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.