We examine predictive machine learning studies from 50 top business and economic journals published between 2010 and 2023. We investigate their transparency regarding the predictive performance of machine learning models compared to less complex traditional statistical models that require fewer...

At the request of the Banco Nacional de Angola (BNA), a technical assistance (TA) mission from the Monetary and Capital Markets (MCM) Department visited Luanda, Angola from May 20 to May 24, 2024. The mission helped the authorities review its forecasting and policy analysis system (FPAS),...

Using a large cross-country dataset covering over 150 countries and more than 10 macroeconomic variables, this study examines the consistency of IMF World Economic Outlook (WEO) forecasts with the full information rational expectations (FIRE) hypothesis. Similar to Consensus Economics forecasts,...

This paper employs predictive regressions to explore the predictability of sovereign Credit Default Swap (CDS) spread dynamics of relevant oil-producing countries. By incorporating oil prices and additional control variables, we predict the rate of CDS spread changes for Brazil, the UK,...

I use Bayesian VARs with stochastic volatility to forecast global temperatures and sea level and ice cover in the Northerin emisphere until 2010, by exploiting (i) their long-run equilibrium relationship with climate change drivers (CCDs) and (ii) the relationship between world GDP and...