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What Do We Lose When We Average Expectations?

Author

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  • Constantin Burgi

    (The George Washington University)

Abstract

In this paper, I use the Bloomberg Survey of forecasts to assess if evaluating the distribution of expectations will lead to important additional insights over the evaluation of the simple average. I first introduce new approaches that allow me to assess the forecast accuracy and the information rigidity at the individual level despite a large share of missing data. Applying these new approaches, I find that taking into account the distribution can significantly improve the predictive power of the survey. For example, I find that the part of uncertainty measured by disagreement can improve the prediction of recessions in a dynamic probit model relative to the simple average. On information rigidity, I find that some of the rigidity found at the aggregate level likely stems from the aggregation process. Together, my findings suggest that we should look at individual expectations whenever possible as important insights are lost by just looking at aggregate expectations.

Suggested Citation

  • Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  • Handle: RePEc:gwc:wpaper:2016-013
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    2. Constantin Bürgi & Tara M. Sinclair, 2021. "What does forecaster disagreement tell us about the state of the economy?," Applied Economics Letters, Taylor & Francis Journals, vol. 28(1), pages 49-53, January.

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    More about this item

    Keywords

    Expectations; Bloomberg Survey; Forecast Evaluation; Uncertainty; Dynamic Probit;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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