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The IWH Forecasting Dashboard: From forecasts to evaluation and comparison

Author

Listed:
  • Heinisch, Katja
  • Behrens, Christoph
  • Döpke, Jörg
  • Foltas, Alexander
  • Fritsche, Ulrich
  • Köhler, Tim
  • Müller, Karsten
  • Puckelwald, Johannes
  • Reichmayr, Hannes

Abstract

The paper describes the "Halle Institute for Economic Research (IWH) Forecasting Dashboard (ForDas)". This tool aims at providing, on a non-commercial basis, historical and actual macroeconomic forecast data for the Germany economy to researchers and interested audiences. The database renders it possible to directly compare forecast quality across selected institutions and over time. It is partly based on data collected in the DFG-funded project "Macroeconomic Forecasts in Great Crises".

Suggested Citation

  • Heinisch, Katja & Behrens, Christoph & Döpke, Jörg & Foltas, Alexander & Fritsche, Ulrich & Köhler, Tim & Müller, Karsten & Puckelwald, Johannes & Reichmayr, Hannes, 2023. "The IWH Forecasting Dashboard: From forecasts to evaluation and comparison," IWH Technical Reports 1/2023, Halle Institute for Economic Research (IWH).
    • Handle: RePEc:zbw:iwhtrp:12023
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    References listed on IDEAS

    as
    1. Birger Antholz, 2006. "Geschichte der quantitativen Konjunkturprognose-Evaluation in Deutschland," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 75(2), pages 12-33.
    2. Engelke, Carola & Heinisch, Katja & Schult, Christoph, 2019. "How forecast accuracy depends on conditioning assumptions," IWH Discussion Papers 18/2019, Halle Institute for Economic Research (IWH).
    3. Döpke, Jörg & Fritsche, Ulrich & Müller, Karsten, 2019. "Has macroeconomic forecasting changed after the Great Recession? Panel-based evidence on forecast accuracy and forecaster behavior from Germany," Journal of Macroeconomics, Elsevier, vol. 62(C).
    4. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    5. Christoph Behrens, 2019. "A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss," Economies, MDPI, vol. 7(3), pages 1-23, September.
    6. Christoph Behrens, 2020. "Evaluating the joint efficiency of German trade forecasts - a nonparametric multivariate approach," Applied Economics, Taylor & Francis Journals, vol. 52(34), pages 3732-3747, July.
    7. Christoph Behrens & Christian Pierdzioch & Marian Risse, 2020. "Do German economic research institutes publish efficient growth and inflation forecasts? A Bayesian analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(4), pages 698-723, March.
    8. Knüppel, Malte & Vladu, Andreea L., 2016. "Approximating fixed-horizon forecasts using fixed-event forecasts," Discussion Papers 28/2016, Deutsche Bundesbank.
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    1. 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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