Studies on Binary Time Series Models with Applications to Empirical Macroeconomics and Finance

In this chapter, various financial variables are examined as predictors of the probability of a recession in the U.S. 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 U.S. and Germany is also a useful additional predictor. 1 A paper “Dynamic Probit Models and Financial Variables in Recession Forecasting” based on this chapter has been published in the Journal of Forecasting, 29, 215–230, 2010, WileyBlackwell, c ©[2009], John Wiley & Sons, Ltd.

[1]  S. Chib,et al.  Analysis of multivariate probit models , 1998 .

[2]  Jack L. Treynor,et al.  MUTUAL FUND PERFORMANCE* , 2007 .

[3]  Allan P. Layton,et al.  Leading Indicators for the Service Sector , 1989 .

[4]  J. Stock,et al.  A Comparison of Direct and Iterated Multistep Ar Methods for Forecasting Macroeconomic Time Series , 2005 .

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

[6]  James G. MacKinnon,et al.  Convenient Specification Tests for Logit and Probit Models , 1984 .

[7]  F. Diebold,et al.  Comparing Predictive Accuracy , 1994, Business Cycles.

[8]  Henri Nyberg,et al.  Forecasting the direction of the US stock market with dynamic binary probit models , 2011 .

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

[10]  Anthony S. Tay,et al.  Direction-of-change forecasts for Asian equity markets based on conditional variance, skewness and Kurtosis dynamics: International evidence , 2007 .

[11]  Arturo Estrella,et al.  A new measure of fit for equations with dichotomous dependent variables , 1998 .

[12]  Stanislav Anatolyev,et al.  Modeling Financial Return Dynamics via Decomposition , 2010 .

[13]  Marcelle Chauvet,et al.  Forecasting Recessions Using the Yield Curve , 2001 .

[14]  Margaret Mary McConnell,et al.  Output Fluctuations in the United States: What Has Changed Since the Early 1980s? , 1998 .

[15]  Henri Nyberg,et al.  Dynamic Probit Models and Financial Variables in Recession Forecasting , 2010 .

[16]  Olivier J. Blanchard,et al.  The Long and Large Decline in U.S. Output Volatility , 2001 .

[17]  J. Cochrane,et al.  Where is the market going ? Uncertain facts and novel theories , 1997 .

[18]  Arturo Estrella,et al.  The term structure as a predictor of real economic activity , 1991 .

[19]  S. B. Thompson,et al.  Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average? , 2008 .

[20]  B. Bernanke,et al.  The Federal Funds Rate and the Channels of Monetary Transnission , 1990 .

[21]  Raffaello Seri,et al.  Non-Causality in Bivariate Binary Time Series , 2006 .

[22]  John W. McDonald,et al.  Marginal regression analysis of a multivariate binary response , 1995 .

[23]  J. Ashford,et al.  Multi-variate probit analysis. , 1970, Biometrics.

[24]  Athanasios Orphanides,et al.  The Unreliability of Output-Gap Estimates in Real Time , 2002, Review of Economics and Statistics.

[25]  Anirvan Banerji,et al.  A framework for measuring international business cycles , 2001 .

[26]  E. Fama,et al.  BUSINESS CONDITIONS AND EXPECTED RETURNS ON STOCKS AND BONDS , 1989 .

[27]  L. Glosten,et al.  Economic Significance of Predictable Variations in Stock Index Returns , 1989 .

[28]  ResponsesClaudia CzadoDepartment,et al.  Multivariate Probit Analysis of Binary Time Series Datawith Missing , 1996 .

[29]  Dick van Dijk,et al.  Testing for Volatility Changes in U.S. Macroeconomic Time Series , 2004, Review of Economics and Statistics.

[30]  R. Engle.  Wald, likelihood ratio, and Lagrange multiplier tests in econometrics , 1984 .

[31]  Michael J. Dueker,et al.  Dynamic Forecasts of Qualitative Variables , 2005 .

[32]  Pentti Saikkonen,et al.  Predicting U.S. Recessions with Dynamic Binary Response Models , 2008, The Review of Economics and Statistics.

[33]  Nicholas M. Kiefer,et al.  Testing for dependence in multivariate probit models , 1982 .

[34]  Francis X. Diebold,et al.  Scoring the Leading Indicators , 2020, Business Cycles.

[35]  G. Schwarz.  Estimating the Dimension of a Model , 1978 .

[36]  M. Hashem Pesaran,et al.  A Simple Nonparametric Test of Predictive Performance , 1992 .

[37]  Yufeng Han.  Return Predictability, Economic Profits, and Model Mis-Specification: How Important are the Better Specified Models? , 2007 .

[38]  Heikki Kauppi,et al.  Yield-Curve Based Probit Models for Forecasting U.S. Recessions: Stability and Dynamics , 2008 .

[39]  D. Osborn,et al.  Predicting growth regimes for European countries , 2005 .

[40]  Stanislav Anatolyev.  Multi-Market Direction-of-Change Modeling Using Dependence Ratios , 2009 .