Combine to compete: Improving fiscal forecast accuracy over time

Abstract

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Budget forecasts have become increasingly important as a tool of fiscal management to influence expectations of bond markets and the public at large. Difficulties in projecting macroeconomic variables in volatile economic times—together with political bias—thwart the accuracy of budget forecasts. Pooling information from many different forecasters can still lead to substantial gains in predictive accuracy when taking into account time variation. We combine the forecasts of both private and public agencies for Italy over the period 1993–2022, and test absolute and relative forecasting performance over time. Although forecast combinations do not necessarily result in less biased or more efficient forecasts, tracking better performing forecasters and combining their budget predictions produces significantly better predictions.