IDEAS home Printed from https://ideas.repec.org/a/bla/obuest/v77y2015i1p66-92.html
   My bibliography  Save this article

Fitting and Forecasting Sovereign Defaults using Multiple Risk Signals

Author

Listed:
  • Roberto Savona
  • Marika Vezzoli

Abstract

type="main" xml:id="obes12052-abs-0001"> In this article, we try to realize the best compromise between in-sample goodness of fit and out-of-sample predictability of sovereign defaults. To do this, we use a new regression-tree based approach that signals impending sovereign debt crises whenever pre-selected indicators exceed specific thresholds. Using data from emerging markets and Greece, Ireland, Portugal and Spain (GIPS) over the period 1975–2010, we show that our model significantly outperforms existing competing approaches (logit, stepwise logit, noise-to-signal ratio and regression trees), while balancing in- and out-of-sample performance. Our results indicate that illiquidity (high short-term debt to reserves) and default history, together with real GDP growth and US interest rates, are the main determinants of both emerging market country defaults and the recent European sovereign debt crisis.

Suggested Citation

  • Roberto Savona & Marika Vezzoli, 2015. "Fitting and Forecasting Sovereign Defaults using Multiple Risk Signals," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(1), pages 66-92, February.
  • Handle: RePEc:bla:obuest:v:77:y:2015:i:1:p:66-92
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/obes.2015.77.issue-1
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Graciela L. Kaminsky, 1998. "Currency and banking crises: the early warnings of distress," International Finance Discussion Papers 629, Board of Governors of the Federal Reserve System (U.S.).
    2. Gian Maria Milesi Ferretti & Assaf Razin, 2000. "Current Account Reversals and Currency Crises: Empirical Regularities," NBER Chapters,in: Currency Crises, pages 285-323 National Bureau of Economic Research, Inc.
    3. Glick, Reuven & Rose, Andrew K., 1999. "Contagion and trade: Why are currency crises regional?," Journal of International Money and Finance, Elsevier, vol. 18(4), pages 603-617, August.
    4. Carmen M. Reinhart & Kenneth S. Rogoff & Miguel A. Savastano, 2003. "Debt Intolerance," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 34(1), pages 1-74.
    5. Eichengreen, Barry & Rose, Andrew & Wyplosz, Charles, 1996. " Contagious Currency Crises: First Tests," Scandinavian Journal of Economics, Wiley Blackwell, vol. 98(4), pages 463-484, December.
    6. Gerlach, Stefan & Smets, Frank, 1995. "Contagious speculative attacks," European Journal of Political Economy, Elsevier, vol. 11(1), pages 45-63, March.
    7. Graciela Kaminsky & Saul Lizondo & Carmen M. Reinhart, 1998. "Leading Indicators of Currency Crises," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 1-48, March.
    8. Andrew Berg & Eduardo Borensztein & Catherine Pattillo, 2005. "Assessing Early Warning Systems: How Have They Worked in Practice?," IMF Staff Papers, Palgrave Macmillan, vol. 52(3), pages 1-5.
    9. Frankel, Jeffrey A. & Rose, Andrew K., 1996. "Currency crashes in emerging markets: An empirical treatment," Journal of International Economics, Elsevier, vol. 41(3-4), pages 351-366, November.
    10. Frankel, Jeffrey A. & Rose, Andrew K., 1996. "Currency Crashes in Emerging Markets: Empirical Indicators," Center for International and Development Economics Research (CIDER) Working Papers 233424, University of California-Berkeley, Department of Economics.
    11. repec:wsi:wschap:9789814749589_0011 is not listed on IDEAS
    12. Luis Catão & Sandeep Kapur, 2006. "Volatility and the Debt-Intolerance Paradox," IMF Staff Papers, Palgrave Macmillan, vol. 53(2), pages 1-1.
    13. Dooley, Michael P, 2000. "A Model of Crises in Emerging Markets," Economic Journal, Royal Economic Society, vol. 110(460), pages 256-272, January.
    14. Orrell, David & McSharry, Patrick, 2009. "System economics: Overcoming the pitfalls of forecasting models via a multidisciplinary approach," International Journal of Forecasting, Elsevier, vol. 25(4), pages 734-743, October.
    15. Demirguc, Asli & Detragiache, Enrica, 2000. "Monitoring Banking Sector Fragility: A Multivariate Logit Approach," World Bank Economic Review, World Bank Group, vol. 14(2), pages 287-307, May.
    16. Morris Goldstein & Graciela Kaminsky & Carmen Reinhart, 2017. "Methodology and Empirical Results," World Scientific Book Chapters,in: TRADE CURRENCIES AND FINANCE, chapter 11, pages 397-436 World Scientific Publishing Co. Pte. Ltd..
    17. Cavallo, Eduardo A. & Frankel, Jeffrey A., 2008. "Does openness to trade make countries more vulnerable to sudden stops, or less? Using gravity to establish causality," Journal of International Money and Finance, Elsevier, vol. 27(8), pages 1430-1452, December.
    18. Axel Schimmelpfennig & Nouriel Roubini & Paolo Manasse, 2003. "Predicting Sovereign Debt Crises," IMF Working Papers 03/221, International Monetary Fund.
    19. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423, October.
    20. Merrick Jr., John J., 2001. "Crisis dynamics of implied default recovery ratios: Evidence from Russia and Argentina," Journal of Banking & Finance, Elsevier, vol. 25(10), pages 1921-1939, October.
    21. Oral, Muhittin & Kettani, Ossama & Cosset, Jean-Claude & Daouas, Mohamed, 1992. "An estimation model for country risk rating," International Journal of Forecasting, Elsevier, vol. 8(4), pages 583-593, December.
    22. Austin P.C. & Tu J.V., 2004. "Bootstrap Methods for Developing Predictive Models," The American Statistician, American Statistical Association, vol. 58, pages 131-137, May.
    23. Kaminsky, Graciela L. & Reinhart, Carmen M., 2000. "On crises, contagion, and confusion," Journal of International Economics, Elsevier, vol. 51(1), pages 145-168, June.
    24. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    25. Fuertes, Ana-Maria & Kalotychou, Elena, 2006. "Early warning systems for sovereign debt crises: The role of heterogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1420-1441, November.
    26. Fuertes, Ana-Maria & Kalotychou, Elena, 2007. "Optimal design of early warning systems for sovereign debt crises," International Journal of Forecasting, Elsevier, vol. 23(1), pages 85-100.
    27. Van Rijckeghem, Caroline & Weder, Beatrice, 2001. "Sources of contagion: is it finance or trade?," Journal of International Economics, Elsevier, vol. 54(2), pages 293-308, August.
    28. Block, Steven A., 2003. "Political conditions and currency crises in emerging markets," Emerging Markets Review, Elsevier, vol. 4(3), pages 287-309, September.
    29. Claessens, Stijn & Pennacchi, George, 1996. "Estimating the Likelihood of Mexican Default from the Market Prices of Brady Bonds," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 31(01), pages 109-126, March.
    30. Michael T. Gapen & Dale F. Gray & Cheng Hoon Lim & Yingbin Xiao, 2005. "Measuring and Analyzing Sovereign Risk with Contingent Claims," IMF Working Papers 05/155, International Monetary Fund.
    31. Manuel De la Rocha & Roberto Perrelli & Christian B. Mulder, 2002. "The Role of Corporate, Legal and Macroeconomic Balance Sheet Indicators in Crisis Detection and Prevention," IMF Working Papers 02/59, International Monetary Fund.
    32. Bennett W Sutton & Luis Catão, 2002. "Sovereign Defaults; The Role of Volatility," IMF Working Papers 02/149, International Monetary Fund.
    33. Kaminsky, Graciela L., 2006. "Currency crises: Are they all the same?," Journal of International Money and Finance, Elsevier, vol. 25(3), pages 503-527, April.
    34. Manasse, Paolo & Roubini, Nouriel, 2009. ""Rules of thumb" for sovereign debt crises," Journal of International Economics, Elsevier, vol. 78(2), pages 192-205, July.
    35. Berg, Andrew & Pattillo, Catherine, 1999. "Predicting currency crises:: The indicators approach and an alternative," Journal of International Money and Finance, Elsevier, vol. 18(4), pages 561-586, August.
    36. Darrell Duffie & Lasse Heje Pedersen & Kenneth J. Singleton, 2003. "Modeling Sovereign Yield Spreads: A Case Study of Russian Debt," Journal of Finance, American Finance Association, vol. 58(1), pages 119-159, February.
    37. Burkart, Oliver & Coudert, Virginie, 2002. "Leading indicators of currency crises for emerging countries," Emerging Markets Review, Elsevier, vol. 3(2), pages 107-133, June.
    38. repec:cup:apsrev:v:95:y:2001:i:01:p:49-69_00 is not listed on IDEAS
    39. Makridakis, Spyros & Taleb, Nassim, 2009. "Living in a world of low levels of predictability," International Journal of Forecasting, Elsevier, vol. 25(4), pages 840-844, October.
    40. Asli Demirgüç-Kunt & Enrica Detragiache, 1998. "The Determinants of Banking Crises in Developing and Developed Countries," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 81-109, March.
    41. Enrica Detragiache & Antonio Spilimbergo, 2001. "Crises and Liquidity; Evidence and Interpretation," IMF Working Papers 01/2, International Monetary Fund.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dawood, Mary & Horsewood, Nicholas & Strobel, Frank, 2017. "Predicting sovereign debt crises: An Early Warning System approach," Journal of Financial Stability, Elsevier, vol. 28(C), pages 16-28.
    2. Döpke, Jörg & Fritsche, Ulrich & Pierdzioch, Christian, 2017. "Predicting recessions with boosted regression trees," International Journal of Forecasting, Elsevier, vol. 33(4), pages 745-759.
    3. Mark Joy & Marek Rusnák & Kateřina Šmídková & Bořek Vašíček, 2017. "Banking and Currency Crises: Differential Diagnostics for Developed Countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 44-67, January.
    4. Gilles Dufrénot & Anne-Charlotte Paret, 2016. "Power-Law Distribution in the Debt-to-Fiscal Revenue Ratio: Empirical Evidence and a Theoretical Model," Working Papers halshs-01357797, HAL.
    5. Paolo Manasse & Roberto Savona & Marika Vezzoli, 2013. "Rules of Thumb for Banking Crises in Emerging Markets," Working Papers 481, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    6. repec:eee:finsta:v:35:y:2018:i:c:p:215-225 is not listed on IDEAS
    7. Detken, Carsten & Alessi, Lucia, 2014. "Identifying excessive credit growth and leverage," Working Paper Series 1723, European Central Bank.
    8. repec:vrs:demode:v:4:y:2016:i:1:p:26:n:15 is not listed on IDEAS
    9. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions in Germany With Boosted Regression Trees," Macroeconomics and Finance Series 201505, University of Hamburg, Department of Socioeconomics.
    10. repec:eee:joecas:v:13:y:2016:i:c:p:100-113 is not listed on IDEAS

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • G01 - Financial Economics - - General - - - Financial Crises
    • H63 - Public Economics - - National Budget, Deficit, and Debt - - - Debt; Debt Management; Sovereign Debt

    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:bla:obuest:v:77:y:2015:i:1:p:66-92. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/sfeixuk.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.