The purpose of the paper is to investigate the accuracy of forecasts derived from univariate and multivariate time-series models. An iterative method to adjust for impact assessment in univariate ARIMA models is discussed and illustrated for the German unemployment rate. Finally, we also examine the
β¦ LIBER β¦
Out-of-sample forecasting of unemployment rates with pooled STVECM forecasts
β Scribed by Costas Milas; Philip Rothman
- Book ID
- 113647969
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 950 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0169-2070
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## Abstract This paper shows that outβofβsample forecast comparisons can help prevent data miningβinduced overfitting. The basic results are drawn from simulations of a simple Monte Carlo design and a real dataβbased design similar to those used in some previous studies. In each simulation, a gener