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A new indicator for nowcasting employment subject to social security contributions in Germany

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  • Christian Hutter

    (Institute for Employment Research (IAB))

Abstract

Contrary to the number of unemployed or vacancies, the number of employees subject to social security contributions (SSC) for Germany is published after a time lag of 2 months. Furthermore, there is a waiting period of 6 months until the values are not revised any more. This paper uses monthly data on the number of people subject to compulsory health insurance (CHI) as auxiliary variable to better nowcast SSC. Statistical evaluation tests using real-time data show that CHI significantly improves nowcast accuracy compared to purely autoregressive benchmark models. The mean squared prediction error for nowcasts of SSC can be reduced by approximately 20%. In addition, CHI outperforms alternative candidate variables such as unemployment, vacancies and industrial production.

Suggested Citation

  • Christian Hutter, 2020. "A new indicator for nowcasting employment subject to social security contributions in Germany," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 54(1), pages 1-10, December.
    • Handle: RePEc:spr:jlabrs:v:54:y:2020:i:1:d:10.1186_s12651-020-00274-w
    DOI: 10.1186/s12651-020-00274-w
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    References listed on IDEAS

    as
    1. Christian Hutter & Enzo Weber, 2015. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," Applied Economics, Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
    2. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    3. 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.
    4. Peter Reinhard Hansen & Allan Timmermann, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," CREATES Research Papers 2012-43, Department of Economics and Business Economics, Aarhus University.
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    7. Bossler, Mario & Gartner, Hermann & Kubis, Alexander & Küfner, Benjamin & Rothe, Thomas, 2019. "The IAB Job Vacancy Survey: Establishment survey on labour demand and recruitment processes, Waves 2000 to 2016 and subsequent quarters 2006 to 2017," FDZ Datenreport. Documentation on Labour Market Data 201903_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
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    More about this item

    Keywords

    Nowcasting; Real-time data; Employees; Social security contributions; Compulsory health insurance;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure

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