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Labour market forecasting in Germany: is disaggregation useful?

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  • Enzo Weber
  • Gerd Zika

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.

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  • Enzo Weber & Gerd Zika, 2016. "Labour market forecasting in Germany: is disaggregation useful?," Applied Economics, Taylor & Francis Journals, vol. 48(23), pages 2183-2198, May.
    • Handle: RePEc:taf:applec:v:48:y:2016:i:23:p:2183-2198
    DOI: 10.1080/00036846.2015.1117044
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    Cited by:

    1. Robert Lehmann, 2021. "Forecasting exports across Europe: What are the superior survey indicators?," Empirical Economics, Springer, vol. 60(5), pages 2429-2453, May.
    2. Gabe de Bondt & Arne Gieseck & Pablo Herrero & Zivile Zekaite, 2021. "Euro Area Income and Wealth Effects: Aggregation Issues," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(6), pages 1454-1474, December.

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