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Labour market forecasting : is disaggregation useful?

Author

Listed:
  • Weber, Enzo

    (Institute for Employment Research (IAB), Nuremberg, Germany)

  • Zika, Gerd

    (Institute for Employment Research (IAB), Nuremberg, Germany)

Abstract

"Using the example of short-term forecasts for German employment figures, the article at hand examines the question whether the use of disaggregated information increases the forecast accuracy of the aggregate. For this purpose, the out-of-sample forecasts for the aggregated employment forecast are compared to and contrasted with forecasts based on a vector-autoregressive model, which includes not only the aggregate but also the numbers of gainfully employed people at the industry level. The Clark/West test is used in the model comparison. It becomes evident that disaggregation significantly improves the employment forecast. Moreover, fluctuation- window tests help identify the phases during which disaggregation increases forecast accuracy to the strongest extent." (Author's abstract, IAB-Doku) ((en))

Suggested Citation

  • Weber, Enzo & Zika, Gerd, 2013. "Labour market forecasting : is disaggregation useful?," IAB-Discussion Paper 201314, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  • Handle: RePEc:iab:iabdpa:201314
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    References listed on IDEAS

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    10. Eggs, Johannes, 2013. "Unemployment benefit II, unemployment and health," IAB-Discussion Paper 201312, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
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    16. Moczall, Andreas, 2013. "Subsidies for substitutes? : New evidence on deadweight loss and substitution effects of a wage subsidy for hard-to-place job-seekers," IAB-Discussion Paper 201305, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
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    Citations

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    Cited by:

    1. Robert Lehmann & Antje Weyh, 2016. "Forecasting Employment in Europe: Are Survey Results Helpful?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 81-117, September.
    2. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    3. Schwengler, Barbara, 2013. "Einfluss der europäischen Regionalpolitik auf die deutsche Regionalförderung," IAB-Discussion Paper 201318, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    4. Robert Lehmann & Klaus Wohlrabe, 2014. "Forecasting gross value-added at the regional level: are sectoral disaggregated predictions superior to direct ones?," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 34(1), pages 61-90, February.
    5. Robert Lehmann, 2021. "Forecasting exports across Europe: What are the superior survey indicators?," Empirical Economics, Springer, vol. 60(5), pages 2429-2453, May.
    6. Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 51(54), pages 5802-5816.
    7. R. Lehmann & K. Wohlrabe, 2017. "Experts, firms, consumers or even hard data? Forecasting employment in Germany," Applied Economics Letters, Taylor & Francis Journals, vol. 24(4), pages 279-283, February.
    8. Bauer, Angela & Kruppe, Thomas, 2013. "Policy Styles : zur Genese des Politikstilkonzepts und dessen Einbindung in Evaluationsstudien," IAB-Discussion Paper 201322, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

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    More about this item

    Keywords

    Beschäftigtenzahl ; Methode ; Prognostik ; Arbeitsmarktprognose;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand

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