Title: A Bayesian approach for inference on probabilistic surveys
Authors: Roberto Casarin - University Ca' Foscari of Venice (Italy) [presenting]
Federico Bassetti - Politecnico Milano (Italy)
Marco Del Negro - Federal Reserve Bank of New York (United States)
Abstract: A non-parametric Bayesian approach is proposed to the estimation of forecast densities in probabilistic surveys. We use it to study the evolution of the subjective forecast distribution for inflation from the U.S. Survey of Professional Forecasters over the past forty years.