Nowcasting Japanese GDPs

In this paper, we discuss the approaches to nowcasting Japanese GDPs, namely preliminary quarterly GDP estimates and revised annual GDP estimates. First, we look at nowcasting preliminary estimates of quarterly GDP using monthly indicators, ranging from hard data to soft data. In doing so, we compare a variety of mixed frequency approaches, a bridge equation approach, Mixed-Data Sampling (MIDAS) and factor-augmented version of these approaches, and also discuss the usefulness of forecast combination. Second, we work on nowcasting revised annual GDP, which is compiled with comprehensive statistics but only available after a considerable delay. In nowcasting the revised annual GDP, we employ several benchmarking methods, including Chow and Lin (1971), and examine the usefulness of monthly supply-side indicators to predict revised annual GDP. Our findings are summarized as follows. First, regarding nowcasting preliminary quarterly GDP, some of the mixed frequency models discussed in this paper record out-of-sample performance superior to an in-sample mean benchmark. Furthermore, there is a gain from combining model forecasts and professional forecasts. Second, regarding nowcasting revised annual GDP, some benchmarking models that exploit supply-side data serve as useful tools for predicting revised annual growth rates.