Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
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.