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Using a Bayesian learning model with heterogeneity across agents, our study aims to identify the relative importance of alternative pathways through which professional forecasters disagree and reach consensus on the term structure of inflation and real GDP forecasts, resulting in different...
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We estimate a Bayesian learning model with heterogeneity aimed at explaining the evolution of expert disagreement in forecasting real GDP growth and inflation over 24 monthly horizons for G7 countries during 1990-2007. Professional forecasters are found to begin and have relatively more success...
Persistent link: https://www.econbiz.de/10008529265
We estimate a Bayesian learning model with heterogeneity aimed at explaining expert forecast disagreement and its evolution over horizons. Disagreement is postulated to have three components due to differences in: (i) the initial prior beliefs, (ii) the weights attached on priors, and (iii)...
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We propose a new measure of differential interpretation in the context of a Bayesian learning model, which allows us to abstract from other sources of disagreement, such as differences in priors. We then develop a likelihood ratio statistic for testing the null hypothesis that agents interpret...
Persistent link: https://www.econbiz.de/10011163299