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

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  • Mehrotra, Aaron
  • Rautava, Jouko

Abstract

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.

Suggested Citation

  • Mehrotra, Aaron & Rautava, Jouko, 2007. "Do sentiment indicators help to assess and predict actual developments of the Chinese economy?," BOFIT Discussion Papers 11/2007, Bank of Finland Institute for Emerging Economies (BOFIT).
    • Handle: RePEc:zbw:bofitp:bdp2007_011
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    References listed on IDEAS

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    1. 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, September.
    2. Curran, Declan & Funke, Michael, 2006. "Taking the temperature: forecasting GDP growth for mainland in China," BOFIT Discussion Papers 6/2006, Bank of Finland Institute for Emerging Economies (BOFIT).
    3. Declan Curran & Michael Funke, 2006. "Taking the Temperature - Forecasting GDP Growth for Mainland China," Quantitative Macroeconomics Working Papers 20606, Hamburg University, Department of Economics.
    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 147-162, April.
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    2. Joscha Beckmann & Ansgar Belke & Michael Kühl, 2011. "Global Integration of Central and Eastern European Financial Markets—The Role of Economic Sentiments," Review of International Economics, Wiley Blackwell, vol. 19(1), pages 137-157, February.
    3. Ansgar Belke & Joscha Beckmann & Michael Kühl, 2010. "Global Integration of Central and Eastern European Financial Markets – The Role of Economic Sentiments," Ruhr Economic Papers 0174, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    4. Juuso Kaaresvirta & Aaron Mehrotra, 2009. "Business surveys and inflation forecasting in China," Economic Change and Restructuring, Springer, vol. 42(4), pages 263-271, November.
    5. Juuso Kaaresvirta & Aaron Mehrotra, 2009. "Business surveys and inflation forecasting in China," Economic Change and Restructuring, Springer, vol. 42(4), pages 263-271, November.
    6. Asger Lunde & Miha Torkar, 2020. "Including news data in forecasting macro economic performance of China," Computational Management Science, Springer, vol. 17(4), pages 585-611, December.

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    Keywords

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    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • P27 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Performance and Prospects

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