Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This study analyzes the dynamic characteristics of staffing employment across different business sectors and across different geographical regions in The Netherlands. We analyze a micro data set of the market leader of the Dutch staffing employment market, i.e. Randstad. We apply the dynamic factor model to extract common information out of a large data set and to isolate business cycle frequencies with the aim of forecasting staffing and total employment. We identify regions and sectors whose cyclical developments lead the staffing labor cycle at the country level. The dynamic factor model exploits these leading characteristics at the disaggregate level to forecast the country aggregate. Finally, both dynamic and static factors turn out to be predictive summary statistics of the micro data set when employed to forecast total employment at the country level.