forecasting applications of the estimated model are demonstrated, based on a novel Bayesian framework for conditioning on judgment …

money in forecasting euro-area inflation. We compare the predictive performance within and among various classes of …

this common forecasting problem manually is resource-intensive, but the existing literature provides little guidance on how … method can reproduce the smoothness of professional forecasts subject to various constraints and slightly improve forecast …

This study applies state-of-the-art machine learning (ML) techniques to forecast IMF-supported programs, analyzes the …

forecast data from the SPF, CBO, Federal Reserve, and asset prices. Unanticipated fiscal stimulus and interest rate shocks we …

This paper analyzes the inflation forecast errors over the period 2021Q1-2022Q3 using forecasts of core and headline … economies. The findings reveal evidence of forecast bias that worsened initially then subsided towards the end of the sample …. There is also evidence of forecast oversmoothing indicating rigidity in forecast revision in the face of incoming …

The paper proposes an algorithm that uses forecast encompassing tests for combining forecasts. The algorithm excludes a … forecast from the combination if it is encompassed by another forecast. To assess the usefulness of this approach, an extensive …

at forecast horizons of 1, 4, and 20 quarters, using the mean squared error, direction of change metrics, and the …