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

Costas Milas () and Philip Rothman ()

Working Paper Series from The Rimini Centre for Economic Analysis

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.

Keywords: nonlinear; asymmetric; STVECM; pooled forecasts; Diebold-Mariano (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
Date: 2007-07, Revised 2007-07
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Journal Article: Out-of-sample forecasting of unemployment rates with pooled STVECM forecasts (2008)
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Persistent link: http://EconPapers.repec.org/RePEc:rim:rimwps:49-07

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