IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/31341.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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.

Suggested Citation

  • Santos, Carlos, 2011. "The euro sovereign debt crisis, determinants of default probabilities and implied ratings in the CDS market: an econometric analysis," MPRA Paper 31341, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:31341
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/31341/1/MPRA_paper_31341.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Lee, Myoung-jae, 1992. "Median regression for ordered discrete response," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 59-77.
    3. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
    4. 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.
    5. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    6. Carlos Santos & David Hendry & Soren Johansen, 2008. "Automatic selection of indicators in a fully saturated regression," Computational Statistics, Springer, vol. 23(2), pages 317-335, April.
    7. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    8. Hausman, Jerry A. & Lo, Andrew W. & MacKinlay, A. Craig, 1992. "An ordered probit analysis of transaction stock prices," Journal of Financial Economics, Elsevier, vol. 31(3), pages 319-379, June.
    9. Manganelli, Simone & White, Halbert & Kim, Tae-Hwan, 2008. "Modeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR," Working Paper Series 957, European Central Bank.
    10. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, January.
    11. 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.
    12. 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.
    13. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    14. Santos, Carlos, 2008. "Impulse saturation break tests," Economics Letters, Elsevier, vol. 98(2), pages 136-143, February.
    15. Richard Cantor & Frank Packer, 1996. "Determinants and impact of sovereign credit ratings," Economic Policy Review, Federal Reserve Bank of New York, vol. 2(Oct), pages 37-53.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Songnian, 2019. "Quantile regression for duration models with time-varying regressors," Journal of Econometrics, Elsevier, vol. 209(1), pages 1-17.
    2. John Geweke & Joel Horowitz & M. Hashem Pesaran, 2006. "Econometrics: A Bird’s Eye View," CESifo Working Paper Series 1870, CESifo.
    3. Mickaël De Backer & Anouar El Ghouch & Ingrid Van Keilegom, 2020. "Linear censored quantile regression: A novel minimum‐distance approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1275-1306, December.
    4. Elke Lüdemann & Ralf Wilke & Xuan Zhang, 2006. "Censored quantile regressions and the length of unemployment periods in West Germany," Empirical Economics, Springer, vol. 31(4), pages 1003-1024, November.
    5. Xuejun Jiang & Yunxian Li & Aijun Yang & Ruowei Zhou, 2020. "Bayesian semiparametric quantile regression modeling for estimating earthquake fatality risk," Empirical Economics, Springer, vol. 58(5), pages 2085-2103, May.
    6. Chen, Songnian, 2010. "An integrated maximum score estimator for a generalized censored quantile regression model," Journal of Econometrics, Elsevier, vol. 155(1), pages 90-98, March.
    7. De Backer, Mickael & El Ghouch, Anouar & Van Keilegom, Ingrid, 2017. "An Adapted Loss Function for Censored Quantile Regression," LIDAM Discussion Papers ISBA 2017003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Jiang, Rong & Qian, Weimin & Zhou, Zhangong, 2012. "Variable selection and coefficient estimation via composite quantile regression with randomly censored data," Statistics & Probability Letters, Elsevier, vol. 82(2), pages 308-317.
    9. Khan, Shakeeb & Powell, James L., 2001. "Two-step estimation of semiparametric censored regression models," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 73-110, July.
    10. Sibelle Diniz & Ana Machado, 2011. "Analysis of the consumption of artistic-cultural goods and services in Brazil," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 35(1), pages 1-18, February.
    11. Bernd Fitzenberger & Ralf Wilke, 2006. "Using quantile regression for duration analysis," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 105-120, March.
    12. João Santos Silva, 2019. "Quantile regression: Basics and recent advances," London Stata Conference 2019 27, Stata Users Group.
    13. Steven Lehrer & Gregory Kordas, 2013. "Matching using semiparametric propensity scores," Empirical Economics, Springer, vol. 44(1), pages 13-45, February.
    14. Moreira S & Pita Barros P, 2009. "Double coverage and demand for health care: Evidence from quantile regression," Health, Econometrics and Data Group (HEDG) Working Papers 09/21, HEDG, c/o Department of Economics, University of York.
    15. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Li, Tong & Oka, Tatsushi, 2015. "Set identification of the censored quantile regression model for short panels with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 363-377.
    17. Schmidt, Christoph M. & Tauchmann, Harald, 2011. "Heterogeneity in the intergenerational transmission of alcohol consumption: A quantile regression approach," Journal of Health Economics, Elsevier, vol. 30(1), pages 33-42, January.
    18. Eliana Christou & Michael G. Akritas, 2019. "Single index quantile regression for censored data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 655-678, December.
    19. Marcelo Cajias & Philipp Freudenreich & Anna Freudenreich, 2020. "Exploring the determinants of real estate liquidity from an alternative perspective: censored quantile regression in real estate research," Journal of Business Economics, Springer, vol. 90(7), pages 1057-1086, August.
    20. Xiaofeng Lv & Gupeng Zhang & Xinkuo Xu & Qinghai Li, 2019. "Weighted quantile regression for censored data with application to export duration data," Statistical Papers, Springer, vol. 60(4), pages 1161-1192, August.

    More about this item

    Keywords

    sovereign debt; Euro Area; Credit Default Swaps; Quantile Regression; Ordered Probit; savings rate;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • H63 - Public Economics - - National Budget, Deficit, and Debt - - - Debt; Debt Management; Sovereign Debt
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:31341. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.