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A Review and Reflection on the Use and Abuse of Chinese Industrial Enterprises Database


  • Nie, Huihua
  • Jiang, Ting
  • Yang, Rudai


Empirical research has called for intensive use of disaggregated data. One of the most heavily used data set in studying the corporate behavior and performance in China is Chinese Industrial Enterprises Database. As we will show, this data set suffers from data matching problems as well as measurement errors, unrealistic outliers and definition ambiguities etc., all of which practically lead to research results thereupon that are at best questionable. In this article, we briefly summarize the data set, selectively review its uses in previous studies, address some critical issues regarding its usage, and propose some remedies and recommendations.

Suggested Citation

  • Nie, Huihua & Jiang, Ting & Yang, Rudai, 2012. "A Review and Reflection on the Use and Abuse of Chinese Industrial Enterprises Database," MPRA Paper 50945, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:50945

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    References listed on IDEAS

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    10. Hongbin Cai & Qiao Liu, 2009. "Competition and Corporate Tax Avoidance: Evidence from Chinese Industrial Firms," Economic Journal, Royal Economic Society, vol. 119(537), pages 764-795, April.
    11. Bai, Chong-En & Lu, Jiangyong & Tao, Zhigang, 2009. "How does privatization work in China?," Journal of Comparative Economics, Elsevier, vol. 37(3), pages 453-470, September.
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    Cited by:

    1. Wu, Yiyun & Zhu, Xiwei, 2017. "Why Geographic Dispersion Before Its Time: Industrial Policy and Economic Geography in the People’s Republic of China," ADBI Working Papers 633, Asian Development Bank Institute.
    2. Peng Bin & Xiaolan Chen & Andrea Fracasso & Chiara Tomasi, 2017. "Resource allocation and productivity across provinces in China," DEM Working Papers 2017/02, Department of Economics and Management.
    3. Dang, Jianwei & Motohashi, Kazuyuki, 2015. "Patent statistics: A good indicator for innovation in China? Patent subsidy program impacts on patent quality," China Economic Review, Elsevier, vol. 35(C), pages 137-155.
    4. Marco Bee & Maria Michela Dickson & Flavio Santi, 2017. "Likelihood-based Risk Estimation for Variance-Gamma Models," DEM Working Papers 2017/03, Department of Economics and Management.
    5. repec:eee:chieco:v:44:y:2017:i:c:p:296-310 is not listed on IDEAS
    6. Ankai Xu, 2016. "Environmental regulations and competitiveness: evidence based on Chinese firm data," CIES Research Paper series 47-2016, Centre for International Environmental Studies, The Graduate Institute.
    7. Gabriella Berloffa & Eleonora Matteazzi & Paola Villa, 2017. "The intergenerational transmission of worklessness in Europe.The role of fathers and mothers," DEM Working Papers 2017/04, Department of Economics and Management.
    8. Pedro Naso & Yi Huang Author Name: Tim Swanson, 2017. "The Porter Hypothesis Goes to China: Spatial Development, Environmental Regulation and Productivity," CIES Research Paper series 53-2017, Centre for International Environmental Studies, The Graduate Institute.
    9. Rudai Yang & Canfei He, 2014. "The productivity puzzle of Chinese exporters: Perspectives of local protection and spillover effects," Papers in Regional Science, Wiley Blackwell, vol. 93(2), pages 367-384, June.
    10. Du, Jun & Liu, Xiaoxuan & Zhou, Ying, 2014. "State advances and private retreats? — Evidence of aggregate productivity decomposition in China," China Economic Review, Elsevier, vol. 31(C), pages 459-474.
    11. Gabriella Berloffa & Eleonora Matteazzi & Alina Sandor & Paola Villa, 2017. "The quality of employment in the early labour market experience of young Europeans," DEM Working Papers 2017/05, Department of Economics and Management.
    12. Lily Fang & Josh Lerner & Chaopeng Wu, 2016. "Intellectual Property Rights Protection, Ownership, and Innovation: Evidence from China," NBER Working Papers 22685, National Bureau of Economic Research, Inc.
    13. Jiao Wang & Ying Long, 2016. "Baseline Water Stress: China," Working Papers id:10948, eSocialSciences.

    More about this item


    Firm-level data; Industrial enterprises; Microeconometrics; Manufacturing sector; Productivity;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General


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