New Monthly Estimation Approach for Nowcasting GDP Growth
: The Case of Japan
October 15, 2013
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This paper proposes a new approach for nowcasting as yet unavailable GDP growth by estimating monthly GDP growth with a large dataset. The model consists of two parts: (i) a few indicators that explain a large part of the variation in GDP growth, and (ii) principal components, which are orthogonal to those indicators and are extracted from a number of GDP source data, capturing the rest of the variation. The approach relies on a static factor model comprising a number of indicators that have a simultaneous relationship with GDP. Applying this approach to data for Japan, we find that our model produces more precise estimates of recent GDP growth at an earlier stage of nowcasting than the nowcasts of professional forecasters.
C53, C82, E37
Factor Models; Forecasting; Nowcasting; Monthly GDP; Real-time Data
We are grateful to Koichiro Kamada for his encouragement and constructive comments from the early stages of this research. We are also grateful to Jan J. J. Groen, Marco J. Lombardi, and Christian Schumacher for their valuable comments and suggestions. We thank Seisaku Kameda, Eiji Maeda, Ichiro Muto, Jouchi Nakajima, Koji Nakamura, Tomohiro Tsuruga, and seminar participants at the Japan Center for Economic Research for their helpful comments. We received excellent research assistance from Saki Inoue. Views expressed in this paper are those of the authors and do not necessarily reflect the official views of the Bank of Japan.
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