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Dynamic probit models and financial variables in recession forecasting

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  • Henri Nyberg

    (Department of Economics and HECER, University of Helsinki, Finland)

Abstract

In this paper, various financial variables are examined as predictors of the probability of a recession in the USA and Germany. We propose a new dynamic probit model that outperforms the standard static model, giving accurate out-of-sample forecasts in both countries for the recession period that began in 2001, as well as the beginning of the recession in 2008. In accordance with previous findings, the domestic term spread proves to be an important predictive variable, but stock market returns and the foreign term spread also have predictive power in both countries. In the case of Germany, the interest rate differential between the USA and Germany is also a useful additional predictor. Copyright © 2009 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1161
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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 29 (2010)
Issue (Month): 1-2 ()
Pages: 215-230

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Handle: RePEc:jof:jforec:v:29:y:2010:i:1-2:p:215-230

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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Cited by:
  1. Henri Nyberg, 2010. "Testing an autoregressive structure in binary time series models," Economics Bulletin, AccessEcon, vol. 30(2), pages 1460-1473.
  2. Vladimir Dubrovskiy & Inna Golodniuk & Janusz Szyrmer, 2009. "Composite Leading Indicators for Ukraine: An Early Warning Model," CASE Network Reports 0085, CASE-Center for Social and Economic Research.
  3. Thomas Theobald, 2012. "Combining Recession Probability Forecasts from a Dynamic Probit Indicator," IMK Working Paper 89-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
  4. Makram El-Shagi & Gregor von Schweinitz, 2012. "Qual VAR Revisited: Good Forecast, Bad Story," IWH Discussion Papers 12, Halle Institute for Economic Research.
  5. Nyberg, Henri, 2011. "Forecasting the direction of the US stock market with dynamic binary probit models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 561-578, April.
  6. Ng, Eric C.Y., 2012. "Forecasting US recessions with various risk factors and dynamic probit models," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 112-125.
  7. Nyberg, Henri, 2010. "QR-GARCH-M Model for Risk-Return Tradeoff in U.S. Stock Returns and Business Cycles," MPRA Paper 23724, University Library of Munich, Germany.
  8. Giovanni De Luca & Alfonso Carfora, 2014. "Predicting U.S. recessions through a combination of probability forecasts," Empirical Economics, Springer, vol. 46(1), pages 127-144, February.
  9. Bellégo, C. & Ferrara, L., 2009. "Forecasting Euro-area recessions using time-varying binary response models for financial," Working papers 259, Banque de France.
  10. Fernandez-Perez, Adrian & Fernández-Rodríguez, Fernando & Sosvilla-Rivero, Simón, 2014. "The term structure of interest rates as predictor of stock returns: Evidence for the IBEX 35 during a bear market," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 21-33.
  11. Ratcliff, Ryan, 2013. "The “probability of recession”: Evaluating probabilistic and non-probabilistic forecasts from probit models of U.S. recessions," Economics Letters, Elsevier, vol. 121(2), pages 311-315.
  12. Khurshid Kiani, 2011. "Fluctuations in Economic and Activity and Stabilization Policies in the CIS," Computational Economics, Society for Computational Economics, vol. 37(2), pages 193-220, February.
  13. Schreiber, Sven, 2014. "Anticipating business-cycle turning points in real time using density forecasts from a VAR," Discussion Papers 2014/2, Free University Berlin, School of Business & Economics.
  14. Huseyin Kaya, 2013. "On the Predictive Power of Yield Spread for Future Growth and Recession: The Turkish Case," Working Papers 010, Bahcesehir University, Betam, revised Mar 2013.
  15. Dovern, Jonas & Gern, Klaus-Jürgen & Jannsen, Nils & Van Roye, Björn & Scheide, Joachim & Hogrefe, Jens & Boss, Alfred & Meier, Carsten-Patrick, 2008. "Weltkonjunktur und deutsche Konjunktur im Herbst 2008," Kiel Discussion Papers 456/457, Kiel Institute for the World Economy (IfW).
  16. Fornari, Fabio & Lemke, Wolfgang, 2010. "Predicting recession probabilities with financial variables over multiple horizons," Working Paper Series 1255, European Central Bank.
  17. Boss, Alfred & Dovern, Jonas & Meier, Carsten-Patrick & Scheide, Joachim, 2008. "Deutsche Konjunktur: leichte Rezession absehbar," Open Access Publications from Kiel Institute for the World Economy 28638, Kiel Institute for the World Economy (IfW).
  18. Milda Maria Burzala, 2012. "The Probability of Recession in Poland Based on the Hamilton Switching Model and the Logit Model," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 12, pages 73-88.
  19. António R. Antunes & Diana Bonfim & Nuno Monteiro & Paulo M.M. Rodrigues, 2014. "Early Warning Indicators of Banking Crises: Exploring new Data and Tools," Economic Bulletin and Financial Stability Report Articles, Banco de Portugal, Economics and Research Department.
  20. Nyberg, Henri, 2013. "Predicting bear and bull stock markets with dynamic binary time series models," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3351-3363.
  21. Kuosmanen, Petri & Vataja, Juuso, 2014. "Forecasting GDP growth with financial market data in Finland: Revisiting stylized facts in a small open economy during the financial crisis," Review of Financial Economics, Elsevier, vol. 23(2), pages 90-97.

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