|
|
|
|
|
| West, Carol Taylor. |
| Panel data on regional employment forecasts from structural equation econometric models and time-series models are used to examine whether accuracy of the forecasts can be predicted, both absolutely and relatively. Specification of accuracy includes the time forecast was made, forecast horizon, and regional economic/demographic characteristics. The estimated model is able to predict accuracy of each forecast set at high step lengths but is less successful at low step lengths and is not successful at all in predicting relative accuracy. Regional characteristics are significant determinants of accuracy for both sets of forecasts, but the significant characteristics differ across methodologies and step lengths. |
| Tipo: Journal Article |
Palavras-chave: Forecasting accuracy; Panel data; Regional economies models. |
| Ano: 2003 |
URL: http://purl.umn.edu/43291 |
| |
|
|
| Dreger, Christian; Schumacher, Christian. |
| This paper discusses a large-scale factor model for the German economy. Following the recent literature, a data set of 121 time series is used via principal component analysis to determine the factors, which enter a dynamic model for German GDP. The model is compared with alternative univariate and multivariate models. These models are based on regression techniques and considerably smaller data sets. Out-of-sample forecasts show that the prediction errors of the factor model are smaller than the errors of the rival models. However, these advantages are not statistically significant, as a test for equal forecast accuracy shows. Therefore, the efficiency gains of using a large data set with this kind of factor models seem to be limited. Diese Arbeit... |
| Tipo: Working or Discussion Paper |
Palavras-chave: Factor models; Principal components; Forecasting accuracy; International Development; E32; C51; C43. |
| Ano: 2002 |
URL: http://purl.umn.edu/26321 |
| |
|
|
|
