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A bottom-up approach for forecasting GDP in a data rich environment
Francisco Craveiro Dias
In an increasingly data-rich environment, the use of factor models for forecasting purposes has gained prominence in the literature and among practitioners. In this article, we extend the work of Dias, Pinheiro and Rua (2015) by assessing the forecasting behaviour of factor models to predict several GDP components and investigate the performance of a bottom-up approach to forecast Portuguese GDP growth. We find supporting evidence of the usefulness of factor models and noteworthy forecasting gains when conducting a bottom-approach drawing on the main aggregates of GDP.