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 …

An essential element of the work of the Fund is to monitor and forecast international trade. This paper uses SWIFT … (PMI), to improve the short-term forecast of international trade. A horse race between linear regressions and machine …

results indicate that the forecast model incorporating internet search data provides additional information about tourist …

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

contributors to overall inflation forecast errors. Perhaps more importantly, relatively small core inflation forecast errors appear …

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 …

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 …