Nowcasting Chinese GDP: Information Content of Economic and Financial Data

Matthew S. Yiu and Kenneth K. Chow
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Matthew S. Yiu: Hong Kong Monetary Authority
Kenneth K. Chow: Hong Kong Institute for Monetary Research

No 42011, Working Papers from Hong Kong Institute for Monetary Research

Abstract: This paper applies the factor model proposed by Giannone, Reichlin, and Small (2005) on a large data set to nowcast (i.e. current-quarter forecast) the annual growth rate of China¡¦s quarterly GDP. The data set contains 189 indicator series of several categories, such as prices, industrial production, fixed asset investment, external sector, money market and financial market. This paper also applies Bai and Ng¡¦s criteria (2002) to determine the number of common factors in the factor model. The identified model generates out-of-sample nowcasts for China's GDP with smaller mean squared forecast errors than those of the Random Walk benchmark. Moreover, using the factor model, we find that interest rate data is the single most important block in estimating current-quarter GDP in China. Other important blocks are consumer and retail prices data and fixed asset investment indicators.

Keywords: Large Data Set; Pseudo Real Time Estimates; Factor Model; Kalman Filtering; Nowcasting; Information Content (search for similar items in EconPapers)
JEL-codes: C33 C53 E32 E37 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2011-02
New Economics Papers: this item is included in nep-cba, nep-for and nep-tra
References: View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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