Determinants of non-performing financing in Indonesian Islamic banks: A regional and sectoral analysis
-
DOIhttp://dx.doi.org/10.21511/bbs.17(4).2022.07
-
Article InfoVolume 17 2022, Issue #4, pp. 72-86
- Cited by
- 545 Views
-
136 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
This study examines the determinants of Islamic banks’ non-performing financing from the perspective of regional and sectoral aspects during the periods before and during the pandemic. The study adopts a dynamic panel data analysis, namely the Generalized Method of Moments, and assesses panel data from the Indonesian banking industry in 32 provinces from October 2018 to July 2021 on a monthly basis. The study uses non-performing financing as the dependent variable and regional inflation, total financing, financing to deposit ratio, and Islamic bank size as the dependent variables. The findings indicate that the COVID-19 pandemic generally influenced the performance of non-performing financing in Islamic banks. This was evident in the significant relationship between regional inflation, total financing, financing to deposit ratio, and the non-performing financing value. Moreover, in the sectoral analysis, a different level of impact was observed in each sector. The most severe impact was seen in the construction sector, while other sectors were less affected during the pandemic. The regional analysis shows that all provinces on Java Island, as the epicenter of the pandemic in Indonesia, did not perform better than the provinces outside Java. Concerning policy implications, the Indonesian Financial Services Authority must be more aware of the determinants of Islamic banks’ non-performing financing by considering sectoral and regional aspects. Furthermore, sectoral and regional-based policies should be developed to achieve and maintain the performance of Islamic banks’ non-performing financing.
Acknowledgments
We are grateful to the Pusat Pengembangan Ekonomi (PPE), Faculty of Business and Economics, Universitas Islam Indonesia No. 259/KajurIE/XII/2021 for support and providing a research grant for the study
- Keywords
-
JEL Classification (Paper profile tab)E60, G20, G21
-
References32
-
Tables9
-
Figures0
-
- Table A1. Data description
- Table B1. GMM results in general
- Table C1. GMM results on sectoral (Agriculture, hunting, and forestry, fishery, and mining and excavation) and regional bases
- Table C2. GMM results on sectoral (processing industry, electricity, gas, and water, and construction) and regional bases
- Table C3. GMM results on sectoral (wholesale and retail trade, accommodation and food providers, and transportation, warehousing, and communication) and regional bases
- Table C4. GMM results on sectoral (financial intermediary, real estate, leasing and corporate service, and education service) and regional bases
- Table C5. GMM results on sectoral (health service and social activities, social, cultural, entertainment, and other services, and personal service serving households) and regional bases
- Table D1. Arellano-Bond test result
- Table E1. Blundell test result
-
- Al Wesabi, H. A. H., & Ahmad, N. H. (2013). Credit risk of Islamic banks in GCC countries. The International Journal of Banking and Finance, 10(2), 95-112.
- Alqahtani, F., & Mayes, D. G. (2018). Financial stability of Islamic banking and the global financial crisis: Evidence from the Gulf Cooperation Council. Economic Systems, 42(2), 346-360.
- An, H., Wang, H., Delpachitra, S., Cottrell, S., & Yu, X. (2022). Early warning system for risk of external liquidity shock in BRICS countries. Emerging Markets Review, 51(PA), 100878.
- Anderson, T. W., & Hsiao, C. (1981). Estimation of dynamic model with error component. Journal of American Statistical Association, 76(375), 598-606.
- Anto, M. H., Fakhrunnas, F., & Tumewang, Y. K. (2022). Islamic banks credit risk performance for home financing: Before and during Covid-19 pandemic. Economic Journal of Emerging Markets, 14(1), 113-125.
- Arellano, M., & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. The Review of Economic Studies, 58(2), 277.
- Arellano, M., & Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68(1), 29-51.
- Baltagi, B. H. (2005). Econometric analysis of panel data (3rd ed). Chichester, England: John Wiley & Sons.
- Bernanke, B., Gertler, M., & Gilchrist, S. (1998). Financial accelerator in a quantitative business cycle framework (NBER Working Paper No. 6455). Cambridge, MA, USA.
- Bond, S. (2002). Dynamic panel data models: A guide to micro data methods and practice. Portuguese Economic Journal, 1, 141-162.
- Bourkhis, K., & Nabi, M. S. (2013). Islamic and conventional banks’ soundness during the 2007–2008 financial crisis. Review of Financial Economics, 22(2), 68-77.
- Castro, V. (2013). Macroeconomic determinants of the credit risk in the banking system: The case of the GIPSI. Economic Modelling, 31, 672-683.
- Elnahass, M., Trinh, V. Q., & Li, T. (2021). Global banking stability in the shadow of Covid-19 outbreak. Journal of International Financial Markets, Institutions & Money, 72, 101322.
- Fakhrunnas, F., Nuri, R., Nugrohowati, I., Haron, R., Bekti, M., & Anto, H. (2022). The Determinants of Non-Performing Loans in the Indonesian Banking Industry : An Asymmetric Approach Before and During the Pandemic Crisis. Sage Open, 1-13.
- Farhan, M., Sattar, A., Chaudhry, A. H., & Khalil, F. (2012). Economic determinants of non-performing loans: Perception of Pakistani bank. European Journal of Business and Management, 4(19), 87-99.
- Jara-Bertin, M., Arias Moya, J., & Rodríguez Perales, A. (2014). Determinants of Bank Performance: Evidence for Latin America. Academia Revista Latinoamericana de Administración, 27(2), 164-182.
- Kabir, M. N., Worthington, A., & Gupta, R. (2015). Comparative credit risk in Islamic and conventional bank. Pacific Basin Finance Journal, 34, 327-353.
- Karadima, M., & Louri, H. (2020). Non-performing loans in the euro area: Does bank market power matter? International Review of Financial Analysis, 72, 101593.
- Khattak, M. A., Hamid, B. A., Islam, M. U., & Ali, M. (2021). Competition, diversification, and stability in the Indonesian banking system. Buletin Ekonomi Moneter Dan Perbankan, 24, 59-88.
- Kiyotaki, N., & Moore, J. (1997). Credit cycles. Journal of Policy Modeling, 105(2), 211-248.
- Klein, N. (2013). Non-performing loans in CESEE: Determinants and impact on macroeconomic performance (Working Paper No. WP/13/72). International Monetary Fund.
- Masood, O., & Ashraf, M. (2012). Bank-specific and macroeconomic profitability determinants of Islamic banks. Qualitative Research in Financial Markets, 4(2/3), 255-268.
- OJK. (2021). Statistik Perbankan Syariah.
- Rashid, A., & Jabeen, S. (2016). Analyzing performance determinants: Conventional versus Islamic banks in Pakistan. Borsa Istanbul Review, 16(2), 92-107.
- Siddiqui, A. (2008). Financial contracts, risk and performance of Islamic banking. Managerial Finance, 34(10), 680-694.
- Statistics Indonesia. (2022). Indonesian Economic Growth Quarter I-2022.
- Tan, Y., & Floros, C. (2012). Bank profitability and inflation: The case of China. Journal of Economic Studies, 39(6), 675-696.
- Touny, M. A., & Shehab, M. A. (2015). Macroeconomic determinants of non-performing loans: An empirical study of some Arab countries. American Journal of Economics and Business Administration, 7(1), 11-22.
- Trinugroho, I., Risfandy, T., & Doddy, M. (2018). Competition, diversification, and bank margins: Evidence from Indonesian Islamic rural banks. Borsa Istanbul Review, 18(4), 349-358.
- Uddin, A., Chowdhury, M. A. F., & Islam, M. N. (2017). Resiliency between Islamic and conventional banks in Bangladesh: dynamic GMM and quantile regression approaches. International Journal of Islamic and Middle Eastern Finance and Management, 10(3), 400-418.
- Warue, B. N. (2013). No Title The Effects of Bank Specific and Macroeconomic Factors on Non Performing Loans in Commercial Banks in Kenya: A Comparative Panel Data Analysis. Advances in Management & Applied Economics, 3(2), 1-7.
- Widarjono, A., Anto, M. B. H., & Fakhrunnas, F. (2020). Financing risk in Indonesian Islamic rural banks: Do financing products matter? Journal of Asian Finance, Economics and Business, 7(9), 305-314.