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Measuring market concentration in China: the problem with using censored data and its rectification

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  • Bai, Chong-En
  • Mao, Jie
  • Zhang, Qiong

Abstract

This paper utilizes the non-linear estimation method to simulate the Zipf distribution, and constructs an alternative measure of Hirschman–Herfindahl index (HHI), in order to reveal the real changes in monopoly of China's industrial markets. Based on the annual waves of the Chinese Industrial Enterprises Database between 1998 and 2009, it finds that: 1) systematic bias of deceptive declining concentration would be very easy to appear when directly using censored survey data with some invariant threshold; 2) with method in this article, an alternative measure of China's market concentration (namely, the estimated Zipfian parameter) can be produced to better depict monopoly trend, even though small firms are censored out in the market surveys and commonly used HHI cannot avoid such systematic bias; and 3) China actually experiences much less competition improvement or monopoly reduction in many industries during this period.

Suggested Citation

  • Bai, Chong-En & Mao, Jie & Zhang, Qiong, 2014. "Measuring market concentration in China: the problem with using censored data and its rectification," China Economic Review, Elsevier, vol. 30(C), pages 432-447.
  • Handle: RePEc:eee:chieco:v:30:y:2014:i:c:p:432-447
    DOI: 10.1016/j.chieco.2014.05.013
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    Cited by:

    1. Zhang, Qiong & Shi, Yupeng & He, Angda & Wen, Xueting, 2017. "Property rights security and firm survival: Micro-data evidence from China," China Economic Review, Elsevier, vol. 44(C), pages 296-310.
    2. Ashish Kumar Sedai, 2019. "Wages in Imperfect Markets: A Post-reforms Study of Indian Manufacturing," Journal of South Asian Development, , vol. 14(3), pages 257-280, December.
    3. Maurizio Naldi & Marta Flamini, 2017. "Censoring and Distortion in the Hirschman–Herfindahl Index Computation," Economic Papers, The Economic Society of Australia, vol. 36(4), pages 401-415, December.
    4. Vitezić Vanja & Srhoj Stjepan & Perić Marko, 2018. "Investigating Industry Dynamics in a Recessionary Transition Economy," South East European Journal of Economics and Business, Sciendo, vol. 13(1), pages 43-67, June.
    5. Barbieri, Elisa & Huang, Manli & Pi, Shenglei & Pollio, Chiara & Rubini, Lauretta, 2021. "Investigating the linkages between industrial policies and M&A dynamics: Evidence from China," China Economic Review, Elsevier, vol. 69(C).
    6. Mao, Jie & Tang, Shiping & Xiao, Zhiguo & Zhi, Qiang, 2021. "Industrial policy intensity, technological change, and productivity growth: Evidence from China," Research Policy, Elsevier, vol. 50(7).
    7. Kordanuli, Bojana & Barjaktarović, Lidija & Jeremić, Ljiljana & Alizamir, Meysam, 2017. "Appraisal of artificial neural network for forecasting of economic parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 515-519.

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    More about this item

    Keywords

    Zipf distribution; Statistical methods; Hirschman–Herfindahl index; Systematic bias;
    All these keywords.

    JEL classification:

    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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