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A bootstrap-based efficiency test of growth and inflation forecasts for Germany

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  • Pierdzioch, Christian

Abstract

I propose a simple to implement bootstrap-based efficiency (BBE) test to reexamine the efficiency of growth and inflation forecasts for Germany. The BBE test is useful as a test of forecast efficiency when a researcher, as is usually the case, can use a large number of macroeconomic and financial variables to proxy the information set of a forecast producer at the time when a forecast was published. A large number of proxy variables translates into a large number of candidate efficiency-regression models and the decision problem is that it is a priori unclear which model a researcher should choose to test for forecast efficiency. The BBE test solves this decision problem in that it requires a researcher to sample from the set of candidate models and, thereby, makes the decision problem tractable.

Suggested Citation

  • Pierdzioch, Christian, 2023. "A bootstrap-based efficiency test of growth and inflation forecasts for Germany," Economics Letters, Elsevier, vol. 224(C).
  • Handle: RePEc:eee:ecolet:v:224:y:2023:i:c:s016517652300054x
    DOI: 10.1016/j.econlet.2023.111029
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    References listed on IDEAS

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    1. 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.
    2. 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, March.
    3. Alexander Foltas & Christian Pierdzioch, 2022. "On the efficiency of German growth forecasts: an empirical analysis using quantile random forests and density forecasts," Applied Economics Letters, Taylor & Francis Journals, vol. 29(17), pages 1644-1653, October.
    4. 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.
    5. Brown, Bryan W & Maital, Shlomo, 1981. "What Do Economists Know? An Empirical Study of Experts' Expectations," Econometrica, Econometric Society, vol. 49(2), pages 491-504, March.
    6. 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.
    7. 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.
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    More about this item

    Keywords

    Forecast efficiency; Bootstrap; Test; Growth; Inflation; Germany;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • 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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