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Chinese statistics: classification systems and data sources

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  • Holz, Carsten A

Abstract

China has become a popular geographic area of research. Researchers make extensive use of Chinese official statistics, but these statistics are often not well understood. This article first clarifies three major issues that affect a wide range of Chinese statistics—from output and employment data to industry profitability—and then elaborates on data sources. The three data issues are changes over time to the sectoral classification system, changes to the ownership classification system, and changes to the coverage of the industry sector. Many of these changes have gone unnoticed or remain poorly understood, leaving the researcher puzzled about varying labels, apparently inconsistent data, and discontinued time series. The second part of the paper offers a gateway to a wealth of Chinese statistics whose existence is not widely known. It also points out the limitations of some of these sources and provides an overview of the secondary literature that discusses the meaning and quality of particular Chinese statistics.

Suggested Citation

  • Holz, Carsten A, 2013. "Chinese statistics: classification systems and data sources," MPRA Paper 43869, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:43869
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    File URL: https://mpra.ub.uni-muenchen.de/43869/1/MPRA_paper_43869.pdf
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    References listed on IDEAS

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    1. Sinton, Jonathan E., 2001. "Accuracy and reliability of China's energy statistics," China Economic Review, Elsevier, vol. 12(4), pages 373-383.
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    Citations

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    Cited by:

    1. Holz, Carsten A, 2013. "Monthly industrial output in China since 1983," MPRA Paper 43867, University Library of Munich, Germany.
    2. repec:eee:regeco:v:65:y:2017:i:c:p:116-126 is not listed on IDEAS
    3. Holz, Carsten A., 2014. "The quality of China's GDP statistics," China Economic Review, Elsevier, vol. 30(C), pages 309-338.
    4. repec:eee:chieco:v:44:y:2017:i:c:p:327-342 is not listed on IDEAS
    5. Matthias Duschl & Shi-Shu Peng, 2013. "Chinese firm dynamics and the role of ownership type A conditional estimation approach of the Asymmetric Exponential Power (AEP) density," Papers on Economics and Evolution 2014-01, Philipps University Marburg, Department of Geography.
    6. Ting Wang & Areendam Chanda, 2016. "Manufacturing Growth and Local Multipliers in China," Departmental Working Papers 2016-02, Department of Economics, Louisiana State University.
    7. repec:bla:jecsur:v:31:y:2017:i:4:p:905-922 is not listed on IDEAS
    8. Carsten A. Holz, 2017. "The Chaning Patterns of Investment in the PRC Economy," CESifo Working Paper Series 6484, CESifo Group Munich.
    9. John Gibson & Chao Li, 2017. "The Erroneous Use Of China'S Population And Per Capita Data: A Structured Review And Critical Test," Journal of Economic Surveys, Wiley Blackwell, vol. 31(4), pages 905-922, September.
    10. Chao Li & John Gibson, 2016. "Pareto's Law and City Size in China: Diverging Patterns in Land and People," Working Papers in Economics 16/09, University of Waikato.
    11. Ma, Ben & Song, Guojun & Zhang, Lei & Sonnenfeld, David A., 2014. "Explaining sectoral discrepancies between national and provincial statistics in China," China Economic Review, Elsevier, vol. 30(C), pages 353-369.

    More about this item

    Keywords

    (all: China) national income accounting; national statistical system; China Standard Industrial Classification System; industrial statistics coverage; ownership classification system; national statistical data sources/limitations/explanations;

    JEL classification:

    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • P27 - Economic Systems - - Socialist Systems and Transition Economies - - - Performance and Prospects

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