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Ülke Kredi Notlarını Etkileyen Faktörlerin Çeşitli Sınıflandırma Analizleri ile İncelenmesi

Author

Listed:
  • Ayşe Mine ÖRENDER

    (Marmara Üniversitesi, Sosyal Bilimler Enstitüsü, İstatistik Tezli Yüksek Lisans Programı, İstanbul, Türkiye)

  • Selay GİRAY YAKUT

    (Marmara Üniversitesi, İktisat Fakültesi, Ekonometri Bölümü, İstatistik Anabilim Dalı, İstanbul, Türkiye)

Abstract

Kredi derecelendirmeleri, Standard and Poor’s Corporation, Moody’s Yatırımcı Servisi ve Fitch Ratings gibi uluslararası derecelendirme kuruluşları tarafından sağlanan kredi riskinin alfabetik göstergeleridir. Kredi notları hükümetlerin kamu borcunu zamanında geri ödeme kabiliyetinin ve istekliliğinin bir değerlendirmesi olduğundan, yatırımcılar, borç veren kuruluşlar ve ilgili piyasa katılımcıları, yayınlanan raporlar doğrultusunda yatırım kararları alabilmektedir. Bu nedenle verilen notlar oldukça önemlidir. Bu çalışmada, 85 ülkenin 2017 yılına ait verisi için lojistik regresyon analizi ve yapay sinir ağları tekniklerinden yararlanılarak Moody’s kredi derecelendirme kuruluşunun ülke kredi notlarını verirken baskın olarak hangi faktörleri ele aldığı belirlenmiş ve verilen kredi notlarına göre ülkeler yatırım yapılabilirlik durumuna göre sınıflara ayrılmıştır. Analiz sonucunda, kişi başına düşen gayrisafi yurtiçi hasıla (GSYİH), enflasyon, genel hükümet faiz dışı dengesi / GSYİH, devlet borcu, dış ödemeler ve resmi Forex rezervleri değişkenleri istatistiksel olarak anlamlı bulunmuş, lojistik regresyon modelinin doğru sınıflandırma oranının %90,6 ve yapay sinir ağları modelinin doğru sınıflandırma oranının %88 olduğu sonucuna varılmıştır. Türkiye zaman zaman yatırım “yapılabilir ülkeler” kategorisinde yer alsa da, kredi derecelendirme kuruluşu Moody’s, 2018 Ağustos ayında Türkiye’nin kredi notunu Ba2’den Ba3’e, 2019 Haziran ayında ise B1’e düşürerek not görünümünü durağandan negatife düşürmüştür. Analiz sonucunda da buna paralel olarak kredi notları açısından Türkiye’nin “yatırım yapılamaz” sınıfına dahil edildiği belirlenmiştir.

Suggested Citation

  • Ayşe Mine ÖRENDER & Selay GİRAY YAKUT, 2019. "Ülke Kredi Notlarını Etkileyen Faktörlerin Çeşitli Sınıflandırma Analizleri ile İncelenmesi," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 31(0), pages 77-93, December.
    • Handle: RePEc:ist:ekoist:v:31:y:2019:i:0:p:77-93
    DOI: 10.26650/ekoist.2019.31.0019
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    References listed on IDEAS

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    1. Gabriel Caldas Montes & Diego S. P. Oliveira & Helder Ferreira Mendonça, 2016. "Sovereign Credit Ratings in Developing Economies: New Empirical Assessment," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(4), pages 382-397, October.
    2. Bissoondoyal-Bheenick, Emawtee & Brooks, Robert & Yip, Angela Y.N., 2006. "Determinants of sovereign ratings: A comparison of case-based reasoning and ordered probit approaches," Global Finance Journal, Elsevier, vol. 17(1), pages 136-154, September.
    3. David F. Tennant & Marlon R. Tracey, 2016. "Sovereign Debt and Credit Rating Bias," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-137-39150-6, December.
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