IMPLEMENTING THE BANKING SECTOR SOUNDNESS INDEX (BSS) FOR PREDICTING BANKING CRISIS
Keywords:
Crisis, Islamic banking, ASEAN, BSS IndexAbstract
Bank is financial intermediary that play important role in the economy. Banks can’t be separated from external and internal factors that can cause financial distress. This study aimed to examine the effect of economic growth, inflation, the ratio of money supply, Capital (CAR), Asset quality (LAR), Management (MAN), Earning (ROA), Liquidity (FDR), and Sensitivity to market risk (SEN) towards predictions Islamic banking crisis in ASEAN using Banking Sector Soundness Index (BSS). The samples in this study are 24 Islamic bank in ASEAN (Indonesia, Malaysia, the Philippines, and Thailand). The results showed that the macroeconomic variables are economic growth and the exchange rate have negatively effect, while the inflation rate and the ratio of the money supply have positively effect. For the bank's internal factors, variable asset quality (LAR) has negative effect to banking crisis.
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Almilia, L. S., & Herdiningtyas, W. (2005). Analisis Rasio CAMEL Terhadap Prediksi Kondisi Bermasalah Pada Lembaga Perbankan Periode 2000-2002. Jurusan Ekonomi Akuntansi, Fakultas Ekonomi - Universitas Kristen Petra, 7(2), 131-147.
Angkinand, A. P. (2009). Banking Regulation and The Output Cost Of Banking Crises. Journal of International Finance Market Institutional & Money, 19, 240-257.
Ascarya. (2009). Pelajaran Yang Dipetik Dari Krisis Keuangan Berulang:Perspektif Ekonomi Islam. Buletin Ekonomi Moneter dan Perbankan, Bank Indonesia.
Bhattacharya, B., & Roy, T. N. (2009) Forewarning Indicator System For Banking Crisis In India. http://ssrn.com/abstract=1906576, 1-37.
Boyacioglu, M. A., Kara, Y., & Baykan, O. K. (2009). Predicting Bank financial Failures Using Neural Networks, Support Vector Machines And Multivariate Statistical Methods: A Comparative Analysis In The Sample Of Savings Deposit Insurancefund (SDIF) Transferred Banks In Turkey. Expert System with Applications, 3355-3366.
Buyukkarabacak, B., & Valev, N. (2012). Credit Information Sharing and Banking Crisis : An Empirical Investigation. Journal of Macroeconomic, 797.
Corsetti, Giancarlo, Paolo Pesenti, & Nouriel Roubini, (1998). What Caused tha Asian Currency and Financial Crisis? Part I: A Macroeconomi Overview. NBER Working Paper No. 6833 Cambridge, Massachusetts: National Bureau of Economic Research.
data.worldbank.org/ retrieved 15 December 2015
Demirguc-Kunt, A., & Detragiache, E. (1999). Monitoring Banking Sector Fraglity; A Multivariat Logit Approach with an Application to the 1996-1997 Banking Crisis. IMF Working Paper, 1-48.
Demirguc-Kunt, A., & Detreagiache, E. (2005). Cross-Coubtry Empirical Studies Of Systemic Bank Distress: A Survey. IMF Working Paper, 1-26.
Fahmi, I. (2015). Manajemen Perbankan Konvensional dan Syariah. Jakarta: Mitra Wacana Media.
Flood, R. P., & Garber, P. M. (1984). Collapsing Exchange Rate Regimes. Journal of International Economic, 1-13.
Kibritçioğlu, A. (2002). Excessive risk-taking, banking sector fragility, and banking crises. U of Illinois, Commerce and Bus. Admin. Working Paper (02-0114).
Kruege, M., Osakwe, P. N., & Page, J. (1998). Fundamentals, Contagion and Currency Crises. Bank of Canada Working Paper, 1-36.
Krugman, P. (1979). A Model of Balance of Payment Crises. Journal of Money, Credit, and Banking 11(3), 311-325.
Mahmood, H., Waheed, A., & Khalid, S. (2014). Role of Macroeconomic Indicators in Banking Crisis. Academic Research International, 2, 205-213.
Marthini, Latifa., & Mahfud, M.K (2012). Analisis Pengaruh rasio CAMEL dan Size terhadap Prediksi Kondisi Bermasalah pada Perbankan. http://eprints.undip.ac.id/35674/1/analisis_pengaruh_rasio_CAMEL_dan_Size_terhadap_Prediksi_kon.pdf. 1-29
Monila, C. A. (2002). Predicting Bank Failures Using A Hazard Model: The Vanezuelan Banking Crisis. Emerging Market Review, 31-50.
Männasoo, K., & Mayes, D. G. (2005). Investigating the Early Signals of Banking Sector Vulnerabilities in Central and Eastern European Emerging Markets. Working Papers of Eesti Pank, 8.
Musdholifah. (2015). Using Index For Predicting Banking Crisis In Asian Countries. International Journal of Empirical Finance, 4(3), 170-183.
Musdholifah, Ismail, M., Kaluge, D., & Maskie, G. (2013). Predicting Banking Crisis in Six Asian Countries. European Journal of Business and Management, 5(28), 176-184.
Obstfeld, M., & K. Rogoff. (1986). Ruling Out Divergent Speculative Bubbles. Journal of Monetary Economics, 17 (3):349-362.
Oktavilia, S. (2008). Deteksi Dini Krisis Perbankan Indonesia: Identifikasi Variabel Makro dengan Model Logit. JEJAK, 1(1), 50-62.
Papi, L., Presbitero, A. F., & Zazzaro, A. (2013). IMF Lending and Banking Crisis. IMF Working paper, 2-32.
Poghasyan, T., & Cihak, M. (2009). Distress in European Banks: An Analysis Based on a New Data Set. IMF Working Paper, 3-26.
Roy, S., & Kemme, D. M. (2012). Causes Of Banking Crises: Deregulation, Credit Booms And Asset Bubbles, Then And Now. International Review of Economics and Finance, 24, 270-194.
Sahut, J.-M., & Mili, M. (2011). Banking Distress in MENA Countries and the Role of Merger as Strategic Policeto Resolve Distress. Economic Modeling, 138-146.
Shehzad, C. T., & Haan, J. D. (2000, Desember 3). Financial Reform and Banking Crises. Casifo working paper, pp. 1-14.
Tatom, J. (2011). Predicting Failure In The Commercial Banking Crisis. Munich Personal RePEc Archive, 2-31.
Wong, J., Wong, T.-C., & Leung, P. (2010). Predicting Banking Distress In The EMEAP Economies. Journal of Financial Stability, 6, 169-179.
