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Survey-based indicators vs. hard data: What improves export forecasts in Europe?

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  • Robert Lehmann

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Abstract

In this study, we evaluate whether survey-based indicators produce lower forecast errors for export growth than indicators obtained from hard data such as price and cost competitiveness measures. Our pseudo out-of-sample analyses and forecastencompassing tests reveal that survey-based indicators outperform the benchmark model as well as the indicators from hard data for most of the twenty European states focused on in our study and the aggregates EA-18 and EU-28. The most accurate forecasts are on average produced by the confidence indicator in the manufacturing sector, the economic sentiment indicator and the production expectations. However, large country differences in the forecast accuracy of survey-based indicators emerge. These differences are mainly explained by country-specific export compositions. A larger share in raw material or oil exports worsens the accuracy of soft indicators. The accuracy of soft indicators improves if countries have a larger share in exports of machinery goods. For hard indicators, we find only weak evidence for the export composition to explain differences in forecast accuracy.

Suggested Citation

  • Robert Lehmann, 2015. "Survey-based indicators vs. hard data: What improves export forecasts in Europe?," ifo Working Paper Series 196, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  • Handle: RePEc:ces:ifowps:_196
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    Cited by:

    1. repec:spr:jbuscr:v:12:y:2016:i:1:d:10.1007_s41549-016-0002-5 is not listed on IDEAS
    2. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65, March.
    3. Waldemar Marz & Johannes Pfeiffer, 2015. "Resource Market Power and Levels of Knowledge in General Equilibrium," ifo Working Paper Series 197, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    4. Sandra Hanslin & Rolf Scheufele, 2016. "Foreign PMIs: A reliable indicator for exports?," Working Papers 2016-01, Swiss National Bank.
    5. Robert Lehmann & Antje Weyh, 2016. "Forecasting Employment in Europe: Are Survey Results Helpful?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 81-117, September.
    6. Christian Grimme & Robert Lehmann & Marvin Noeller, 2018. "Forecasting Imports with Information from Abroad," CESifo Working Paper Series 7079, CESifo Group Munich.
    7. 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.
    8. Hanslin Grossmann, Sandra & Scheufele, Rolf, 2015. "Foreign PMIs: A reliable indicator for Swiss exports," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112830, Verein für Socialpolitik / German Economic Association.

    More about this item

    Keywords

    Export forecasting; European business and consumer survey; export expectations; price and cost competitiveness.;

    JEL classification:

    • F01 - International Economics - - General - - - Global Outlook
    • F10 - International Economics - - Trade - - - General
    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation

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