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Business-cycle reports and the efficiency of macroeconomic forecasts for Germany

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  • Alexander Foltas
  • Christian Pierdzioch

Abstract

We study the efficiency of growth and inflation forecasts published by three leading German economic research institutes during a period of time ranging from 1970 to 2017. To this end, we examine whether the information used by the research institutes when they formed their forecasts helps to explain the ex-post realized forecast errors. We identify the information that the research institutes used to set up their quantitative forecasts by applying computational-linguistics techniques to decompose the business-cycle reports published by the research institutes into various topics. Our results show that several topics have predictive value for the forecast errors.

Suggested Citation

  • Alexander Foltas & Christian Pierdzioch, 2022. "Business-cycle reports and the efficiency of macroeconomic forecasts for Germany," Applied Economics Letters, Taylor & Francis Journals, vol. 29(10), pages 867-872, June.
    • Handle: RePEc:taf:apeclt:v:29:y:2022:i:10:p:867-872
    DOI: 10.1080/13504851.2021.1896668
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    1. Ullrich Heilemann & Herman O. Stekler, 2013. "Has The Accuracy of Macroeconomic Forecasts for Germany Improved?," German Economic Review, Verein für Socialpolitik, vol. 14(2), pages 235-253, May.
    2. Holden, K & Peel, D A, 1990. "On Testing for Unbiasedness and Efficiency of Forecasts," The Manchester School of Economic & Social Studies, University of Manchester, vol. 58(2), pages 120-127, June.
    3. Allan Timmermann, 2007. "An Evaluation of the World Economic Outlook Forecasts," IMF Staff Papers, Palgrave Macmillan, vol. 54(1), pages 1-33, May.
    4. Foltas, Alexander, 2020. "Testing investment forecast efficiency with textual data," Working Papers 19, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    5. Christoph Behrens & Christian Pierdzioch & Marian Risse, 2018. "A test of the joint efficiency of macroeconomic forecasts using multivariate random forests," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 560-572, August.
    6. Jörg Döpke & Ulrich Fritsche, 2006. "Growth and inflation forecasts for Germany a panel-based assessment of accuracy and efficiency," Empirical Economics, Springer, vol. 31(3), pages 777-798, September.
    7. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46, National Bureau of Economic Research, Inc.
    8. Jacob A. Mincer, 1969. "Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance," NBER Books, National Bureau of Economic Research, Inc, number minc69-1.
    9. Patton, Andrew J. & Timmermann, Allan, 2007. "Testing Forecast Optimality Under Unknown Loss," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1172-1184, December.
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    Cited by:

    1. Foltas, Alexander, 2024. "Inefficient forecast narratives: A BERT-based approach," Working Papers 45, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    2. Pierdzioch, Christian, 2023. "A bootstrap-based efficiency test of growth and inflation forecasts for Germany," Economics Letters, Elsevier, vol. 224(C).
    3. Foltas, Alexander, 2023. "Quantifying priorities in business cycle reports: Analysis of recurring textual patterns around peaks and troughs," Working Papers 44, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.

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    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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