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On the use of cross-sectional measures of forecast uncertainty

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  • Driver, Ciaran
  • Trapani, Lorenzo
  • Urga, Giovanni

Abstract

This paper investigates the role of cross-sectional dependence among private forecasters, assessing its impact on the measurement and use of the forecasting uncertainty. We determine the circumstances under which cross-sectional measures of uncertainty (such as the disagreement across forecasters) are valid proxies for private information, and analyse the impact of distributional assumptions on private signals. In particular, we explore the role played by cross dependence among forecasters, arising from factors such as partially shared private information. We validate the theory through a Monte Carlo exercise, which reinforces our findings, as well as through an application to US nonfarm payroll data.

Suggested Citation

  • Driver, Ciaran & Trapani, Lorenzo & Urga, Giovanni, 2013. "On the use of cross-sectional measures of forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 29(3), pages 367-377.
    • Handle: RePEc:eee:intfor:v:29:y:2013:i:3:p:367-377
    DOI: 10.1016/j.ijforecast.2012.11.005
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    Cited by:

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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.
    3. 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.
    4. Atalla, Tarek & Joutz, Fred & Pierru, Axel, 2016. "Does disagreement among oil price forecasters reflect volatility? Evidence from the ECB surveys," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1178-1192.

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