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(Research Paper) Nowcasting Japanese GDPs

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November 7, 2018 Kyosuke Chikamatsu*1 Naohisa Hirakata*2 Yosuke Kido*3 Kazuki Otaka*4 Full Text [PDF 603KB] Abstract 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

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November 7, 2018 Kyosuke Chikamatsu*1 Naohisa Hirakata*2 Yosuke Kido*3 Kazuki Otaka*4

Full Text [PDF 603KB]

Abstract

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.

JEL classification C53

Keywords Nowcasting; Forecast Combination; Mixed-Data Sampling (MIDAS); Benchmarking

We are grateful for helpful comments from Naoko Hara, Hibiki Ichiue, Naoya Kato, Tomonori Murakoshi, Ichiro Muto, Shinsuke Ohyama and Toshitaka Sekine. The views expressed herein are those of the authors alone and do not necessarily reflect those of the Bank of Japan.

*1Research and Statistics Department, Bank of Japan E-mail : [email protected] *2Research and Statistics Department, Bank of Japan E-mail : [email protected] *3Research and Statistics Department, Bank of Japan E-mail : [email protected] *4Research and Statistics Department, Bank of Japan (currently at Personnel and Corporate Affairs Department) E-mail : [email protected]

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The Bank of Japan (BOJ) also known as Nippon Ginko, is the central bank of Japan. The Bank is often called Nichigin for short. It has its headquarters in Chuo, Tokyo.

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