countries less accurate than a naive forecast given by the average growth rate in the recent past. The analysis suggests that a …

analysis, including for debt sustainability assessments, and points to statistical methods to improve forecast accuracy by …

We develop a framework to nowcast (and forecast) economic variables with machine learning techniques. We explain how … models to predict real output growth with lower forecast errors than traditional models. By combining multiple machine … learning models into ensembles, we lower forecast errors even further. We also identify measures of variable importance to help …

-recession years are revised slowly; in recession years, the pace of revision picks up but not sufficiently to avoid large forecast …

documents of the following years to understand the evolution of fiscal forecast errors. Our findings suggest that: (i) for most … terms of drivers, we show that forecast errors for the fiscal balance-to-GDP ratio are positively correlated with GDP growth … and terms of trade changes and negatively with GDP deflator surprises; (iv) forecast errors for public debt-to-GDP ratios …

This paper investigates the performance of the IMF WEO growth forecast revisions across different horizons and country … negative; (ii) on average, growth revisions are in the right direction, becoming progressively more responsive to the forecast … revisions in all country groups; (iv) WEO and Consensus Forecast growth revisions are highly correlated; (v) fall-to-spring WEO …

Financial crises pose unique challenges for forecast accuracy. Using the IMF's Monitoring of Fund Arrangement (MONA … informational value as they consistently outperform naive forecast approaches. However, we also document that there is room for … improvement: two thirds of the key macroeconomic variables that we examine are forecast inefficiently and 6 variables (growth of …

several traditional models of investment, we forecast that the U.S. investment in equipment and software will grow by about 10 …