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Regional employment forecasts with spatial interdependencies

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Author Info

  • Hampel, Katharina

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

  • Kunz, Marcus
  • Schanne, Norbert

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

  • Wapler, Rüdiger

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

  • Weyh, Antje

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

Abstract

"The labour-market policy-mix in Germany is increasingly being decided on a regional level. This requires additional knowledge about the regional development which (disaggregated) national forecasts cannot provide. Therefore, we separately forecast employment for the 176 German labour- market districts on a monthly basis. We first compare the prediction accuracy of standard time-series methods: autoregressive integrated moving averages (ARIMA), exponentially weighted moving averages (EWMA) and the structural-components approach (SC) in these small spatial units. Second, we augment the SC model by including autoregressive elements (SCAR) in order to incorporate the influence of former periods of the dependent variable on its current value. Due to the importance of spatial interdependencies in small labour-market units, we further augment the basic SC model by lagged values of neighbouring districts in a spatial dynamic panel (SCSAR). The prediction accuracies of the models are compared using the mean absolute percentage forecast error (MAPFE) for the simulated out-of-sample forecast for 2005. Our results show that the SCSAR is superior to the SCAR and basic SC model. ARIMA and EWMA models perform slightly better than SCSAR in many of the German labour-market districts. This reflects that these two moving-average models can better capture the trend reversal beginning in some regions at the end of 2004. All our models have a high forecast quality with an average MAPFE lower than 2.2 percent." (Author's abstract, IAB-Doku) ((en))

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Bibliographic Info

Paper provided by Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany] in its series IAB Discussion Paper with number 200702.

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Length: 46 pages
Date of creation: 16 Jan 2007
Date of revision:
Handle: RePEc:iab:iabdpa:200702

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Keywords: regionaler Arbeitsmarkt; Beschäftigungsentwicklung; Prognoseverfahren; Arbeitsmarktprognose - Methode;

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Citations

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Cited by:
  1. R. Patuelli & N. Schanne & D. A. Griffith & P. Nijkamp, 2011. "Persistence of Regional Unemployment: Application of a Spatial Filtering Approach to Local Labour Markets in Germany," Working Papers wp743, Dipartimento Scienze Economiche, Universita' di Bologna.
  2. Robert Lehmann & Klaus Wohlrabe, 2013. "Forecasting GDP at the regional level with many predictors," ERSA conference papers ersa13p15, European Regional Science Association.
  3. Bruckmeier, Kerstin & Graf, Tobias & Rudolph, Helmut, 2008. "Working poor: Arm oder bedürftig? : eine Analyse zur Erwerbstätigkeit in der SGB-II-Grundsicherung mit Verwaltungsdaten," IAB Discussion Paper 200834, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  4. Hohendanner, Christian, 2007. "Verdrängen Ein-Euro-Jobs sozialversicherungspflichtige Beschäftigung in den Betrieben?," IAB Discussion Paper 200708, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  5. Alfred Garloff & Carsten Pohl & Norbert Schanne, 2013. "Do small labor market entry cohorts reduce unemployment?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(15), pages 379-406, September.
  6. M. Mayor-Fernández & R. Patuelli, 2012. "Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions," Working Papers wp835, Dipartimento Scienze Economiche, Universita' di Bologna.
  7. Hutter, Christian & Weber, Enzo, 2013. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," IAB Discussion Paper 201317, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  8. 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].
  9. Eckey, Hans-Friedrich & Schwengler, Barbara & Türck, Matthias, 2007. "Vergleich von deutschen Arbeitsmarktregionen," IAB Discussion Paper 200703, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  10. Norbert Schanne, 2011. "Forecasting Regional Labour Markets with GVAR Models and Indicators (refereed paper)," ERSA conference papers ersa10p1044, European Regional Science Association.
  11. Amend, Elke & Herbst, Patrick, 2008. "Labor market pooling and human capital investment decisions," IAB Discussion Paper 200804, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  12. Rolf Schenker & Martin Straub, 2011. "Analyse der kantonalen Arbeitslosenquoten mittels räumlichen Zeitreihenmodellen," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, vol. 5(1), pages 75-87, March.
  13. 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].

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