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Nowcasting Business Cycles Using Toll Data

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Author Info

  • Askitas, Nikos

    () (IZA)

  • Zimmermann, Klaus F.

    () (IZA and University of Bonn)

Abstract

Nowcasting has been a challenge in the recent economic crisis. We introduce the Toll Index, a new monthly indicator for business cycle forecasting and demonstrate its relevance using German data. The index measures the monthly transportation activity performed by heavy transport vehicles across the country and has highly desirable availability properties (insignificant revisions, short publication lags) as a result of the innovative technology underlying its data collection. It is coincident with production activity due to the prevalence of just-in-time delivery. The Toll Index is a good early indicator of production as measured for instance by the German Production Index, provided by the German Statistical Office, which is a well-known leading indicator of the Gross National Product. The proposed new index is an excellent example of technological, innovation-driven economic telemetry, which we suggest should be established more around the world.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 5522.

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Length: 19 pages
Date of creation: Feb 2011
Date of revision:
Publication status: published online in: Journal of Forecasting, 2011 [ Early view:]
Handle: RePEc:iza:izadps:dp5522

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Related research

Keywords: telemetry; nowcasting; transportation; business cycles; production forecasting; macroeconomic forecasting; new products; evaluating forecasts; data mining;

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References

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  1. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor and Francis Journals, vol. 26(1), pages 53-90.
  2. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
  3. Tom Stark & Dean Croushore, 2001. "Forecasting with a real-time data set for macroeconomists," Working Papers 01-10, Federal Reserve Bank of Philadelphia.
  4. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
  5. Laurent Ferrara & Dominique Guegan & Patrick Rakotomarolahy, 2009. "GDP nowcasting with ragged-edge data : A semi-parametric modelling," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00344839, HAL.
  6. Nikolay Robinzonov & Klaus Wohlrabe, 2008. "Freedom of Choice in Macroeconomic Forecasting: An Illustration with German Industrial Production and Linear Models," Ifo Working Paper Series Ifo Working Paper No. 57, Ifo Institute for Economic Research at the University of Munich.
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Cited by:
  1. Roland Döhrn & Sönke Maatsch, 2012. "Der RWI/ISL-Containerumschlag-Index," Wirtschaftsdienst, Springer, vol. 92(5), pages 352-354, May.
  2. Roland Döhrn, 2013. "Transportation Data as a Tool for Nowcasting Economic Activity – The German Road Pricing System as an Example," Ruhr Economic Papers 0395, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.

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