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Testing for differences in survey-based density expectations: A compositional data approach

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  • Dovern, Jonas
  • Glas, Alexander
  • Kenny, Geoff

Abstract

We propose to treat survey-based density expectations as compositional data when testing either for heterogeneity in density forecasts across different groups of agents or for changes over time. Monte Carlo simulations show that the proposed test has more power relative to both a bootstrap approach based on the KLIC and an approach which involves multiple testing for differences of individual parts of the density. In addition, the test is computaionally much faster than the KLIC-based one, which relies on simulations, and allows for comparisons across multiple groups. Using density expectations from the ECB Survey of Professional Forecasters and the U.S. Survey of Consumer Expectations, we show the usefulness of the test in detecting possible changes in density expectations over time and across different types of forecasters.

Suggested Citation

  • Dovern, Jonas & Glas, Alexander & Kenny, Geoff, 2023. "Testing for differences in survey-based density expectations: A compositional data approach," Working Papers 39, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    • Handle: RePEc:zbw:pp1859:39
    DOI: 10.18452/25967
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    More about this item

    Keywords

    compositional data; density forecasts; survey forecasts; disagreement;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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