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Characteristics and implications of Chinese macroeconomic data revisions

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  • Sinclair, Tara M.

Abstract

The research examining macroeconomic data for developed economies suggests that an understanding of the nature of data revisions is important both for the production of accurate macroeconomic forecasts and for forecast evaluation. This paper focuses on Chinese data, for which there has been substantial debate about data quality for some time. The key finding in this paper is that, while it is true that the Chinese macroeconomic data revisions are not well-behaved, they are not very different from similarly-timed U.S. macroeconomic data revisions. The positive bias in Chinese real GDP revisions is a result of the fast-growing service sector, which is notably hard to measure in real time. A better understanding of the revisions process is particularly helpful for studies of the forecast errors from surveys of forecasters, where the choice of the vintage for outcomes may have an impact on the estimated forecast errors.

Suggested Citation

  • Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.
    • Handle: RePEc:eee:intfor:v:35:y:2019:i:3:p:1108-1117
    DOI: 10.1016/j.ijforecast.2019.04.010
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    Cited by:

    1. repec:bof:bofitp:urn:nbn:fi:bof-201511031430 is not listed on IDEAS
    2. John G. Fernald & Eric Hsu & Mark M. Spiegel, 2015. "Is China fudging its figures? Evidence from trading partner data," Working Paper Series 2015-12, Federal Reserve Bank of San Francisco.
    3. Fernald, John G. & Hsu, Eric & Spiegel, Mark M., 2021. "Is China fudging its GDP figures? Evidence from trading partner data," Journal of International Money and Finance, Elsevier, vol. 110(C).
    4. repec:zbw:bofitp:2015_002 is not listed on IDEAS
    5. repec:zbw:bofitp:urn:nbn:fi:bof-201511031430 is not listed on IDEAS
    6. Holz, Carsten A., 2014. "The quality of China's GDP statistics," China Economic Review, Elsevier, vol. 30(C), pages 309-338.
    7. repec:zbw:bofitp:2015_029 is not listed on IDEAS
    8. Baum, Christopher F. & Kurov, Alexander & Wolfe, Marketa Halova, 2015. "What do Chinese macro announcements tell us about the world economy?," Journal of International Money and Finance, Elsevier, vol. 59(C), pages 100-122.
    9. Pang, Ke & Siklos, Pierre L., 2016. "Macroeconomic consequences of the real-financial nexus: Imbalances and spillovers between China and the U.S," Journal of International Money and Finance, Elsevier, vol. 65(C), pages 195-212.
    10. John G. Fernald & Eric Hsu & Mark M. Spiegel, 2015. "Is China fudging its figures? Evidence from trading partner data," Working Paper Series 2015-12, Federal Reserve Bank of San Francisco.
    11. Pang, Ke & Siklos, Pierre L., 2016. "Macroeconomic consequences of the real-financial nexus: Imbalances and spillovers between China and the U.S," Journal of International Money and Finance, Elsevier, vol. 65(C), pages 195-212.
    12. Harry X. Wu & Eric Girardin, 2016. "The ‘new’ normal is ‘old’ in China: Very late catching up and return to the (pre-WTO) old normal," EcoMod2016 9721, EcoMod.
    13. Fernald, John G. & Hsu, Eric & Spiegel, Mark M., 2021. "Reprint: Is China fudging its GDP figures? Evidence from trading partner data," Journal of International Money and Finance, Elsevier, vol. 114(C).

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    More about this item

    Keywords

    China; Real-time data; Data revisions; Forecasting; Real GDP; Real GNP;
    All these keywords.

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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