Forecasting recessions: can we do better on MARS?

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.

[1]  J. Friedman Estimating Functions of Mixed Ordinal and Categorical Variables Using Adaptive Splines , 1991 .

[2]  Clive W. J. Granger,et al.  Modelling nonlinear relationships between extended-memory variables , 1995 .

[3]  Halbert White,et al.  Artificial neural networks: an econometric perspective ∗ , 1994 .

[4]  Peter Craven,et al.  Smoothing noisy data with spline functions , 1978 .

[5]  Abdol S. Soofi,et al.  Nonlinear deterministic forecasting of daily dollar exchange rates , 1999 .

[6]  P. Lewis,et al.  Nonlinear Modeling of Time Series Using Multivariate Adaptive Regression Splines (MARS) , 1991 .

[7]  Julián Andrada-Félix,et al.  Exchange-rate forecasts with simultaneous nearest-neighbour methods: evidence from the EMS , 1999 .

[8]  Clive W. J. Granger,et al.  Long memory series with attractors , 2001 .

[9]  Clive W. J. Granger,et al.  Modeling nonlinear relationships between extended-memory variables , 2001 .

[10]  Frederic S. Mishkin,et al.  Predicting U.S. Recessions: Financial Variables as Leading Indicators , 1995, Review of Economics and Statistics.

[11]  Kenneth N. Kuttner,et al.  Indicator Properties of the Paper-Bill Spread: Lessons from Recent Experiences , 1994 .

[12]  S. Gerlach,et al.  Does the Term Structure Predict Recessions? The International Evidence , 1998 .

[13]  Joseph G. Haubrich,et al.  Predicting real growth using the yield curve , 1996 .

[14]  Min Qi,et al.  Nonlinear Predictability of Stock Returns Using Financial and Economic Variables , 1999 .

[15]  Michael J. Dueker Strengthening the Case for the Yield Curve as a Predictor of U.S. Recessions , 1997 .

[16]  Scott D. Schuh,et al.  Beyond shocks : what causes business cycles? , 1998 .

[17]  J. Friedman Multivariate adaptive regression splines , 1990 .

[18]  Richard D. Porter,et al.  Is the Price Level Tied to the M2 Monetary Aggregate in the Long Run , 1991 .

[19]  J. Gooijer,et al.  Forecasting exchange rates using TSMARS , 1998 .

[20]  C. Granger,et al.  Modelling Nonlinear Economic Relationships , 1995 .

[21]  Clive W. J. Granger,et al.  Unit Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates , 1998 .

[22]  Cointegration tests on MARS , 1994 .

[23]  Peter Temin,et al.  The Causes of American Business Cycles: an Essay in Economic Historiography , 1998 .

[24]  Greg Tkacz,et al.  Predicting Canadian Recessions Using Financial Variables: A Probit Approach , 1998 .

[25]  Daryl Pregibon,et al.  Estimating Optimal Transformations for Multiple Regression and Correlation: Comment , 1985 .