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Identifying Regional and Sectoral Dynamics of the Dutch Staffing Labour Cycle

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Author Info
Ard den Reijer

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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.

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Publisher Info
Paper provided by Netherlands Central Bank, Research Department in its series DNB Working Papers with number 153.

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Date of creation: Nov 2007
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Handle: RePEc:dnb:dnbwpp:153

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Related research
Keywords: staffing labour; dynamic factor model; disaggregate forecasting;

Find related papers by JEL classification:
C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
J44 - Labor and Demographic Economics - - Particular Labor Markets - - - Professional Labor Markets and Occupations
J63 - Labor and Demographic Economics - - Mobility, Unemployment, and Vacancies - - - Turnover; Vacancies; Layoffs

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  4. 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. [Downloadable!] (restricted)
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  6. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, Elsevier. [Downloadable!] (restricted)
  7. Ard den Reijer, 2006. "The Dutch business cycle: which indicators should we monitor?," DNB Working Papers 100, Netherlands Central Bank, Research Department. [Downloadable!]
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    Other versions:
    • Lawrence J. Christiano & Terry J. Fitzgerald, 1999. "The Band Pass Filter," NBER Working Papers 7257, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  10. Altissimo, Filippo & Cristadoro, Riccardo & Forni, Mario & Lippi, Marco & Veronese, Giovanni, 2006. "New EuroCOIN: Tracking Economic Growth in Real Time," CEPR Discussion Papers 5633, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  12. 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, vol. 82(4), pages 540-554, November. [Downloadable!] (restricted)
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  13. Segal, Lewis M & Sullivan, Daniel G, 1997. "The Growth of Temporary Services Work," Journal of Economic Perspectives, American Economic Association, vol. 11(2), pages 117-36, Spring. [Downloadable!] (restricted)
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  16. Schumacher, Christian, 2005. "Forecasting German GDP using alternative factor models based on large datasets," Discussion Paper Series 1: Economic Studies 2005,24, Deutsche Bundesbank, Research Centre. [Downloadable!]
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  17. 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. [Downloadable!] (restricted)
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