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Early warning systems for sovereign debt crises: The role of heterogeneity

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Cited by:

  1. Dean Fantazzini, 2022. "Crypto-Coins and Credit Risk: Modelling and Forecasting Their Probability of Death," JRFM, MDPI, vol. 15(7), pages 1-34, July.
  2. 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.
  3. Sarlin, Peter, 2013. "On policymakers’ loss functions and the evaluation of early warning systems," Economics Letters, Elsevier, vol. 119(1), pages 1-7.
  4. Bartolucci, Francesco & Nigro, Valentina, 2007. "Maximum likelihood estimation of an extended latent Markov model for clustered binary panel data," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3470-3483, April.
  5. Smith, Jonathan Acosta & Grill, Michael & Lang, Jan Hannes, 2017. "The leverage ratio, risk-taking and bank stability," Working Paper Series 2079, European Central Bank.
  6. Han-Hsing Lee & Kuanyu Shih & Kehluh Wang, 2016. "Measuring sovereign credit risk using a structural model approach," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1097-1128, November.
  7. Quentin Bro de Comères, 2022. "Predicting European Banks Distress Events: Do Financial Information Producers Matter?," Working Papers hal-03752678, HAL.
  8. Chiaramonte, Laura & Casu, Barbara, 2017. "Capital and liquidity ratios and financial distress. Evidence from the European banking industry," The British Accounting Review, Elsevier, vol. 49(2), pages 138-161.
  9. Dean Fantazzini & Stephan Zimin, 2020. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 19-69, March.
  10. Arazmuradov, Annageldy, 2016. "Assessing sovereign debt default by efficiency," The Journal of Economic Asymmetries, Elsevier, vol. 13(C), pages 100-113.
  11. Fuertes, Ana-Maria, 2008. "Sieve bootstrap t-tests on long-run average parameters," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3354-3370, March.
  12. Dean Fantazzini & Raffaella Calabrese, 2021. "Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure," JRFM, MDPI, vol. 14(11), pages 1-23, October.
  13. Dean Fantazzini & Silvia Figini, 2009. "Random Survival Forests Models for SME Credit Risk Measurement," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 29-45, March.
  14. Fantazzini, Dean, 2008. "Credit Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 12(4), pages 84-137.
  15. Thangjam Rajeshwar Singh, 2011. "An ordered probit model of an early warning system for predicting financial crisis in India," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the IFC Conference on "Initiatives to address data gaps revealed by the financial crisis", Basel, 25-26 August 2010, volume 34, pages 185-201, Bank for International Settlements.
  16. repec:zbw:bofrdp:2014_011 is not listed on IDEAS
  17. Tamás Kristóf, 2021. "Sovereign Default Forecasting in the Era of the COVID-19 Crisis," JRFM, MDPI, vol. 14(10), pages 1-24, October.
  18. repec:zbw:bofitp:2011_018 is not listed on IDEAS
  19. Moreno Badia, Marialuz & Medas, Paulo & Gupta, Pranav & Xiang, Yuan, 2022. "Debt is not free," Journal of International Money and Finance, Elsevier, vol. 127(C).
  20. Alina Mihaela Dima & Simona Vasilache, 2016. "Credit Risk modeling for Companies Default Prediction using Neural Networks," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 127-143, September.
  21. Tuomas Antero Peltonen & Michela Rancan & Peter Sarlin, 2019. "Interconnectedness of the banking sector as a vulnerability to crises," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(2), pages 963-990, April.
  22. Barbara Jarmulska, 2022. "Random forest versus logit models: Which offers better early warning of fiscal stress?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 455-490, April.
  23. Dieter Gerdesmeier & Hans‐Eggert Reimers & Barbara Roffia, 2010. "Asset Price Misalignments and the Role of Money and Credit," International Finance, Wiley Blackwell, vol. 13(3), pages 377-407, December.
  24. Cheng, Xian & Zhao, Haichuan, 2019. "Modeling, analysis and mitigation of contagion in financial systems," Economic Modelling, Elsevier, vol. 76(C), pages 281-292.
  25. 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.
  26. Sarlin, Peter & Peltonen, Tuomas A., 2013. "Mapping the state of financial stability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 46-76.
  27. Bellini, Tiziano & Riani, Marco, 2012. "Robust analysis of default intensity," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3276-3285.
  28. Ms. Svetlana Cerovic & Mrs. Kerstin Gerling & Andrew Hodge & Mr. Paulo A Medas, 2018. "Predicting Fiscal Crises," IMF Working Papers 2018/181, International Monetary Fund.
  29. Sarlin, Peter & Ramsay, Bruce A., 2014. "Ending over-lending : Assessing systemic risk with debt to cash flow," Research Discussion Papers 11/2014, Bank of Finland.
  30. Fantazzini, Dean, 2023. "Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models," MPRA Paper 117141, University Library of Munich, Germany.
  31. Roberto Savona & Marika Vezzoli, 2012. "Multidimensional Distance‐To‐Collapse Point And Sovereign Default Prediction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 19(4), pages 205-228, October.
  32. Fu, Junhui & Zhou, Qingling & Liu, Yufang & Wu, Xiang, 2020. "Predicting stock market crises using daily stock market valuation and investor sentiment indicators," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
  33. Sarlin, Peter & Ramsay, Bruce A., 2014. "Ending over-lending: Assessing systemic risk with debt to cash flow," Bank of Finland Research Discussion Papers 11/2014, Bank of Finland.
  34. S Figini & P Giudici, 2011. "Statistical merging of rating models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1067-1074, June.
  35. Xianglong Liu, 2023. "Towards Better Banking Crisis Prediction: Could an Automatic Variable Selection Process Improve the Performance?," The Economic Record, The Economic Society of Australia, vol. 99(325), pages 288-312, June.
  36. Lanbiao Liu & Chen Chen & Bo Wang, 2022. "Predicting financial crises with machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 871-910, August.
  37. Panayotis Michaelides & Mike Tsionas & Panos Xidonas, 2020. "A Bayesian Signals Approach for the Detection of Crises," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 551-585, September.
  38. Sarlin, Peter & Ramsay, Bruce A., 2015. "Ending over-lending: assessing systemic risk with debt to cash flow," Working Paper Series 1769, European Central Bank.
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