Business and consumer surveys are the main source of agents' expectations. In this study we use survey expectations about a wide range of economic variables to forecast GDP growth. We propose an empirical approach to derive mathematical functional forms that link survey-based expectations to...

We apply the two-step machine-learning method proposed by Claveria et al. (2021) to generate country-specific sentiment indicators that provide estimates of year-on-year GDP growth rates. In the first step, by means of genetic programming, business and consumer expectations are evolved to derive...

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...