There are many real-world situations in which complex interacting forces are best described by a series of equations. Traditional regression approaches to these situations involve modeling and estimating each individual equation (producing estimates of "partial derivatives") and then solving the...

This study presents an extension of the Gaussian process regression model for multiple-input multiple-output forecasting. This approach allows modelling the cross-dependencies between a given set of input variables and generating a vectorial prediction. Making use of the existing correlations in...

This paper takes stock of revenue forecasting practices in low-income countries, and provides a comprehensive and condensed account of the revenue forecasting process. Based on a new dataset on 34 low-income countries, it catalogues forecasting practices and procedures from inception until...

This paper develops a simple procedure for incorporating market-based information into the construction of fan charts. Using the International Monetary Fund (IMF)'s global growth forecast as a working example, the paper goes through the theoretical and practical considerations of this new...