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An entropy-based machine learning algorithm for combining macroeconomic forecasts

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An entropy-based machine learning algorithm for combining macroeconomic forecasts

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Bretó Martínez, Carles; Espinosa, Priscila; Hernández, Penélope; Pavía Miralles, José Manuel

Aquest document és un/a article, creat/da en: 2019

This paper applies a Machine Learning approach with the aim of providing a single aggregated prediction from a set of individual predictions. Departing from the well-known maximum-entropy inference methodology, a new factor capturing the distance between the true and the estimated aggregated predictions presents a new problem. Algorithms such as ridge, lasso or elastic net help in finding a new methodology to tackle this issue. We carry out a simulation study to evaluate the performance of such a procedure and apply it in order to forecast and measure predictive ability using a dataset of predictions on Spanish gross domestic product.

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