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Nowcasting New Zealand GDP Using Machine Learning Algorithms

Adam RichardsonThomas Van Florenstein MulderM. Tugrul Vehbi

出版	Australian National University, Crawford School of Public Policy, Centre for Applied Macroeconomic Analysis, 2018
URL	http://books.google.com.hk/books?id=CG3TzQEACAAJ&hl=&source=gbs_api

註釋

This paper analyses the real-time nowcasting performance of machine learning algorithms estimated on New Zealand data. Using a large set of real-time quarterly macroeconomic indicators, we train a range of popular machine learning algorithms and nowcast real GDP growth for each quarter over the 2009Q1-2018Q1 period. We compare the predictive accuracy of these nowcasts with that of other traditional univariate and multivariate statistical models. We find that the machine learning algorithms outperform the traditional statistical models. Moreover, combining the individual machine learning nowcasts further improves the performance than in the case of the individual nowcasts alone.