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Forecasting recessions: can we do better on MARS?

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  • Peter Sephton

Abstract

A number of recent articles have examined the ability of financial variables to predict recessions. In this article, Peter Sephton extends the literature by considering a non-linear, nonparametric approach to predicting the probability of recession using multivariate adaptive regression splines (MARS). The results suggest that this data-intensive approach to modeling is not a panacea for recession forecasting. Although it does well explaining the data within the sample, its out-of-sample forecasts do not improve upon the benchmark probit specification.

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Bibliographic Info

Article provided by Federal Reserve Bank of St. Louis in its journal Review.

Volume (Year): (2001)
Issue (Month): Mar ()
Pages: 39-49

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Handle: RePEc:fip:fedlrv:y:2001:i:mar:p:39-49:n:v.83no.2

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Related research

Keywords: Recessions ; Forecasting;

References

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  1. Michael Dueker, 1997. "Strengthening the case for the yield curve as a predictor of U.S. recessions," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 41-51.
  2. Bernard, Henri J & Gerlach, Stefan, 1998. "Does the Term Structure Predict Recessions? The International Evidence," CEPR Discussion Papers 1892, C.E.P.R. Discussion Papers.
  3. Benjamin M. Friedman & Kenneth N. Kuttner, 1994. "Indicator Properties of the Paper-Bill Spread: Lessons from Recent Experiences," NBER Working Papers 4969, National Bureau of Economic Research, Inc.
  4. Cao, Liangyue & Soofi, Abdol S., 1999. "Nonlinear deterministic forecasting of daily dollar exchange rates," International Journal of Forecasting, Elsevier, vol. 15(4), pages 421-430, October.
  5. Enders, Walter & Granger, C. W. J., 1998. "Unit Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates," Staff General Research Papers 1388, Iowa State University, Department of Economics.
  6. Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon & Andrada-Felix, Julian, 1999. "Exchange-rate forecasts with simultaneous nearest-neighbour methods: evidence from the EMS," International Journal of Forecasting, Elsevier, vol. 15(4), pages 383-392, October.
  7. De Gooijer, Jan G. & Ray, Bonnie K. & Krager, Horst, 1998. "Forecasting exchange rates using TSMARS," Journal of International Money and Finance, Elsevier, vol. 17(3), pages 513-534, June.
  8. Granger, Clive W J, 1995. "Modelling Nonlinear Relationships between Extended-Memory Variables," Econometrica, Econometric Society, vol. 63(2), pages 265-79, March.
  9. Atta-Mensah, Joseph & Tkacz, Greg, 1998. "Predicting Canadian Recessions Using Financial Variables: A Probit Approach," Working Papers 98-5, Bank of Canada.
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Citations

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Cited by:
  1. Pons Novell, J., 2002. "Ciclo de la economía española y contenido informativo de los tipos de interés," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 20, pages 583-598, Diciembre.
  2. K. Batu Tunay, 2010. "Banking Crises and Early Warning Systems: A Model Suggestion for Turkish Banking Sector," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 4(1), pages 9-46.
  3. David Jamieson Bolder & Yuliya Romanyuk, 2008. "Combining Canadian Interest-Rate Forecasts," Working Papers 08-34, Bank of Canada.
  4. Sharda, V.N. & Patel, R.M. & Prasher, S.O. & Ojasvi, P.R. & Prakash, Chandra, 2006. "Modeling runoff from middle Himalayan watersheds employing artificial intelligence techniques," Agricultural Water Management, Elsevier, vol. 83(3), pages 233-242, June.
  5. Peter Sephton, 2005. "Forecasting inflation using the term structure and MARS," Applied Economics Letters, Taylor & Francis Journals, vol. 12(4), pages 199-202.
  6. David Jamieson Bolder & Tiago Rubin, 2007. "Optimization in a Simulation Setting: Use of Function Approximation in Debt Strategy Analysis," Working Papers 07-13, Bank of Canada.

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