Determinants of Sovereign Credit Ratings for Advanced and Developing Economies: Ordered Response Models
Öz
In this study, macroeconomic indicators affecting the sovereign credit ratings assigned by S&P are analyzed using ordered probit, random effects ordered probit and random effects ordered probit models with unit averages over time. Annual data of 87 countries, including 34 advanced and 53 developing economies, for the period 2009-2018 are used. Analyses are conducted separately for all countries, developing economies and advanced economies. According to the findings, the average of governance indicators, GDP per capita, growth rate, unemployment rate, inflation rate, current account balance, savings, borrowings and spendings are important macroeconomic indicators. When the percentages of correct predictions of the models are compared, all three models perform best for advanced economies. Among the three models, the best performance with a margin of error of ±4 is obtained with the random effects ordered probit model with unit averages over time.
Anahtar Kelimeler
Credit rating Standard and Poor’s random effects ordered probit sovereign credit ratings
Kaynakça
- Afonso, A. (2003). Understanding the determinants of sovereign debt ratings: Evidence for the two leading agencies. Journal of Economics and Finance, 27(1), 56-74.
- Afonso, A., Gomes, P., & Rother, P. (2009). Ordered response models for sovereign debt ratings. Applied Economics Letters, 16(8), 769-773.
- Afonso, A., Gomes, P., & Rother, P. (2011). Short‐and long‐run determinants of sovereign debt credit ratings. International Journal of Finance & Economics, 16(1), 1-15.
- Alexe, S., Hammer, P. L., Kogan, A., & Lejeune, M. A. (2003). A non-recursive regression model for country risk rating. RUTCOR-Rutgers University Research Report RRR, 9, 1-40.
- Bissoondoyal-Bheenick, E. (2005). An analysis of the determinants of sovereign ratings. Global Finance Journal, 15(3), 251-280.
- Brewer, T. L., & Rivoli, P. (1990). Politics and perceived country creditworthiness in international banking. Journal of Money, Credit and Banking, 22(3), 357-369.
- Butler, A. W., & Fauver, L. (2006). Institutional environment and sovereign credit ratings. Financial Management, 35(3), 53-79.
- Cantor, R., & Packer, F. (1996). Determinants and impact of sovereign credit ratings. Economic policy review, 2(2).
- Cosset, J. C., & Roy, J. (1991). The determinants of country risk ratings. Journal of International Business Studies, 22(1), 135-142.
- De Moor, L., Luitel, P., Sercu, P., & Vanpée, R. (2018). Subjectivity in sovereign credit ratings. Journal of Banking & Finance, 88, 366-392.
- Depken, C., LaFountain, C., & Butters, R. (2007). Corruption and creditworthiness: evidence from sovereign credit ratings. Working Papers 0601, Department of Economics, University of Texas at Arlington.
- Duygun, M., Ozturk, H., Shaban, M., & Tortosa-Ausina, E. (2014). Quo Vadis, raters? A frontier approach to identify misratings in sovereign credit risk (No. 2014/10).
- Eliasson, A. C. (2002). Sovereign credit ratings (No. 02-1). Research Notes.
- Erdem, O., & Varli, Y. (2014). Understanding the sovereign credit ratings of emerging markets. Emerging Markets Review, 20, 42-57.
- Gültekin-Karakaş, D., Hisarcıklılar, M., & Öztürk, H. (2011). Sovereign risk ratings: Biased toward developed countries?. Emerging Markets Finance and Trade, 47(sup2), 69-87.
- Haspolat, F. B. (2015). Analysis of Moody's sovereign credit ratings: criticisms towards rating agencies are still valid?. Procedia Economics and Finance, 30, 283-293.
- Hill, P., Brooks, R., & Faff, R. (2010). Variations in sovereign credit quality assessments across rating agencies. Journal of Banking & Finance, 34(6), 1327-1343.
- Hu, Y. T., Kiesel, R., & Perraudin, W. (2002). The estimation of transition matrices for sovereign credit ratings. Journal of Banking & Finance, 26(7), 1383-1406.
- Longhi, S., & Nandi, A. (2015). A Practical guide to using panel data. Sage.
- Mellios, C., & Paget-Blanc, E. (2006). Which factors determine sovereign credit ratings?. The European Journal of Finance, 12(4), 361-377.
- Monfort, B., & Mulder, C. (2000). Using credit ratings for capital requirements on lending to emerging market economies: possible impact of a new Basel accord. IMF Working Papers 00/69.
- Mundlak, Y. (1978). On the pooling of time series and cross section data. Econometrica: journal of the Econometric Society, 69-85.
- Overes, B. H., & van der Wel, M. (2022). Modelling sovereign credit ratings: Evaluating the accuracy and driving factors using machine learning techniques. Computational Economics, 1-31.
- Öztürk, H. (2014). The origin of bias in sovereign credit ratings: Reconciling agency views with institutional quality. The Journal of Developing Areas, 161-188.
- Öztürk, H., Namli, E., & Erdal, H. I. (2016). Modelling sovereign credit ratings: The accuracy of models in a heterogeneous sample. Economic Modelling, 54, 469-478.
- Sandström, A. (2008). Political risk in credit evaluation: Empirical studies and survey results. Ph.D. dissertation, Swedish School of Economics and Business Administration, Helsinki.
- SEC. (2020). Annual report on nationally recognized statistical rating organizations. US. https://www.sec.gov/files/2019-annual-report-on-nrsros.pdf.
- Takawira, O., & Mwamba, W. M. (2020). Determinants of sovereign credit ratings: An application of the Naïve Bayes Classifier. Eurasian Journal of Economics and Finance, 8(4), 279-299.
Gelişmiş ve Gelişmekte Olan Ekonomiler İçin Ülke Kredi Notlarının Belirleyicileri: Sıralı Tercih Modelleri
Öz
Çalışmada S&P tarafından verilen ülke kredi notlarını etkileyen makroekonomik göstergeler; sıralı probit, tesadüfi etkiler sıralı probit ve zamana göre birim ortalamaları ile tesadüfi etkiler sıralı probit modeller ile araştırılmaktadır. 34 gelişmiş ve 53 gelişmekte olan ekonomi olmak üzere toplam 87 ülkenin 2009-2018 dönemi yıllık verileri kullanılmaktadır. Analizler tüm ülkeler, gelişmekte olan ekonomiler ve gelişmiş ekonomiler için ayrı ayrı uygulanmaktadır. Elde edilen bulgulara göre yönetim göstergeleri ortalaması, kişi başına GSYİH, büyüme oranı, işsizlik oranı, enflasyon oranı, cari denge, tasarruflar, borçlanma ve harcama önemli makroekonomik göstergelerdir. Kullanılan modellerin doğru tahmin yüzdeleri kıyaslandığında üç model de en iyi performansı gelişmiş ekonomiler için göstermektedir. Üç model içerisinde ±4 hata payına göre en iyi performans ise zamana göre birim ortalamaları ile tesadüfi etkiler sıralı probit model ile elde edilmektedir.
Anahtar Kelimeler
kredi derecelendirme Standard and Poor tesadüfi etkiler sıralı probit ülke kredi notu.
Kaynakça
- Afonso, A. (2003). Understanding the determinants of sovereign debt ratings: Evidence for the two leading agencies. Journal of Economics and Finance, 27(1), 56-74.
- Afonso, A., Gomes, P., & Rother, P. (2009). Ordered response models for sovereign debt ratings. Applied Economics Letters, 16(8), 769-773.
- Afonso, A., Gomes, P., & Rother, P. (2011). Short‐and long‐run determinants of sovereign debt credit ratings. International Journal of Finance & Economics, 16(1), 1-15.
- Alexe, S., Hammer, P. L., Kogan, A., & Lejeune, M. A. (2003). A non-recursive regression model for country risk rating. RUTCOR-Rutgers University Research Report RRR, 9, 1-40.
- Bissoondoyal-Bheenick, E. (2005). An analysis of the determinants of sovereign ratings. Global Finance Journal, 15(3), 251-280.
- Brewer, T. L., & Rivoli, P. (1990). Politics and perceived country creditworthiness in international banking. Journal of Money, Credit and Banking, 22(3), 357-369.
- Butler, A. W., & Fauver, L. (2006). Institutional environment and sovereign credit ratings. Financial Management, 35(3), 53-79.
- Cantor, R., & Packer, F. (1996). Determinants and impact of sovereign credit ratings. Economic policy review, 2(2).
- Cosset, J. C., & Roy, J. (1991). The determinants of country risk ratings. Journal of International Business Studies, 22(1), 135-142.
- De Moor, L., Luitel, P., Sercu, P., & Vanpée, R. (2018). Subjectivity in sovereign credit ratings. Journal of Banking & Finance, 88, 366-392.
- Depken, C., LaFountain, C., & Butters, R. (2007). Corruption and creditworthiness: evidence from sovereign credit ratings. Working Papers 0601, Department of Economics, University of Texas at Arlington.
- Duygun, M., Ozturk, H., Shaban, M., & Tortosa-Ausina, E. (2014). Quo Vadis, raters? A frontier approach to identify misratings in sovereign credit risk (No. 2014/10).
- Eliasson, A. C. (2002). Sovereign credit ratings (No. 02-1). Research Notes.
- Erdem, O., & Varli, Y. (2014). Understanding the sovereign credit ratings of emerging markets. Emerging Markets Review, 20, 42-57.
- Gültekin-Karakaş, D., Hisarcıklılar, M., & Öztürk, H. (2011). Sovereign risk ratings: Biased toward developed countries?. Emerging Markets Finance and Trade, 47(sup2), 69-87.
- Haspolat, F. B. (2015). Analysis of Moody's sovereign credit ratings: criticisms towards rating agencies are still valid?. Procedia Economics and Finance, 30, 283-293.
- Hill, P., Brooks, R., & Faff, R. (2010). Variations in sovereign credit quality assessments across rating agencies. Journal of Banking & Finance, 34(6), 1327-1343.
- Hu, Y. T., Kiesel, R., & Perraudin, W. (2002). The estimation of transition matrices for sovereign credit ratings. Journal of Banking & Finance, 26(7), 1383-1406.
- Longhi, S., & Nandi, A. (2015). A Practical guide to using panel data. Sage.
- Mellios, C., & Paget-Blanc, E. (2006). Which factors determine sovereign credit ratings?. The European Journal of Finance, 12(4), 361-377.
- Monfort, B., & Mulder, C. (2000). Using credit ratings for capital requirements on lending to emerging market economies: possible impact of a new Basel accord. IMF Working Papers 00/69.
- Mundlak, Y. (1978). On the pooling of time series and cross section data. Econometrica: journal of the Econometric Society, 69-85.
- Overes, B. H., & van der Wel, M. (2022). Modelling sovereign credit ratings: Evaluating the accuracy and driving factors using machine learning techniques. Computational Economics, 1-31.
- Öztürk, H. (2014). The origin of bias in sovereign credit ratings: Reconciling agency views with institutional quality. The Journal of Developing Areas, 161-188.
- Öztürk, H., Namli, E., & Erdal, H. I. (2016). Modelling sovereign credit ratings: The accuracy of models in a heterogeneous sample. Economic Modelling, 54, 469-478.
- Sandström, A. (2008). Political risk in credit evaluation: Empirical studies and survey results. Ph.D. dissertation, Swedish School of Economics and Business Administration, Helsinki.
- SEC. (2020). Annual report on nationally recognized statistical rating organizations. US. https://www.sec.gov/files/2019-annual-report-on-nrsros.pdf.
- Takawira, O., & Mwamba, W. M. (2020). Determinants of sovereign credit ratings: An application of the Naïve Bayes Classifier. Eurasian Journal of Economics and Finance, 8(4), 279-299.
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Ekonometrik ve İstatistiksel Yöntemler, Ekonometri (Diğer), Makro İktisat (Diğer) |
| Bölüm | Makaleler |
| Yazarlar | |
| Erken Görünüm Tarihi | 29 Aralık 2023 |
| Yayımlanma Tarihi | 30 Aralık 2023 |
| Gönderilme Tarihi | 26 Temmuz 2023 |
| Yayımlandığı Sayı | Yıl 2023 Cilt: 7 Sayı: 2 |
