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Analyse der kantonalen Arbeitslosenquoten mittels räumlichen Zeitreihenmodellen

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Abstract

In diesem Beitrag untersuchen wir die räumlichen Abhängigkeiten der Arbeitslosigkeit in der Schweiz. Dazu modellieren wir die kantonalen Arbeitslosenquoten in einem räumlichen Zeitreihenmodell, das u.W. in der Schweiz noch nicht angewandt wurde. In diesem Modell wird die Arbeitslosenquote eines Kantons neben einer Reihe von exogenen erklärenden Variablen auch durch die distanzgewichteten Arbeitslosenquoten der Nachbarkantone sowie die zugehörigen Schocks erklärt. Obwohl die Existenz von räumlichen Abhängigkeiten in regionalen Arbeitsmärkten kaum bestritten wird, werden sie nur selten explizit modelliert. Unsere Modellschätzung für den Zeitraum 1998 bis 2007 ergibt, dass die kantonalen Arbeitslosenquoten sowohl in den Niveaus als auch in den Schocks räumlich abhängig sind, wobei die Abhängigkeiten in den Schocks stärker sind als in den Niveaus.

Suggested Citation

  • 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.
    • Handle: RePEc:kof:anskof:v:5:y:2011:i:1:p:75-87
    DOI: 10.3929/ethz-a-005427569
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    1. Schanne, N. & Wapler, R. & Weyh, A., 2010. "Regional unemployment forecasts with spatial interdependencies," International Journal of Forecasting, Elsevier, vol. 26(4), pages 908-926, October.
    2. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    3. repec:fth:geneec:97.05 is not listed on IDEAS
    4. Raymond J. G. M. Florax & Thomas Graaff, 2004. "The Performance of Diagnostic Tests for Spatial Dependence in Linear Regression Models: A Meta-Analysis of Simulation Studies," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax & Sergio J. Rey (ed.), Advances in Spatial Econometrics, chapter 2, pages 29-65, Springer.
    5. Paolo Filippini & Angelo Rossi, 1993. "Ausländische Arbeitnehmer und regionale Arbeitslosigkeitsdisparitäten," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 129(III), pages 357-369, September.
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