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Working day effects on GDP

Author

Listed:
  • Gebhard Flaig

Abstract

The strong growth in German GDP in the first quarter of 2000 as well as the recent economic forecast of the Ifo Institute have again shown how great an influence a differing number of working days can have on economic growth. In this contribution, the problem is analysed using a structural time-series model. Not only the working day component is estimated but at the same time estimations are made for the production potential and the output gap. As a "by-product", this approach supplies a forecast function both for the examined time series itself as well as for the components it is based on.

Suggested Citation

  • Gebhard Flaig, 2000. "Working day effects on GDP," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 53(22), pages 12-17, August.
    • Handle: RePEc:ces:ifosdt:v:53:y:2000:i:22:p:12-17
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    Citations

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    Cited by:

    1. Gebhard Flaig, 2001. "Is there a "new economy"? Effects on the American production potential," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 54(05), pages 16-21, October.
    2. Klaus Abberger & Gebhard Flaig & Wolfgang Nierhaus, 2007. "ifo Konjunkturumfragen und Konjunkturanalyse : ausgewählte methodische Aufsätze aus dem ifo Schnelldienst," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 33.
    3. Erich Langmantel, 2001. "Are business cycles in Euroland similar?," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 54(06), pages 53-54, October.
    4. Gebhard Flaig, 2002. "Unoberserved Components Models for Quarterly German GDP," CESifo Working Paper Series 681, CESifo.

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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