Journals / Maliye Dergisi / 2022 / Cilt: 0 - Sayı: 182

Predicting Financial Stress in Turkey

Türkiye’de Finansal Baskının Öngörülmesi

Pages
30–50
Publication Date
2023-10-16
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

At quarterly frequency, debt service ratio issues signal three quarters before entering into high financial stress regime, whereas industrial production issues signal four quarters before exiting from high financial stress period.

📌 3 Key Takeaways

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Objective & Hypothesis:The aim of this study is to predict financial stress periods in Turkey within the framework of Markov Regime Switching method.
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Key Findings & Data:The results of the empirical analysis indicate that spread between commercial and housing loan interest rates at monthly frequency provides a warning signal four months prior to transition from low financial stress to high financial stress regime.
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Conclusion & Impact:At quarterly frequency, debt service ratio issues signal three quarters before entering into high financial stress regime, whereas industrial production issues signal four quarters before exiting from high financial stress period.
🔬Design:Makale
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The aim of this study is to predict financial stress periods in Turkey within the framework of Markov Regime Switching method. For this study, a new “Turkey Financial Stress Index” was prepared and used as dependent variable to predict regime changes. The results of the empirical analysis indicate that spread between commercial and housing loan interest rates at monthly frequency provides a warning signal four months prior to transition from low financial stress to high financial stress regime. At quarterly frequency, debt service ratio issues signal three quarters before entering into high financial stress regime, whereas industrial production issues signal four quarters before exiting from high financial stress period.

Özet

Bu çalışmanın amacı Türkiye’de finansal baskı dönemlerinin Markov rejim değişimi yöntemi çerçevesinde öngörülmesidir. Bu çalışma için ilk olarak yeni bir “Türkiye Finansal Baskı Endeksi” hazırlanmış ve rejim değişimlerini öngörebilmek adına bağımlı değişken olarak kullanılmıştır. Aylık veriler ile yapılan ampirik analiz sonuçlarına göre, ticari ile konut kredi faiz oranları arasındaki fark değişkeni düşük finansal baskı rejiminden yüksek finansal baskı rejimine geçiş olmadan dört ay önce uyarı sinyali verebilmektedir. Çeyrek dönemlik veriler kullanılarak elde edilen analiz sonuçlarına göre borç servis oranı yüksek finansal baskı rejimine girmeden üç çeyrek önce, sanayi üretimi ise yüksek finansal baskı döneminden çıkmadan dört çeyrek önce sinyal vermektedir.

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Cite This Article

SÖNMEZ, E., KOCAASLAN, Ö. K. (2023). Predicting Financial Stress in Turkey. Maliye Dergisi, Cilt: 0 - Sayı: 182, 30–50. https://ajindex.com/articles/967566

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References (13)

  1. Abiad, A. (2007),
  2. Hidden Markov Models in Finance, Early Warning Systems for Currency Crises: A Regime-Switching Approach, Springer, Boston, MA, 155-184.
  3. Balakrishnan, R., Danninger, S., Tytell, I. ve Elekdağ, S.A. (2009), “The Transmission of Financial Stress from Advanced to Emerging Economies”, IMF Working Paper No. 09/133. Bülbül, H. ve Akgül, I. (2018), “Türkiye Finansal Stres Endeksi ve Markov Rejim Değişim Modeli ile Yüksek Stres Dönemlerinin Belirlenmesi”, Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 13(3), 125-140.
  4. Cardarelli, R., Elekdağ, S.A. ve Lall, S. (2009), “Financial Stress, Downturns, and Recoveries, Downturns, and Recoveries”, IMF Working Paper No. 09/100. Cardarelli, R., Elekdağ, S. ve Lall, S. (2011), “Financial Stress and Economic Contractions”, Journal of Financial Stability, 7(2), 78-97.
  5. Cerra, V. ve Saxena, S.C. (2002), “Contagion, Monsoons, and Domestic Turmoil in Indonesia’s Currency Crisis”, Review of International Economics, 10(1), 36-44.
  6. Cevik, E.I., Dibooğlu, S. ve Kenc, T. (2013), “Measuring Financial Stress in Turkey”, Journal of Policy Modeling, 35(2), 370-383.
  7. Chadwick, M.G. ve Özturk, H. (2019), “Measuring Financial Systemic Stress for Turkey: A Search for the Best Composite Indicator”, Economic Systems, 43(1), 151-172.
  8. Demirgüç-Kunt, A., Detragiache, E. ve Gupta, P. (2006), “Inside the Crisis: An Empirical Analysis of Banking Systems in Distress”, Journal of International Money and Finance, 25(5), 702-718.
  9. Diebold, F.X., Lee, J.H. ve Weinbach, G.C. (1994), Business Cycles: Durations, Dynamics, and Forecasting, “Regime Switching with Time Varying Transition Probabilities”. Duprey, T. ve Klaus, B. (2017), “How to Predict Financial Stress? An Assessment of Markov Switching Models”, ECB Working Paper No. 2057.
  10. Eichengreen, B., Rose, A.K. ve Wyplosz, C. (1994), “Speculative Attacks on Pegged Exchange Rates: An Empirical Exploration with Special Reference to the European Monetary System”, NBER Working Paper. Eichengreen, B., Rose, A.K. ve Wyplosz, C. (1995), “Exchange Market Mayhem: The Antecedents and Aftermath of Speculative Attacks”, Economic Policy, 10(21), 249-312.
  11. Ekinci, A. (2013), “Financial Stress Index for Turkey”, Doğuş Üniversitesi Dergisi, 14(2), 213-229.
  12. European Central Bank (2022), “Country-Level Index of Financial Stress”, https://sdw.ecb.europa.eu/browse.do?node=9693347 (Erişim Tarihi: 30.03.2022)
  13. European Central Bank (2022), “Composite Indicator of Systemic Stress”, https://sdw.ecb.