IDEAS home Printed from https://ideas.repec.org/r/eee/jimfin/v35y2013icp76-103.html
   My bibliography  Save this item

Predicting financial crises: The (statistical) significance of the signals approach

Citations

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


Cited by:

  1. Sarlin, Peter, 2013. "On policymakers’ loss functions and the evaluation of early warning systems," Economics Letters, Elsevier, vol. 119(1), pages 1-7.
  2. Tobias Knedlik & Gregor Von Schweinitz, 2012. "Macroeconomic Imbalances as Indicators for Debt Crises in Europe," Journal of Common Market Studies, Wiley Blackwell, vol. 50(5), pages 726-745, September.
  3. Dany-Knedlik, Geraldine & Kämpfe, Martina & Knedlik, Tobias, 2021. "The appropriateness of the macroeconomic imbalance procedure for Central and Eastern European Countries," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 48(1), pages 123-139.
  4. Hyeongwoo Kim & Wen Shi & Hyun Hak Kim, 2020. "Forecasting financial stress indices in Korea: a factor model approach," Empirical Economics, Springer, vol. 59(6), pages 2859-2898, December.
  5. Tristan Nguyen & Nguyen Ngoc Duy, 2017. "Developing an Early Warning System for Financial Crises in Vietnam," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 7(4), pages 413-430, April.
  6. Yamarik, Steven & El-Shagi, Makram & Yamashiro, Guy, 2016. "Does inequality lead to credit growth? Testing the Rajan hypothesis using state-level data," Economics Letters, Elsevier, vol. 148(C), pages 63-67.
  7. El-Shagi, Makram & Kelly, Logan, 2019. "What can we learn from country-level liquidity in the EMU?," Journal of Financial Stability, Elsevier, vol. 42(C), pages 75-83.
  8. Knedlik, Tobias, 2012. "The European Commission’s Scoreboard of Macroeconomic Imbalances – The Impact of Preferences on an Early Warning System," IWH Discussion Papers 10/2012, Halle Institute for Economic Research (IWH).
  9. Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  10. Hyeongwoo Kim & Wen Shi, 2021. "Forecasting financial vulnerability in the USA: A factor model approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 439-457, April.
  11. Knedlik, Tobias, 2014. "The impact of preferences on early warning systems — The case of the European Commission's Scoreboard," European Journal of Political Economy, Elsevier, vol. 34(C), pages 157-166.
  12. Sarlin, Peter & von Schweinitz, Gregor, 2021. "Optimizing Policymakers’ Loss Functions In Crisis Prediction: Before, Within Or After?," Macroeconomic Dynamics, Cambridge University Press, vol. 25(1), pages 100-123, January.
  13. Stefan Eichler, 2017. "How Do Political Factors Shape the Bank Risk–Sovereign Risk Nexus in Emerging Markets?," Review of Development Economics, Wiley Blackwell, vol. 21(3), pages 451-474, August.
  14. Popescu, Alexandra & Turcu, Camelia, 2017. "Sovereign debt and systemic risk in the eurozone," Economic Modelling, Elsevier, vol. 67(C), pages 275-284.
  15. El-Shagi, Makram & Fidrmuc, Jarko & Yamarik, Steven, 2020. "Inequality and credit growth in Russian regions," Economic Modelling, Elsevier, vol. 91(C), pages 550-558.
  16. Hyeongwoo Kim & Wen Shi, 2015. "Forecasting Financial Market Vulnerability in the U.S.: A Factor Model Approach," Auburn Economics Working Paper Series auwp2015-04, Department of Economics, Auburn University.
  17. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2019. "Does machine learning help us predict banking crises?," Journal of Financial Stability, Elsevier, vol. 45(C).
  18. von Schweinitz, Gregor & Sarlin, Peter, 2015. "Signaling Crises: How to Get Good Out-of-Sample Performance Out of the Early Warning System," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112964, Verein für Socialpolitik / German Economic Association.
  19. Markus Holopainen & Peter Sarlin, 2015. "Toward robust early-warning models: A horse race, ensembles and model uncertainty," Papers 1501.04682, arXiv.org, revised Apr 2016.
  20. Tsionas, Mike G. & Mamatzakis, Emmanuel & Ongena, Steven, 2020. "Does risk aversion affect bank output loss? The case of the Eurozone," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1127-1145.
  21. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers 48/2018, Deutsche Bundesbank.
  22. Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: Partial Least Squares Factor Model Approach," Working Papers 2017-14, Economic Research Institute, Bank of Korea.
  23. Makram El-shagi & Logan J Kelly, 2014. "Liquidity in the liquidity crisis: evidence from Divisia monetary aggregates in Germany and the European crisis countries," Economics Bulletin, AccessEcon, vol. 34(1), pages 63-72.
  24. Zhi-Qiang Jiang & Gang-Jin Wang & Askery Canabarro & Boris Podobnik & Chi Xie & H. Eugene Stanley & Wei-Xing Zhou, 2018. "Short term prediction of extreme returns based on the recurrence interval analysis," Quantitative Finance, Taylor & Francis Journals, vol. 18(3), pages 353-370, March.
  25. Christian Dreger & Konstantin A. Kholodilin, 2018. "Early Warning System of Government Debt Crises," Discussion Papers of DIW Berlin 1724, DIW Berlin, German Institute for Economic Research.
  26. Makram El-Shagi & Axel Lindner & Gregor von Schweinitz, 2016. "Real Effective Exchange Rate Misalignment in the Euro Area: A Counterfactual Analysis," Review of International Economics, Wiley Blackwell, vol. 24(1), pages 37-66, February.
  27. Tomáš Domonkos & Filip Ostrihoň & Ivana Šikulová & Maria Širaňová, 2016. "Analyzing macroeconomic imbalances in the EU," EcoMod2016 9660, EcoMod.
  28. 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.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.