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Exploiting Heterogeneity in the Survey of Professional Forecasters

Author

Listed:
  • Tae-Hwy Lee

    (Department of Economics, University of California Riverside)

  • Saerom Lee

    (University of California, Riverside)

Abstract

The mean response in the Survey of Professional Forecasters (SPF) is widely used to summarize individual forecasts. In this paper, we propose a novel summary forecast that enhances the predictive power of the mean response by selectively incorporating idiosyncratic signals. Our framework is motivated by the observation that while individual forecasts are highly correlated—suggesting a factor structure—they also exhibit significant heterogeneity. We treat the mean response as the primary common factor and define heterogeneity as the idiosyncratic component of each individual forecast after accounting for this commonality. Employing a factor-adjusted regularized framework, we integrate informative idiosyncratic components to improve the mean response. Using SPF data from the Federal Reserve Bank of Philadelphia and the European Central Bank, we show that incorporating these idiosyncratic components leads to significant predictive gains over the mean response.

Suggested Citation

  • Tae-Hwy Lee & Saerom Lee, 2026. "Exploiting Heterogeneity in the Survey of Professional Forecasters," Working Papers 202602, University of California at Riverside, Department of Economics.
    • Handle: RePEc:ucr:wpaper:202602
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    References listed on IDEAS

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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