Determinants of credit default swaps implied ratings during the crisis: was sovereign risk mispriced?
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Author(s)Maria Alberta OliveiraLink to ORCID Index: https://orcid.org/0000-0003-2918-1354
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Carlos SantosLink to ORCID Index: https://orcid.org/0000-0002-5100-0794
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DOIhttp://dx.doi.org/10.21511/imfi.15(3).2018.01
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Article InfoVolume 15 2018, Issue #3, pp. 1-14
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This paper addresses the question of whether sovereign risk pricing was related to macroeconomic fundamentals, between 2007 and 2015, in a sample of OECD countries. The authors argue that the conflicting evidence in the literature is due to poor methodology options. The researchers innovate by modelling sovereign credit default swaps implied ratings as our sovereign risk proxy, instead of spreads, avoiding common pitfalls. Furthermore, the authors improve the variable selection, model specification and the econometric procedures used. A panel ordered probit model is chosen, assuring robust inference. The authors relax the parallel lines assumption, allowing for rating-varying coefficients of explanatory variables. The result is the first congruent model of sovereign risk during the years of the financial crisis and of the Euro Area crisis. Fiscal space variables, economic activity indicators, variables pertaining to external imbalances, and contagion proxies are relevant, with effects matching theory priors. The scientists clarify conundrums in the previous literature, posed by lack of significance of some macro fundamentals and by puzzling signs of some estimated coefficients. Moreover, this is the first paper to estimate not only the global risk premium, but also the impact of changing risk aversion. The authors find no support for claims of sovereign risk mispricing during the sample period. The results allow relevant policy conclusions, namely concerning the validity of different fiscal consolidation paths in financially distressed countries.
- Keywords
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JEL Classification (Paper profile tab)C23, E44, F34, G01, G12, G15
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References35
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Tables3
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Figures0
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- Table 1. Estimation results: panel ordered probit
- Table A1. Confidence Intervals for αi
- Table A2. Estimation results: panel ordered logit
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- Afonso, A., Arghyrou, M. G., Bagdatoglou, G., & Kontonikas, A. (2015). On the time-varying relationship between EMU sovereign spreads and their determinants. Economic Modelling, 44, 363-371.
- Afonso, A., Gomes, P., & Rother, P. (2007). What “hides” behind sovereign debt ratings? (ECB Working Paper Series, 711).
- Aizenman, J., Hutchison, M., & Jinjarak, Y. (2013). What is the risk of European sovereign debt defaults? Fiscal space, CDS spreads and market pricing of risk. Journal of International Money and Finance, 34, 37-59.
- Arghyrou, M. G., & Kontonikas, A. (2012). The emu sovereign-debt crisis: Fundamentals, expectations and contagion. Journal of International Financial Markets, Institutions and Money, 22(4), 658-677.
- Bahaj, S. A. (2014). Systemic Sovereign Risk: Macroeconomic Implications in the Euro Area (Working Paper 191/2014, Oesterreichische National Bank).
- Bannier, C. E., Heidorn, T., & Vogel, H. D. (2014). Characteristics and development of corporate and sovereign CDS. Journal of Risk Finance, 15(5), 482-509.
- Bärdsen, G., Eitrheim, O., Jansen, E. S., & Nymoen, R. (2005). The Econometrics of Macroeconomic Modelling. Oxford University Press.
- Beirne, J., & Fratzscher, M. (2013). The pricing of sovereign risk and contagion during the European sovereign debt crisis. Journal of International Money and Finance, 34, 60-82.
- Boffelli, S., Skintzi, V. D., & Urga, G. (2017). High- and Low-Frequency Correlations in European Government Bond Spreads and Their Macroeconomic Drivers. Journal of Financial Econometrics, 15, 62-105.
- Borensztein, E., Cowan, K., & Valenzuela, P. (2013). Sovereign Ceilings “Lite”? The Impact of Sovereign Ratings on Corporate Ratings. Journal of Banking & Finance, 37, 4014-4024.
- Bruneau, C., Delatte, A., & Fouquau, J. (2014). Was the European sovereign crisis self-fulfilling? Empirical evidence about the drivers of market sentiments. Journal of Macroeconomics, 42(C), 38-51.
- Caceres, C., Guzzo, V., & Segoviano, M. (2010). Sovereign Spreads: Global Risk Aversion, Contagion or Fundamentals (IMF Working Paper WP/10/120). International Monetary Fund, May.
- Cantor, R., & Packer, F. (1996). Determinants and impact of sovereign credit ratings. Economic Policy Review, 2, 37-53.
- De Santis, R. A. (2016). Impact of the Asset Purchase Programme on Euro Area Government Bond Yields using Market News (Working Paper 1939). European Central Bank.
- Delatte, A. L., Gex, M., & López- Villavicencio, A. (2012). Has the CDS market influenced the borrowing cost of European countries during the sovereign crisis? Journal of International Money and Finance, 481-497.
- Doornik, J. A. (2009). Autometrics. In J. L. Castle and N. Shephard (Eds.), The Methodology and Practice of Econometrics: a Festschrift in honour of David F. Hendry. Oxford University Press.
- Elkamhi, R., Jacobs, K., & Pan, X. (2014). The Cross Section of Recovery Rates and Default Probabilities Implied by Credit Default Swap Spreads. Journal of Financial and Quantitative Analysis, 49(1), 193-220.
- Eliasson, A. (2002). Sovereign credit ratings (Working Papers 02-1). Deutsche Bank.
- Feldhütter, P., & Schaefer, S. (2018). The Myth of the Credit Spreads Puzzle. The Review of Financial Studies, Forthcoming.
- Flannery, M. J., & Hankins, K. W. (2013). Estimating Dynamic Panel Models in Corporate Finance. Journal of Corporate Finance, 19, 1-19.
- Frechette, G. (2001). sg158: Random-effects ordered probit. Stata Technical Bulletin, 59, 23-27. Reprinted in Stata Technical Bulletin Reprints 10, 261-266.
- Heinz, F. F., & Sun, Y. (2014). Sovereign CDS Spreads in Europe – The Role of Global Risk Aversion, Economic Fundamentals, Liquidity, and Spillovers (IMF Working Paper 14/17).
- Heynderickx, W., Cariboni, J., Schoutens, W., & Smits, B. (2016). The relationship between risk-neutral and actual default probabilities: the credit risk premium. Applied Economics, 48(42), 4066-4081.
- Klinger, S., & Lando, D. (2018). Safe Haven CDS premiums. The Review of Financial Studies, Forthcoming.
- Kriz, K., Wang, Q., & Issarachaiyos, S. (2015). Debt burden and perceived sovereign default risk: evidence from credit default swaps. Public Finance and Management, 15(3), 203-224.
- Mas-Colell, A., Whinston, M. D., & Green, J. R. (1995). Microeconomic Theory. Oxford Student Edition.
- Oliveira, L., Curto, J. D., & Nunes, J. P. (2012). The determinants of sovereign credit spread changes in the Euro-zone. Journal of International Financial Markets, Institutions & Money, 22, 278-304.
- Oliveira, M. A., & Santos, C. (2015). Market Exuberance in Sovereign Credit Default Swaps: Assessing the EU Regulatory Framework and Trading Profit Opportunities. Investment Management and Financial Innovations, 12(4), 70-80.
- Paniagua, J., Sapena, J., & Tamarit, C. (2017). Sovereign debt spreads in EMU: The time-varying role of fundamentals and market distrust. Journal of Financial Stability, 33, 187-206.
- Pfarr, C., Schmid, A., & Schneider, U. (2011). Estimating Ordered Categorical Variables using Panel Data: a Generalized Ordered Probit Model with an Autofit Procedure. Journal of Economics and Econometrics, 54(1), 7-23.
- Poon, W. P. H. (2003). Are unsolicited Credit Ratings biased downward? Journal of Banking & Finance, 27, 593-614.
- Santos, C. (2011). The Euro Sovereign Debt Crisis: Determinants of Default Probabilities and Implied Ratings in the CDS Market: An Econometric Analysis. Journal of Advanced Studies in Finance, 2(3), 53-61.
- Williams, R. (2006). Generalized Ordered Logit/Partial Proportional Odds Models for Ordinal Dependent Variables. The Stata Journal, 6(1), 58- 82.
- Williams, R. (2016). Understanding and Interpreting Generalized Ordered Logit Models. The Journal of Mathematical Sociology, 40(1), 7-20.
- Yuan, C., & Pongsiri, T. J. (2015). Fiscal austerity, growth prospects and sovereign CDS spreads: The Eurozone and beyond. International Economics, 141, 50-79.
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ESG-driven approach to managing insurance companies’ sustainable development
Inna Khovrak 
doi: http://dx.doi.org/10.21511/ins.11(1).2020.05
Insurance Markets and Companies Volume 11, 2020 Issue #1 pp. 42-52 Views: 1535 Downloads: 540 TO CITE АНОТАЦІЯEnvironmental, social and governance criteria (ESG) are considered to be the main factors in measuring the sustainability and ethical impact of companies. This article focuses on comparing the ability of insurance companies to use an ESG-driven approach to managing their sustainable development. The study is conducted using comparative analysis, statistical analysis, and a case study method. The study compares six ESG Ratings on four main criteria (dependent variables, independent variables, scale type, sample), that allows choosing the most appropriate rating for the analysis of insurance companies. As a result, 156 insurance companies are compared by the level of ESG risk (low ESG risk – 24 companies, medium ESG risk – 111 companies, high ESG risk – 21 companies) and by geographical affiliation (26 countries) using descriptive statistics. The assessment of effectiveness of the ESG-driven approach to managing sustainable development of insurance companies is carried out on the example of 16 companies by comparing their non-financial reporting (the sample is selected based on of the annual report for 2019-2020). The study identifies the most common guidelines for report development, as well as components of the ESG-driven approach: environmental (waste and pollution, climate change, energy efficiency), social (workforce and diversity, customer engagement, communities), governance (code and values, reporting, risk management). The study systematizes the best practices of insurance companies for applying the ESG-driven approach to manage their sustainable development and highlights the need for insurance companies to improve their reporting and disclosure practices related to the development of the ESG-driven approach.
Acknowledgment
Comments from the Editor and anonymous referees have been gratefully acknowledged.
