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Multivariate STAR Unemployment Rate Forecasts

Author

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  • Costas Milas

    (City University)

  • Phil Rothman

    (East Carolina University)

Abstract

In this paper we use smooth transition vector error-correction models (STVECMs) in a simulated out-of-sample forecasting experiment for the unemployment rates of the four non-Euro G-7 countries, the U.S., U.K., Canada, and Japan. For the U.S., pooled forecasts constructed by taking the median value across the point forecasts generated by the STVECMs perform better than the linear VECM benchmark more so during business cycle expansions. Pooling across the linear and nonlinear forecasts tends to lead to statistically signißcant forecast improvement for business cycle expansions for Canada, while the opposite is the case for the U.K.

Suggested Citation

  • Costas Milas & Phil Rothman, 2005. "Multivariate STAR Unemployment Rate Forecasts," Econometrics 0502010, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0502010
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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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