IDEAS home Printed from https://ideas.repec.org/p/iab/iabfob/200606.html
   My bibliography  Save this paper

Indikatoren-Modelle zur Kurzfristprognose der Beschäftigung in Deutschland

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://doku.iab.de/forschungsbericht/2006/fb0606.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Christian Hott & André Kunkel, 2004. "An Ifo employment indicator," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(06), pages 53-57, March.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kavussanos, Manolis G. & Alizadeh-M, Amir H., 2002. "Seasonality patterns in tanker spot freight rate markets," Economic Modelling, Elsevier, vol. 19(5), pages 747-782, November.
    2. Ghassen El Montasser, 2015. "The Seasonal KPSS Test: Examining Possible Applications with Monthly Data and Additional Deterministic Terms," Econometrics, MDPI, vol. 3(2), pages 1-16, May.
    3. Roberto Martínez-Espiñeira, 2007. "An Estimation of Residential Water Demand Using Co-Integration and Error Correction Techniques," Journal of Applied Economics, Taylor & Francis Journals, vol. 10(1), pages 161-184, May.
    4. Braun, R. Anton & Evans, Charles L., 1995. "Seasonality and equilibrium business cycle theories," Journal of Economic Dynamics and Control, Elsevier, vol. 19(3), pages 503-531, April.
    5. A. M. Robert Taylor, 2003. "Locally Optimal Tests Against Unit Roots in Seasonal Time Series Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(5), pages 591-612, September.
    6. Chambers, Marcus J. & Ercolani, Joanne S. & Taylor, A.M. Robert, 2014. "Testing for seasonal unit roots by frequency domain regression," Journal of Econometrics, Elsevier, vol. 178(P2), pages 243-258.
    7. Shin, Dong Wan & Oh, Man-Suk, 2000. "Semiparametric tests for seasonal unit roots based on a semiparametric feasible GLSE," Statistics & Probability Letters, Elsevier, vol. 50(3), pages 207-218, November.
    8. Paulo Rodrigues & Philip Hans Franses, 2005. "A sequential approach to testing seasonal unit roots in high frequency data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(6), pages 555-569.
    9. Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 985-1004.
    10. Hans Franses, Philip & Koehler, Anne B., 1998. "A model selection strategy for time series with increasing seasonal variation," International Journal of Forecasting, Elsevier, vol. 14(3), pages 405-414, September.
    11. Smith, Jeremy & Otero, Jesus, 1997. "Structural breaks and seasonal integration," Economics Letters, Elsevier, vol. 56(1), pages 13-19, September.
    12. Beenstock, Michael & Reingewertz, Yaniv & Paldor, Nathan, 2016. "Testing the historic tracking of climate models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1234-1246.
    13. Beaulieu, J Joseph & Miron, Jeffrey A, 1992. "A Cross Country Comparison of Seasonal Cycles and Business Cycles," Economic Journal, Royal Economic Society, vol. 102(413), pages 772-788, July.
    14. J.D. Hollingworth, 1997. "Leading Indicators of Australian Recessions: Part 2," Economics Discussion / Working Papers 97-17, The University of Western Australia, Department of Economics.
    15. del Barrio Castro, Tomás & Osborn, Denise R., 2023. "Periodic Integration and Seasonal Unit Roots," MPRA Paper 117935, University Library of Munich, Germany, revised 2023.
    16. D R Osborn & M Sensier, 2004. "Modelling UK Inflation: Persistence, Seasonality and Monetary Policy," Centre for Growth and Business Cycle Research Discussion Paper Series 46, Economics, The University of Manchester.
    17. Hamori, Shigeyuki, 2001. "Seasonality and stock returns: some evidence from Japan," Japan and the World Economy, Elsevier, vol. 13(4), pages 463-481, December.
    18. Ioannis Chatziantoniou & Stavros Degiannakis & Bruno Eeckels & George Filis, 2016. "Forecasting tourist arrivals using origin country macroeconomics," Applied Economics, Taylor & Francis Journals, vol. 48(27), pages 2571-2585, June.
    19. Evren Erdoğan Cosar, 2006. "Seasonal behaviour of the consumer price index of Turkey," Applied Economics Letters, Taylor & Francis Journals, vol. 13(7), pages 449-455.
    20. Boswijk, H. Peter & Franses, Philip Hans & van Dijk, Dick, 2010. "Cointegration in a historical perspective," Journal of Econometrics, Elsevier, vol. 158(1), pages 156-159, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iab:iabfob:200606. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: IAB, Geschäftsbereich Wissenschaftliche Fachinformation und Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/iabbbde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.