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Dergiler / Adam Akademi Sosyal Bilimler Dergisi / 2026 / Cilt: 14 Sayı: 1

Kriz Zamanı Sapması: İslami Bankacılık için Çok Terimli Lojistik Regresyon Yöntemi

Crisis Duration Bias: A Multinomial Logit Approach for Islamic Banking

Ayşegül Aytaç(SOCIAL SCIENCES UNIVERSITY OF ANKARA)0000-0001-8086-0091
Sayfa
27–45
Yayın Tarihi
2024-06-30
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Sonuçlar, kriz süresi sapma problemini ve makroekonomik ve bankacılık değişkenlerinin İslami bankaların bankacılık krizlerine karşı olan kırılganlıklarını açıklamada başarılı olduğunu göstermektedir.

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Amaç & Hipotez:Bu çalışmada, İslami bankaların bankacılık krizlerini tahmin edebilmek için bir erken uyarı sistemi oluşturulmuştur.
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Temel Bulgular & Veri:Bu amaçla, açıklayıcı değişkenlerin sakin ve kriz/kriz sonrası dönemlerde farklı seviyelerde olduğu göz önüne alınarak çok terimli lojistik regresyon kullanılmıştır.
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Sonuç & Katkı:Sonuçlar, kriz süresi sapma problemini ve makroekonomik ve bankacılık değişkenlerinin İslami bankaların bankacılık krizlerine karşı olan kırılganlıklarını açıklamada başarılı olduğunu göstermektedir.
🔬Tür:Araştırma Makalesi
📍Kapsam:2006 Verileri
⚙️Değişkenler:Bankacılık Krizi · İslami Bankacılık · Çok Terimli Regresyon Analizi

Özet

Bu çalışmada, İslami bankaların bankacılık krizlerini tahmin edebilmek için bir erken uyarı sistemi oluşturulmuştur. Bu amaçla, açıklayıcı değişkenlerin sakin ve kriz/kriz sonrası dönemlerde farklı seviyelerde olduğu göz önüne alınarak çok terimli lojistik regresyon kullanılmıştır. Analiz, Bussiere and Fratzscher (2006) ve Caggiano et al. (2016) göz önüne alınarak üç zaman penceresi ile oluşturulmuştur. Buna göre, her ülkedeki İslami Bankalar sakin dönem (Yi,t=0), kırılganlık öncesi dönem (Yi,t=1) ve kırılganlık sonrası dönem (Yi,t=2) dönemlerini deneyimlemektedir. Sonuçlar, kriz süresi sapma problemini ve makroekonomik ve bankacılık değişkenlerinin İslami bankaların bankacılık krizlerine karşı olan kırılganlıklarını açıklamada başarılı olduğunu göstermektedir. Bu çalışma aynı zamanda çok terimli lojistik regresyon ve ikili lojistik regresyon yönteminin genel tahmin başarısına dikkat çekmektedir. Sonuçlara göre, çok değişkenli lojistik regresyon, ikili lojistik regresyona kıyasla daha iyi başarılı tahmin performansı göstermektedir.

Abstract

In this study an early warning system (EWS) model is constructed for predicting the banking crisis (BC) of Islamic banks (IBs). To this aim, multinomial logit regression is employed regarding the levels of the explanatory variables are different in their tranquil and crisis/post-crisis levels which is called as the crisis duration bias (CDB). The analysis is conducted with three time windows following Bussiere and Fratzscher (2006) and Caggiano et al. (2016). Accordingly, the IBs in each country experiences three states as tranquil period (Yi,t=0), a pre-fragility period (Yi,t=1) and post-fragility period (Yi,t=2). The results address CDB problem and both macroeconomic and banking sector variables are crucial in determining the early warning indicators of the fragility of IBs. This study also draws attention to predictive performances of binomial logit approach and multinomial logit approach. According to the results, the overall predictive performance of the multinomial logit regression reveals superior results than binomial logit regression.

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Bu Makaleye Atıf Yap

Aytaç, A. (2024). Kriz Zamanı Sapması: İslami Bankacılık için Çok Terimli Lojistik Regresyon Yöntemi. Adam Akademi Sosyal Bilimler Dergisi, Cilt: 14 Sayı: 1, 27–45. https://doi.org/10.31679/adamakademi.1261323

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Kaynakça (53)

  1. Abduh, M., Omar, M. O. & J. Duasa (2011), The Impact of Crisis and Macroeconomic Variables Towards Islamic Banking Deposits. American Journal of Applied Sciences, 8, 1413-1418.
  2. Abduh, M. and Y. Idrees. (2013). Determinants of Islamic Banking Profitability in Malaysia. Australian Journal of Basic and Applied Sciences, 7, 204-210.
  3. Alaeddin, O, Dakash, M. Al &Azrak, T. (2021). Implementing the Blockchain Technology in Islamic Financial Industry: Opportunities and Challenges. Journal of Information Technology Management. 13, 99-115.
  4. Al Sharif, B. M. (2021). Impact of Real Exchange Rate and Real Interest Rate on Islamic Bank’ Performance: An Empirical Study. Indian Journal of Economics and Business, 20, 445- 460.
  5. Amba, M. S. &F. Almukharreq (2013). Impact of the Financial Crisis on Profitability of the IBs vs Conventional Banks- Evidence from GCC. International Journal of Financial Research, 4, doi: 10.5430/ijfr.v4n3p83.
  6. Angkinand, A. P. &T. D. Willett (2011). Exchange Rate Regimes and BCs: The Channels of Influence Investigated. International Journal of Finance and Economics, 16, 256–274.
  7. Ansari, S., &A. Rehman (2012). Financial Performance of Islamic And Conventional Banks in Pakistan: A comparative study. In 8th international conference on Islamic economics and finance, 11, 2017.
  8. Anwar, S. &M. Hasan (2018). Anns-Based Early Warning System for Indonesian IBs. Buletin Ekonomi Moneter dan Perbankan, 20, 326-342.
  9. Arora, R. U (2012). Financial Inclusion and Human Capital in Developing Asia: The Australian Connection. Third World Quarterly, 33, 179-199.
  10. Asutay, M. &H. Izar (2007). Estimating the Profitability of Islamic Banking: Evidence from Bank Muamalat Indonesia. Review of Islamic Economics, 11, 17-29.
  11. Azrak, Tawfik &H. Hazaa (2019). The Profit/Gain from Islamic Law of Contract Perspective and The Issue of Ownership Risk (Daman al‐Milkiyyah). Journal of Islamic Finance, 10, 111-116.
  12. Babecký, J., Havránek, T., Matějů, J., Rusnák, M., Šmídková &K., Vašíček, B. (2012). Leading Indicators of Crisis Incidence Evidence from Developed Countries. Working Paper Series No 1486, European Central Bank, Frankfurt.
  13. Bashir, A. H (2003). Determinants of Profitability in IBs: Some Evidence from the Middle East. Islamic Economic Studies, 11, 31-57.
  14. Beck, T., Demirgüç-Kunt, A. &O. Merrouche (2013). Islamic vs. conventional banking: Business model, efficiency and stability. Journal of Banking & Finance, 37, 433-447.
  15. Bourke, P (1989). Concentration and Other Determinants of Bank Profitability In Europe, North America And Australia. Journal of Banking&Finance, 13, 65-79.
  16. Bussiere, M. &M. Fratzscher (2006). Towards A New Early Warning System of Financial Crises. Elsevier Journal of International Money and Finance, 25, 953-973.
  17. Caggiano, G., Calice, P. &L. Leonida (2014). Early Warning Systems and Systemic BCs in Low Income Countries: A Multinomial Logit Approach. Journal of Banking & Finance. 27, 258-269.
  18. Chowdhury, M.A.F. &M.E.S.M. Rasid (2016). Determinants of Performance of IBs in GCC Countries: Dynamic GMM Approach. Emerald Group Publishing Limited, Bingley.
  19. Davis, E. P. &D. Karim (2008). Comparing Early Warning Systems for BCs. Journal of Financial Stability, 4, 89–120, doi:10.1016/j.jfs.2007.12.004.
  20. Demirgüç-Kunt, A. &E. Detragiache (1998). The Determinants of BCs in Developing and Developed Countries. IMF Staff Papers, 45, 81–109.
  21. Drehmann, M. &M. Juselius (2014). Evaluating Early Warning Indicators of BCs: Satisfying Policy Requirements. International Journal of Forecasting, 30, 759-780.
  22. Du Plessis, E (2022). Multinomial Modeling Methods: Predicting Four Decades of International BCs. Economic Systems, doi: 10.1016/j.ecosys.2022.100979.
  23. Ekinci, R. &G. Poyraz (2019). The Effect of Credit Risk on Financial Performance of Deposit Banks in Turkey. Procedia Computer Science, 158, 979–987.
  24. Elgari, M. A. (2003). Credit Risk in Islamic Banking and Finance. Islamic Economic Studies, 10, 1-25.
  25. Fakhrunnas, F., Tumewang, Y. K. &M. B. H. Anto (2021). The Impact of Inflation on IBs’ Home Financing Risk: Before and During the Covid-19 Outbreak. Banks and Banks Systems, 16, 78-90.
  26. Frydl, E. J (1999). The Length and Cost of BCs. IMF Working Paper, International Monetary Fund, New York, NY.
  27. Grier, W. A (2012). Credit Analysis of Financial Institutions, Euromoney Books, London.
  28. Hardy, D.C. &C. Pazarbaşıoğlu (1998). Leading Indicators of BCs: Was Asia Different?” IMF Staff Papers, 46, 247-258.
  29. Hasan, M. &J. Dridi (2011). The Effects of the Global Crisis on Islamic and Conventional Banks: A Comparative Study. Journal of International Commerce, Economics and Policy, 02, 163–200, doi:10.1142/s1793993311000270.
  30. Hays, H., De Lurgio, A. &A. Gilbert (2008). Efficiency Ratios and Community Bank Performance. Journal of Finance and Accountancy, 1, 1-15.
  31. Heffernan, S. A. &X. Fu (2010). Determinants of Financial Performance in Chinese Banking. Applied Financial Economics, 20, 1585-1600.
  32. Hoggarth, G., Reis, R. &V. Saporta (2002). Costs of Banking System Instability: Some Empirical Evidence. Journal of Banking and Finance, 26, pp. 825–855, doi:10.1016/S0378-4266(01)00268-0.
  33. Hussien, M.E., Alam, M.M., Murad, M.W. & Wahid, A.N.M. (2019). The Performance of Islamic Banks during the 2008 Global Financial Crisis: Evidence from the Gulf Cooperation Council Countries. Journal of Islamic Accounting and Business Research, 10(3), 407-420.
  34. Kaminsky, G. L. &C. M. Reinhart (1999). The Twin Crises: The Causes of Banking and Balance-Of-Payments Problems. American Economic Review, 89, pp. 473–500. doi:10.1257/aer.89.3.473.
  35. Khan, T. &H. Ahmed (2001). Risk Management: An Analysis of Issue in Islamic Financial Industry, Occasional Papers 91, The Islamic Research and Teaching Institute (IRTI), Jeddah.
  36. Kibritçioğlu, A., (2003). Monitoring Banking Sector Fragility. The Arab Bank Review, 5, 51-66.
  37. Kindleberger, C. &R. Aliber (2005). Manias, Panics and Crashes A History of Financial Crises, Palgrave Macmillan, London.
  38. Kozarevic, E., Nurikic Barakovic, M. &S. Nuhanovic (2014). Specifics of Risk Management In Islamic Finance And Banking, With Emphasis On Bosnia And Herzegovina. Çankırı Karatekin University Journal of The Faculty of Economics and Administrative Sciences, 4, 151-166.
  39. Kusuma, D. B. &J. Duasa (2016). Building an Early Warning Towards: The Resilience Of Islamic Banking In Indonesia. Al-Iqtishad: Journal of Islamic Economics, 9, 13-32.
  40. Moin, M.S (2008). Performance of Islamic Banking and Conventional banking in Pakistan. International Journal of Innovative and Applied Finance, 3, pp. 419-433.
  41. Nurfalah, I., Rusydiana, A.S., Laila, N. &E.F. Cahyono (2018). Early Warning to BCs in the Dual Financial System in Indonesia: The Markov Switching Approach. JKAU: Islamic Economics, 31, pp. 133-156.
  42. Pereira Pedro, C., Ramalho, J. J. S. &J. V. da Silva (2018). The Main Determinants of BCs in OECD Countries. Review of World Economics, 154, 203–227.
  43. Perry, P. (1992). Do Banks Gain or Lose from Inflation?. Journal of Retail Banking, 14, 25-30.
  44. Rashwan, M.H (2012). How did listed Islamic and traditional banks Perform: Pre and post 2008 financial crisis?” Journal of Applied Finance and Banking, 2, 149-175.
  45. Rehman, R. &A. Rashid (2021). Impacts of Bank-Specific and Macroeconomic Risks on Growth and Stability of Islamic and Conventional Banks: An Empirical Analysis from Pakistan. Journal of Asian Finance, Economics and Business, 9, doi: 10.13106/jafeb.2022.vol9.no2.0001.
  46. ICD - Thomson Reuters Islamic Finance Development Report (2021). Islamic Finance Development Report 2021: Advancing Economies. Thomson Reuters.
  47. Salim, R., Arjomandi, A. &K. H. Dakpo (2017). Banks’ Efficiency and Credit Risk Analysis Using By-Production Approach: The Case of Iranian Banks. Applied Economics, 49, 2974–2988.
  48. Solarin, S. A., Hammoudeh, S. &M. Shahbaz (2018). Influence of Economic Factors on Disaggregated Islamic Banking Deposits: Evidence with Structural Breaks in Malaysia. Journal of International Financial Markets, Institutions, and Money, 55, 13–28.
  49. Srouji, A.F., M.S.Ab. Halim, Z. Lubis &M. Hamdella. (2015). Assesment od IBs Profitability Ratios-Evidence from Jordan. International Journal of Recent Advances in Multidisciplinary Research, 02, 887-891. Srairi, Samir Abderrazek. (2009) "Factors Influencing the Profitability of Conventional and Islamic Commercial Banks in GCC Countries", Review of Islamic Economics, Vol. 13, No. 1, 5-30.
  50. Tabash, M. I. &S. Anagreh (2017). Do IBs Contribute to Growth Of The Economy? Evidence from United Arab Emirates (UAE). Banks and Bank Systems, 12, 113–118.
  51. Tok, E. &A. J. Yesuf (2022). Embedding Value-Based Principles in the Culture of IBs to Enhance Their Sustainability, Resilience, and Social Impact. Sustainability, 14, doi: 10.3390/su14020916.
  52. Uddin, A., Chowdhury, M.A.F., and Islam, M.N. (2019). Resiliency Between Islamic and Conventional Banks In Bangladesh: Dynamic GMM and Quantile Regression Approaches. Journal of Islamic Accounting and Business Research, 10(4), 657-676.
  53. Von Hagen, J. &T. K. Ho (2007). Money Market Pressure and The Determinants of BCs. Journal of Money, Credit and Banking, 39, 1037–1066.