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Identifying Regional and Sectoral Dynamics of the Dutch Staffing Labour Cycle

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  • Ard den Reijer

Abstract

This study analyses the dynamic characteristics of staffing employment across di¤erent business sectors and across different geographical regions in the Netherlands. We analyse a micro data set of the market leader of the Dutch staffing employment market, 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 economic activity. We identify regions and sectors whose cyclical developments lead the staffing labour cycle at the country level. The second question is then which model specification can best exploit the identified leading indicators at the disaggregate level to forecast the country aggregate? The dynamic factor model turns out to outperform univariate benchmark forecasting models by exploiting the substantial temporal variation of the staffing labour market at the disaggregate level.

Suggested Citation

  • Ard den Reijer, 2007. "Identifying Regional and Sectoral Dynamics of the Dutch Staffing Labour Cycle," DNB Working Papers 153, Netherlands Central Bank, Research Department.
  • Handle: RePEc:dnb:dnbwpp:153
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    File URL: https://www.dnb.nl/binaries/Working%20Paper%20153_tcm46-166903.pdf
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    References listed on IDEAS

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    1. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, pages 830-840.
    2. Daude, Christian & Fratzscher, Marcel, 2008. "The pecking order of cross-border investment," Journal of International Economics, Elsevier, vol. 74(1), pages 94-119, January.
    3. Forni, Mario & Lippi, Marco, 2001. "The Generalized Dynamic Factor Model: Representation Theory," Econometric Theory, Cambridge University Press, vol. 17(06), pages 1113-1141, December.
    4. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, Elsevier.
    5. de Haas, Ralph & van Lelyveld, Iman, 2010. "Internal capital markets and lending by multinational bank subsidiaries," Journal of Financial Intermediation, Elsevier, pages 1-25.
    6. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2004. "The generalized dynamic factor model consistency and rates," Journal of Econometrics, Elsevier, vol. 119(2), pages 231-255, April.
    7. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    8. Jörg Breitung & Sandra Eickmeier, 2006. "Dynamic factor models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, pages 27-42.
    9. Filippo Altissimo & Riccardo Cristadoro & Mario Forni & Marco Lippi & Giovanni Veronese, 2010. "New Eurocoin: Tracking Economic Growth in Real Time," The Review of Economics and Statistics, MIT Press, pages 1024-1034.
    10. Lewis M. Segal & Daniel G. Sullivan, 1997. "The Growth of Temporary Services Work," Journal of Economic Perspectives, American Economic Association, pages 117-136.
    11. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, pages 191-221.
    12. Hendry, David F. & Hubrich, Kirstin, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 589, European Central Bank.
    13. Christian Schumacher, 2007. "Forecasting German GDP using alternative factor models based on large datasets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 271-302.
    14. Ziegler, Christina & Eickmeier, Sandra, 2006. "How good are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Discussion Paper Series 1: Economic Studies 2006,42, Deutsche Bundesbank, Research Centre.
    15. Michael Kvasnicka, 2003. "Inside the Black Box of Temporary Help Agencies," Labor and Demography 0311001, EconWPA.
    16. Jörg Breitung & Sandra Eickmeier, 2006. "Dynamic factor models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, pages 27-42.
    17. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, pages 540-554.
    18. Jean Boivin & Serena Ng, 2005. "Understanding and Comparing Factor-Based Forecasts," International Journal of Central Banking, International Journal of Central Banking, vol. 1(3), December.
    19. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    20. de Groot, E.A. & Franses, Ph.H.B.F., 2005. "Real time estimates of GDP growth," Econometric Institute Research Papers EI 2005-01, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    21. Jamie Peck & Nik Theodore, 2007. "Flexible recession: the temporary staffing industry and mediated work in the United States," Cambridge Journal of Economics, Oxford University Press, vol. 31(2), pages 171-192, March.
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    Cited by:

    1. Claudia M. Buch & Sandra Eickmeier & Esteban Prieto, 2014. "Macroeconomic Factors and Microlevel Bank Behavior," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(4), pages 715-751, June.
    2. Buch, Claudia M. & Eickmeier, Sandra & Prieto, Esteban, 2010. "Macroeconomic factors and micro-level bank risk," Discussion Paper Series 1: Economic Studies 2010,20, Deutsche Bundesbank.

    More about this item

    Keywords

    staffing labour; dynamic factor model; disaggregate forecasting;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • J44 - Labor and Demographic Economics - - Particular Labor Markets - - - Professional Labor Markets and Occupations
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs

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