This paper examines matched point and density forecasts of inflation from the Survey of Professional Forecasters to analyze the relationship between expected inflation, disagreement, and uncertainty. We extend previous studies through our data construction and estimation methodology. Specifically, we derive measures of disagreement and uncertainty by using a decomposition proposed in earlier research by Wallis and by applying the concept of entropy from information theory. We also undertake the empirical analysis within a seemingly unrelated regression framework. Our results offer mixed support for the propositions that disagreement is a useful proxy for uncertainty and that increases in expected inflation are accompanied by heightened inflation uncertainty. However, we document a robust, quantitatively and statistically significant positive association between disagreement and expected inflation.
Survey of Professional Forecasters, density forecasts, point forecasts, inflation predictions, seemingly related regression