Shadow prices of industrial air pollutant emissions in China

Yinyin Wu, Jie Yu, Malin Song, Jiandong Chen, Wenxuan Hou

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Shadow prices of undesirable outputs assess the opportunity costs of emissions reduction and provide a comprehensive measuring indicator for the overall environmental regulation stringency. Shadow prices of industrial air pollutant emissions in China for 2006–2016 have been estimated by different nonparametric models, and their determinants, as well as the emissions controlling effects of environmental regulations, have been further investigated in this study. Our empirical results reveal that the conventional polluting technology model is consistent with the two sub-technologies model, and that shadow prices estimated by different models differed in absolute values but shared the same growth trends and regional characteristics. Decomposition results according to the logarithmic mean divisia index (LMDI) method indicate that variations in the shadow prices were due to the combined forces of the energy saving and end-of-pipe controlling effects in the analyzed periods. Moreover, we found that China’s environmental regulations with regional disparities in recent years (2006–2016) have effectively reduced industrial air pollutant emissions at an increasing rate, and that the environmental taxes imposed in 2018 still followed the existing regional unbalances of environmental regulation stringency.
Original languageEnglish
JournalEconomic Modelling
Early online date19 Feb 2020
Publication statusE-pub ahead of print - 19 Feb 2020

Keywords / Materials (for Non-textual outputs)

  • shadow prices
  • industrial air pollutant emissions
  • decomposition effects
  • environmental tax


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