30.

Akerlof, G. (1970). The Market for "Lemons": Quality Uncertainty and the Market Mechanism. The Quarterly Journal of Economics, 84(3), 488-500.

Al Shamsi, F., Aly, H., and El-Bassiouni, M. (2009). Measuring and explaining the efficiencies of the United Arab Emirates banking system. Applied Economics, 41(27), 3505 -3519

Balaz, P. and Londarev, A. (2006). Oil and its position in the process of globalization of the world economy. Politicka Ekonomie, 54 (4), 508-528.

Bank Negara Malaysia, (2016). Bank Negara Malaysia Monthly Statistical Bulletin January.

Bracons, A. O., Charles A. E. G., Dimitrios P. T., and Lea Z. (2013). Towards a Measure of Financial Fragility. Discussion Paper Series No. 554(2).

Brown, S., & Yucel, M. (2002). Energy prices and aggregate economic activity and interpretative survey. The Quarterly Review of Economic and Finance, 42(2), 193 -208.

Caruth, A., Hooker, M., & Oswald, A. (1998). Unemployment equilibria and input prices: Theory and evidence from the United States. Review of Economics and Statistic, 80(4), 621 -628

Cihák. (2007). Introduction to Applied Stress Testing. IMF Working Paper, 59.

Cihak, M & H. Hesse. (2008). Islamic banks and financial stability: An empirical analysis. IMF Working Paper 08/16.

Clair, R. St. (2004). Macroeconomic Determinants of Banking Financial Performance and Resilience in. Monetary Autharity of Singapore Staff Paper, 38.

Cologni, A. and Manera, M. (2008). Oil Prices, Inflation and Interest Rates in a Structural Cointegrated VAR Model for the G-7 Countries. Energy Economics, 30(3), 856-888.

Cologni, A. and Manera M. (2009). The Asymmetric Effects of Oil Shocks on Output Growth: A Markov–Switching analysis for the G-7 countries. Economic Modelling, 26(1), 1–29.

Cunado, J., and Perez de Garcia, F. (2005). Oil prices, economic activity and inflation: evidence for some Asian countries. The Quarterly Review of Economics and Finance 45 (1), 65-83.

Davis, S. J. (2001). Sectoral job creation and destruction responses to oil price changes. Journal of Monetary Economics., 48(3), 465 -512

Dell’Ariccia, G. and R. Marquez. (2004). Information and Bank Credit Allocation. Journal of Financial Economics, 72(1), 185–214.

Demirgüç-Kunt, A. and H. Huizinga,. (1999). Determinants of Commercial Bank Interest Margins and Profitability: Some International Evidence. World Bank Economic Review, 13(2),, 379–408.

Demirguç-Kunt, A. and E. Detragiache. (1998). The Determinants of Banking Crises in Developing and. IMF Staff Paper, 45(1) 81 -109

Demirgüç-Kunt, A., L. Laeven, and R. Levine,. (2004). Regulations, Market Structure, Institutions, and the Cost of Financial Intermediation. Journal of Money, Credit and Banking, 36( 3), 593–622.

Ferderer, J. P. (1996). Oil price volatility and the macroeconomy: A solution to the asymmetry puzzle. Journal of Macroeconomics., 18(1), 1 -26.

Gronwald, M. (2008). Large oil shocks and the US economy: Infrequent incidents with large effects. Energy Journal, 29, 151-71.

Kilian, L. and R. Vigfusson. (2011). Are the Responses of the U.S. Economy Asymmetric in Energy Price Increases and decreases? Quantitative Economics, 2(3), 419-453.

Kinda, T., Mlachila, M., and Ouedraogo, R. (2016). Commodity Price Shocks and Financial Sector Fragility. IMF Working Paper No.16/12

Lawrence, E. C. (1995). Consumer default and the life cycle model. Journal of Money Credit and, 27(4), 939-954.

Mostafa, M. (2007). Benchmarking top Arab banks’ efficiency through efficient frontier analysis. Industrial Management Data Systems, 107(6), 802-823

Nursechafia, and Abduh, M. (2014). The Susceptibility of Islamic Banks’ Credit Risk Towards. Journal of Islamic Finance. 3(1), 22 -36

Poghosyan, T., and Hesse, H. (2009). Oil Prices and Bank Profitability: Evidence from Major Oil-Exporting Countries in the Middle East and North Africa. International Monetary Fund, Working Paper No. 09/220, 1-21.

Rinaldi L. and Sanchis-Arellano, A. (2006). Household debt sustainability: What explains household non-performing loans? An Empirical Analysis. ECB Working Paper, 570.

Said, A. (2013). Risks and Efficiency in the Islamic Banking Systems: The Case of Selected Islamic Banks in MENA Region. International Journal of Economics and Financial Issues 3(1), 66-73.

Said, A. (2015). The Influence of Oil Prices on Islamic Banking Efficiency Scores during the Financial Crisis: Evidence from the MENA area. International Journal of Finance & Banking Studies 4(3), 35-43.

Samad, A. S. (2004). Performance of interest free Islamic Banks vis-à-vis interest-based conventional banks of Bahrain. IIUM Journal of Economics and Management, 12(2), 1-15.

Samad, A., and Hassan, M.K. (1999). The performance of [the] Malaysian Islamic bank during 1984-1997: An exploratory study. International Journal of Islamic Financial Services, 4(1), 55-69.

Shamsudheen, S. V., and Masih, M. (2015). Does the conventional benchmark prop up non-performing loans in Islamic banks? A case study of Malaysia with ARDL Approach. MPRA Paper No. 65845.

Yip, C., Lim, H., and Golam Hassan, A. (2009). The impacts of oil shocks on Malaysia's GDP growth, Proceedings of the 5th Asian Mathematical Conference. Malaysia.