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Constructing a new leading indicator for unemployment from a survey among German employment agencies

  • Hutter, Christian

    ()

    (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany])

  • Weber, Enzo

    ()

    (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany])

"The paper investigates the predictive power of a new survey implemented by the Federal Employment Agency (FEA) for forecasting German unemployment in the short run. Every month, the CEOs of the FEA's regional agencies are asked about their expectations of future labor market developments. We generate an aggregate unemployment leading indicator that exploits serial correlation in response behavior through identifying and adjusting temporarily unreliable predictions. We use out-of-sample tests suitable in nested model environments to compare forecasting performance of models including the new indicator to that of purely autoregressive benchmarks. For all investigated forecast horizons (1, 2, 3 and 6 months), test results show that models enhanced by the new leading indicator significantly outperform their benchmark counterparts. To compare our indicator to potential competitors we employ the model confidence set. Results reveal that models including the new indicator perform very well." (Author's abstract, IAB-Doku) ((en))

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Paper provided by Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany] in its series IAB Discussion Paper with number 201317.

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Length: 30 pages
Date of creation: 21 Oct 2013
Date of revision:
Handle: RePEc:iab:iabdpa:201317
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  1. Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
  2. Peter Reinhard Hansen & Allan Timmermann, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," CREATES Research Papers 2012-43, School of Economics and Management, University of Aarhus.
  3. Yashiv, Eran, 2007. "Labor Search and Matching in Macroeconomics," IZA Discussion Papers 2743, Institute for the Study of Labor (IZA).
  4. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
  5. Petrongolo, Barbara & Pissarides, Christopher, 2000. "Looking Into The Black Box: A Survey Of The Matching Function," CEPR Discussion Papers 2409, C.E.P.R. Discussion Papers.
  6. Schanne, Norbert, 2012. "The formation of experts' expectations on labour markets : do they run with the pack?," IAB Discussion Paper 201225, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  7. Schanne, Norbert & Wapler, Rüdiger & Weyh, Antje, 2008. "Regional unemployment forecasts with spatial interdependencies," IAB Discussion Paper 200828, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  8. Askitas, Nikos & Zimmermann, Klaus F., 2009. "Google Econometrics and Unemployment Forecasting," IZA Discussion Papers 4201, Institute for the Study of Labor (IZA).
  9. Abberger, Klaus, 2007. "Qualitative business surveys and the assessment of employment -- A case study for Germany," International Journal of Forecasting, Elsevier, vol. 23(2), pages 249-258.
  10. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  11. Eran Yashiv, 2007. "Labor Search and Matching in Macroeconomics," CEP Discussion Papers dp0803, Centre for Economic Performance, LSE.
  12. Clements, Michael P. & Hendry, David F., 1996. "Multi-Step Estimation for Forecasting," The Warwick Economics Research Paper Series (TWERPS) 447, University of Warwick, Department of Economics.
  13. Dale T. Mortensen & Christopher A. Pissarides, 1993. "Job Creation and Job Destruction in the Theory of Unemployment," CEP Discussion Papers dp0110, Centre for Economic Performance, LSE.
  14. Marcellino, Massimiliano & Stock, James H & Watson, Mark W, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," CEPR Discussion Papers 4976, C.E.P.R. Discussion Papers.
  15. Peter F. Christoffersen & Francis X. Diebold, 1997. "Cointegration and long-horizon forecasting," Working Papers 97-14, Federal Reserve Bank of Philadelphia.
  16. Yashiv, Eran, 2007. "Labor search and matching in macroeconomics," European Economic Review, Elsevier, vol. 51(8), pages 1859-1895, November.
  17. Amos Golan & Jeffrey M. Perloff, 2004. "Superior Forecasts of the U.S. Unemployment Rate Using a Nonparametric Method," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 433-438, February.
  18. Hamilton, James D & Perez-Quiros, Gabriel, 1996. "What Do the Leading Indicators Lead?," The Journal of Business, University of Chicago Press, vol. 69(1), pages 27-49, January.
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