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The euro sovereign debt crisis, determinants of default probabilities and implied ratings in the CDS market: an econometric analysis

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  • Santos, Carlos

Abstract

In this paper we take an innovative econometric look at the Euro Zone Sovereign Debt Crisis. We are particularly interested in understanding which determinants have led investors to ask for higher yields on sovereign debt from the Euro shatter belt. We dismiss the definition of speculation previously used in the literature, on the basis of the irrelevance of Granger Causality as an operational tool for this purpose. Instead, we suggest that speculative behavior would only exist if market assessment would be unrelated to economic fundamentals of such countries. Using a cross section of countries, we improve on the scarce literature on the Econometrics of Credit Default Swap Markets on sovereign debt. Firstly, we use an ordered probit model to determine whether economic fundamentals are driving the implied rating assessments. Secondly, we provide a pioneering application of quantile regression to this domain, to determine which variables matter at different conditional quantiles of the implied default probability distribution. Finally, Fisher’s Z statistic is used to relate bond markets to domestic saving rates. Overall, the different methodologies support the conclusion that the domestic savings rate is lenders’ main concern. Economies with worse saving habits are penalized both in the CDS market, and in the sovereign bonds markets. Notwithstanding, for countries on the top quantiles of the implied default probabilities, public debt and external debt also play a significant role, increasing the likelihood of higher insurance premium in the derivatives market. When looking at the Portuguese Case it seems clear that public policies that fail to take savings into proper account shall always be deemed to fail, as the country had the lowest net savings rate in the EU27 in 2008, followed closely by Greece.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 31341.

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Date of creation: May 2011
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Handle: RePEc:pra:mprapa:31341

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Keywords: sovereign debt; Euro Area; Credit Default Swaps; Quantile Regression; Ordered Probit; savings rate;

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  1. Machado, Jose A.F. & Silva, J. M. C. Santos, 2005. "Quantiles for Counts," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1226-1237, December.
  2. Yannis Bilias & Roger Koenker, 2001. "Quantile regression for duration data: A reappraisal of the Pennsylvania Reemployment Bonus Experiments," Empirical Economics, Springer, vol. 26(1), pages 199-220.
  3. Lee, M.J., 1990. "Median Regression For Ordered Discrete Response," Papers 9-90-11, Pennsylvania State - Department of Economics.
  4. Richard Cantor & Frank Packer, 1996. "Determinants and impacts of sovereign credit ratings," Research Paper 9608, Federal Reserve Bank of New York.
  5. Hausman, J.A. & Lo, A.W. & MacKinlay, A.C., 1991. "An Ordered Probit Analysis of Transaction Stock Prices," Weiss Center Working Papers 26-91, Wharton School - Weiss Center for International Financial Research.
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  7. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
  8. Manski, Charles F., 1985. "Semiparametric analysis of discrete response : Asymptotic properties of the maximum score estimator," Journal of Econometrics, Elsevier, vol. 27(3), pages 313-333, March.
  9. Santos, Carlos, 2008. "Impulse saturation break tests," Economics Letters, Elsevier, vol. 98(2), pages 136-143, February.
  10. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
  11. Koenker R. & Geling O., 2001. "Reappraising Medfly Longevity: A Quantile Regression Survival Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 458-468, June.
  12. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
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