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Nowcasting Chinese GDP: Information Content of Economic and Financial Data

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  • Matthew S. Yiu

    (Hong Kong Monetary Authority)

  • Kenneth K. Chow

    (Hong Kong Institute for Monetary Research)

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    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.

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    Bibliographic Info

    Paper provided by Hong Kong Institute for Monetary Research in its series Working Papers with number 042011.

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    Length: 26 pages
    Date of creation: Feb 2011
    Date of revision:
    Handle: RePEc:hkm:wpaper:042011

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    Related research

    Keywords: Large Data Set; Pseudo Real Time Estimates; Factor Model; Kalman Filtering; Nowcasting; Information Content;

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