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Do sentiment indicators help to assess and predict actual developments of the Chinese economy?

This paper evaluates the usefulness of business sentiment indicators for forecasting developments in the Chinese real economy. We use data on diffusion indices collected by the People’s Bank of China for forecasting industrial production, retail sales and exports. Our bivariate vector autoregressive models, each composed of one diffusion index and one real sector variable, generally outperform univariate AR models in forecasting one to four quarters ahead. Similarly, principal components analysis, combining information from various diffusion indices, leads to enhanced forecasting performance. Our results indicate that Chinese business sentiment indicators convey useful information about current and future developments in the real economy. They also suggest that the official data provide a fairly accurate picture of the Chinese economy.

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File URL: http://www.suomenpankki.fi/bofit_en/tutkimus/tutkimusjulkaisut/dp/Documents/dp1107.pdf
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Paper provided by Bank of Finland, Institute for Economies in Transition in its series BOFIT Discussion Papers with number 11/2007.

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Length: 27 pages
Date of creation: 04 May 2007
Date of revision:
Handle: RePEc:hhs:bofitp:2007_011
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  1. Declan Curran & Michael Funke, 2006. "Taking the Temperature - Forecasting GDP Growth for Mainland China," Quantitative Macroeconomics Working Papers 20606, Hamburg University, Department of Economics.
  2. Ronny Nilsson, 2006. "Composite Leading Indicators and Growth Cycles in Major OECD Non-Member Economies and recently new OECD Members Countries," OECD Statistics Working Papers 2006/5, OECD Publishing.
  3. Carsten A. Holz, 2004. "China's Statistical System in Transition: Challenges, Data Problems, and Institutional Innovations," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 50(3), pages 381-409, 09.
  4. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
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