publication . Article . 2011

Differential Interpretation in the Survey of Professional Forecasters

Open Access
  • Published: 20 Jul 2011 Journal: SSRN Electronic Journal (eissn: 1556-5068, Copyright policy)
  • Publisher: Elsevier BV
In this paper we estimate a simple Bayesian learning model to expectations data from the Survey of Professional Forecasters. We reformulate the model in terms of forecast revisions, which allows to abstract from differences in priors and to focus the analysis on the relationship between revisions and signal. The model depends on two parameters, the forecaster’s belief about the signal bias and its weight. The empirical analysis shows that there is significant heterogeneity in the parameters among forecasters, in particular at longer forecast horizons. The cross-sectional distribution of the estimated bias parameter has a median close to zero, while its dispersio...
arXiv: Physics::Atmospheric and Oceanic Physics
free text keywords: Economics and Econometrics, Accounting, Finance
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