Lumpy Forecasts

Title: “Lumpy Forecasts” Speaker: Javier Turén (Instituto de Economía, PUC Chile). Abstract: Professional forecasters adjust inflation forecasts in a lumpy way—forecasts are changed infrequently, and when adjusted, they are revised by a significant amount. As the forecasting horizon shrinks, the frequency of revisions, the size of revisions, and forecast errors decrease. Using a fixed-event forecasting framework, we assess the role of the consensus forecast and private information in shaping forecast revisions, both at the extensive and the intensive margins. A model of Bayesian belief formation with forecast revision costs and strategic con- cerns (i) delivers lumpy forecasts consistent with the survey evidence, (ii) rationalizes forecast efficiency tests, and (iii) generates state-dependent responses to inflation volatility. We pro- pose a two-stage procedure to cleanse lumpy forecasts and obtain a measure of underlying inflation beliefs.