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Re-estimation of firms' total factor productivity in China's iron and steel industry

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  • Sheng, Yu
  • Song, Ligang

Abstract

Using the firm-level census data, this paper re-estimated the total factor productivity (TFP) of firms in China's iron and steel industry and examined its potential determinants over the period 1998–2007. To deal with the “endogenous input” problem, we used the semi-parametric regression techniques for estimating the firm-level TFP. The results suggest that firms' TFP in China's iron and steel industry has been steadily increasing over time with the key drivers of productivity improvement differing substantially between firms with different characteristics including their size, ownership type and geographical location. Notably, the productivity of small firms is positively related to market share and negatively related to R&D. Large state-owned enterprises' productivity is relatively insensitive to changes in market share and R&D, while the non-state owned enterprises are more likely to obtain their productivity gains through export. Increasing firm size is generally positively correlated to firms' performance in TFP, and it is more so in the less developed Western than the Eastern and Central regions. The findings suggest that different policy instruments targeting firms with different characteristics in the process of restructuring the industry may be desirable.

Suggested Citation

  • Sheng, Yu & Song, Ligang, 2013. "Re-estimation of firms' total factor productivity in China's iron and steel industry," China Economic Review, Elsevier, vol. 24(C), pages 177-188.
  • Handle: RePEc:eee:chieco:v:24:y:2013:i:c:p:177-188
    DOI: 10.1016/j.chieco.2012.12.004
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    Cited by:

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    2. Yang, Wei & Shi, Jinfeng & Qiao, Han & Shao, Yanmin & Wang, Shouyang, 2017. "Regional technical efficiency of Chinese Iron and steel industry based on bootstrap network data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 14-24.
    3. Kong, Dongmin & Tao, Yunqing & Wang, Yanan, 2020. "China's anti-corruption campaign and firm productivity: Evidence from a quasi-natural experiment," China Economic Review, Elsevier, vol. 63(C).
    4. Gong, Binlei, 2020. "Agricultural productivity convergence in China," China Economic Review, Elsevier, vol. 60(C).
    5. Satoshi Nakano & Kazuhiko Nishimura, 2015. "Quality-adjusted productivity gain in the propagation of innovation," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 4(1), pages 1-16, December.
    6. Sun, Sizhong & Anwar, Sajid, 2019. "R&D activities and FDI in China’s iron ore mining industry," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 47-56.
    7. He, Ming & Chen, Yang & van Marrewijk, Charles, 2021. "The effects of urban transformation on productivity spillovers in China," Economic Modelling, Elsevier, vol. 95(C), pages 473-488.
    8. Sun, Sizhong & Anwar, Sajid, 2015. "R&D status and the performance of domestic firms in China's coal mining industry," Energy Policy, Elsevier, vol. 79(C), pages 99-103.
    9. Hammed Amusa & Njeri Wabiri & David Fadiran, 2019. "Agglomeration and productivity in South Africa: Evidence from firm-level data," WIDER Working Paper Series wp-2019-93, World Institute for Development Economic Research (UNU-WIDER).
    10. Allen, Creina & Day, Garth, 2014. "Depletion of non-renewable resources imported by China," China Economic Review, Elsevier, vol. 30(C), pages 235-243.

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    More about this item

    Keywords

    Total factor productivity; China iron and steel industry; Production function estimation;
    All these keywords.

    JEL classification:

    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O25 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Industrial Policy

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