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Out-of-Sample Forecasting of Unemployment Rates with Pooled STVECM Forecasts

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Author Info
Costas Milas () (Keele University, UK and The Rimini Centre for Economics Analysis, Italy.)
Philip Rothman () (East Carolina University, USA)

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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 linear and STVECM forecasts appear to perform better than the linear AR(p) benchmark more so during business cycle expansions. Such pooling also tends to lead to statistically significant forecast improvement for the U.K. ÒReality checksÓ of these results suggest that they do not stem from data snooping.

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Publisher Info
Paper provided by Rimini Centre for Economic Analysis in its series Working Paper Series with number 49-07.

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Date of creation: Jul 2007
Date of revision: Jul 2007
Handle: RePEc:rim:rimwps:49-07

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Related research
Keywords: nonlinear asymmetric STVECM pooled forecasts Diebold-Mariano

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