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Indikatoren-Modelle zur Kurzfristprognose der Beschäftigung in Deutschland

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  • Gaggermeier, Christian

Abstract

"In Deutschland wird die Zahl der Erwerbstätigen aus verschiedenen Datenquellen errechnet und steht erst mit zeitlicher Verzögerung zur Verfügung - bis vor kurzem erst etwa 70 Tage nach dem Ende des jeweiligen Berichtsmonats. Um diese Lücke zu überbrücken und die Zahl der Erwerbstätigen bzw. der sozialversicherungspflichtig Beschäftigten über einen Zeitraum von drei Monaten über den letzten verfügbaren Wert hinaus zu prognostizieren, habe ich Konjunkturindikatoren wie Geschäftserwartungen und Auftragseingänge sowie approximierende Variablen wie die Zahl der Arbeitslosen oder der Beitragszahler der Arbeitslosenversicherung zu Modellen kombiniert. Diese Indikatoren-Modelle können die Entwicklung der Beschäftigung durchaus erklären, allerdings nicht so gut, dass ihre Prognosegüte diejenige von autoregressiven Modellen erreichen würde. Die Prognosen von reinen autoregressiven Modellen können jedoch teilweise dadurch verbessert werden, dass man sie um Konjunkturindikatoren erweitert." (Autorenreferat, IAB-Doku)

Suggested Citation

  • Gaggermeier, Christian, 2006. "Indikatoren-Modelle zur Kurzfristprognose der Beschäftigung in Deutschland," IAB-Forschungsbericht 200606, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  • Handle: RePEc:iab:iabfob:200606
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    File URL: https://doku.iab.de/forschungsbericht/2006/fb0606.pdf
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    References listed on IDEAS

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    1. Christian Hott & André Kunkel, 2004. "Ein ifo Beschäftigungsindikator," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(06), pages 53-57, March.
    2. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    3. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    4. Joseph Beaulieu, J. & Miron, Jeffrey A., 1993. "Seasonal unit roots in aggregate U.S. data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 305-328.
    5. Hassler, Uwe, 2003. "Zeitabhängige Volatilität und instationäre Zeitreihen: Zum Nobelpreis an Robert F. Engle und Clive W. J. Granger," Wirtschaftsdienst – Zeitschrift für Wirtschaftspolitik (1949 - 2007), ZBW - Leibniz Information Centre for Economics, vol. 83(12), pages 811-816.
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