Are Islamic Banks Truly Shariah Compliant? An Application of Time Series Multivariate Forecasting Techniques to Islamic Bank Financing

Rafi, Umar and Masih, Mansur (2014): Are Islamic Banks Truly Shariah Compliant? An Application of Time Series Multivariate Forecasting Techniques to Islamic Bank Financing.

Abstract

This paper analyzes the Shariah compliant nature of Islamic banks (IB) by using Time Series Multivariate Forecasting techniques to test the correlation and direction of causality between interest rates and IB financing . Islamic finance defines a 0% Interest rate, both on the asset and on the liability side. Thus, in a utopian Islamic financial system, any movement in interest rates should have no direct impact on any aspect of any Islamic bank. However, the supposition of IBs being genuinely Shariah compliant from a Credit Risk perspective has been challenged by many Shariah scholars. Using Malaysia as a test case, this paper measures changes in KLIBOR (Kuala Lampur Interbank Offer Rate) and tests them for correlations and directional causality with the IB Lending rate (used as a proxy measure for financing by Malaysian IBs). If a correlation and causality can be established between KLIBOR and financing by IBs, then it is an indication that IB’s may not be genuinely Shariah compliant. This research is original in that it attempts to relate an important issue of a fiqhi nature to data analysis, via some time series forecasting techniques. It also discusses the policy impacts of the results, and the subsequent risk faced by the Regulators in managing the Interest rate risks for a financial system structured on dual banking - Islamic and Conventional. The findings of the research tend to indicate a correlation and lead-lag causality relationship between Interest rate changes and Islamic bank financing.

• Item Type: MPRA Paper
• Language: English
• Keywords: Islamic banks, Shariah compliant, Time series techniques, 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 > G2 - Financial Institutions and Services > G21 - Banks ; Depository Institutions ; Micro Finance Institutions ; Mortgages; G - Financial Economics > G2 - Financial Institutions and Services > G28 - Government Policy and Regulation

References

Abu Bakr, N., Tahir, I. (2009). Applying Multiple Linear Regression and Neural Network to Predict Bank Performance. International Business Research, Vol. 2 No.4.

Chong, B. S. and Liu, M. H. (2009). Islamic Banking: Interest Free or Interest Based. Pacific Basin Finance Journal, Vol 17. 125 – 144.

Durrani, M., Boocock, G., (2006). Venture Capital, Islamic Finance and SMEs. Palgrave McMillon. New York, NY.

Enders, Walter. (2010). Applied Econometric Time Series. John Wiley & Sons. Alabama

Engle, R., Granger, W. (1987). Cointegration and Error Correction: Representation, Estimation and Testing. Econometrica, Vol. 55, No. 2. (Mar., 1987), pp. 251-276.

Hakan, E. E., Gulumser, A.B., (2011). Impact of Interest Rates on Islamic and Conventional Banks: The Case of Turkey. Munich Personal RePEc Archive.

Haron, Sudan, Ahmad, Norafifah (2000). The Effects of Conventional Interest Rates and Rate of Profit on Funds Deposited with Islamic Banking System in Malaysia. International Journal of Islamic Financial Services, Vol. 1 No.4

Kader, R.A., Leong, K.Y., (2009). The Impact of Interest Rate Changes on Islamic Bank Financing. International Review of Business Research Papers, Vol. 5 No. 3, 189-201.

Masih, M., Al-Elg, A. and Madani, H. (2009). Causality Between Financial Development and Economic Growth: an application of vector error correction and variance decomposition methods to Saudi Arabia, Applied Economics, 41, 1691–1699

Masih, M. and Algahtani, I.(2008). Estimation of Long-Run Demand for Money: An Application of Long-Run Structural Modelling to Saudi Arabia. Economia internazionale, 81–99

Masih, M., Al-Sahlawi, M. A. and De Mello, L. (2010). What drives carbon-dioxide emissions: Income of electricity generation? Evidence from Saudi Arabia, The Journal of Energy and Development, Vol. 33, No. 2, 201–213

Pesaran, B. and Pesaran, M. H. (2009). Time Series Econometrics using Microfit 5.0. Oxford University Press. UK.

Usmani, M.T. (1998), An Introduction to Islamic Finance. Karachi, Pakistan.

Yussof, L.M.M., Rahman, A.A., Alias, N. (2001). Interest Rate and Loan Supply: Islamic Versus Conventional Banking System. Jurnal kollomi Malaysia, Vol 35. 61 – 68.