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Forecasting GDP all over the World: Evidence from Comprehensive Survey Data

Author

Listed:
  • Garnitz, Johanna
  • Lehmann, Robert
  • Wohlrabe, Klaus

Abstract

Comprehensive and international comparable leading indicators across countries and continents are rare. In this paper, we use a free and fast available source of leading indicators, the World Economic Survey (WES) conducted by the ifo Institute, to forecast growth of Gross Domestic Product (GDP) in 44 countries and three country aggregates separately. We come up with three major results. First, for 35 countries as well as the three aggregates a model containing one of the major WES indicators produces on average lower forecast errors compared to an autoregressive benchmark model. Second, the most important WES indicators are either the economic climate or the expectations on future economic development for the next six months. And last, 70% of all country-specific models contain WES information from at least one of the main trading partners. Thus, by allowing WES indicators from economic important partners to forecast GDP of the country under consideration, increases forecast accuracy.

Suggested Citation

  • Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2017. "Forecasting GDP all over the World: Evidence from Comprehensive Survey Data," MPRA Paper 81772, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:81772
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    File URL: https://mpra.ub.uni-muenchen.de/81772/1/MPRA_paper_81772.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    World Economic Survey; Economic Climate; Forecasting GDP;

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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