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ABSTRACT
This paper examines whether labour market forecasts can be improved by using disaggregated information. We construct vector-autoregressive models for employment by sector in order to produce out-of-sample forecasts of aggregate employment. Forecast accuracy is compared to univariate models by using Clark/West tests. In an application to German data, it is evident that disaggregation significantly improves the employment forecast. Moreover, using fluctuation-window tests we find that disaggregation yields superior results especially in phases with strong and sustained employment changes.
KEYWORDS:
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1 Even though this would have been preferable for a forecasting exercise, we were not able to obtain data measured in real time for the relevant sample period.
2 For better comparability, the mean of the absolute values of the loadings of each principal component is normalized to one.