The effect of environmental policy on Chinese firm's green productivity and shadow price: A metafrontier input distance function approach
Ning Zhang and
Technological Forecasting and Social Change, 2019, vol. 144, issue C, 129-136
In this paper, a new parametric meta-frontier estimation method, which we call the metafrontier input distance function (MIDF), is proposed to construct a new green productivity index and the shadow price for Chinese coal-fired power plants. Taking the policy heterogeneity into account, 93 Chinese coal-fired power plants are divided into two groups based on whether they are located in China's key “environmental protection cities”, a Chinese environmental protection policy. Using this method, the productivity and the shadow price of the two groups are compared. We find that the average annual growth rate of green productivity of coal-fired power plants in key environmental protection cities is 5.11% from 2005 to 2010, while in the non-key environmental protection cities it is 9.43%, suggesting that environmental regulation will damage productivity growth. Interestingly, although coal-fired power plants in key environmental protection cities face more stringent environmental regulation, their green productivity index still shows an overall upward trend, which partially supports the Porter hypothesis. For the shadow price of sulfur dioxide (SO2), the group-based shadow price of coal-fired power plants in key environmental protection cities is 5419 US dollar per ton on average, while in non-key environmental protection cities it is 1628 US dollar per ton, which also indicates that power plants facing more stringent regulation bear greater abatement costs.
Keywords: Metafrontier input distance function; Green productivity index; Shadow price; China; Environmental policy (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:144:y:2019:i:c:p:129-136
Access Statistics for this article
Technological Forecasting and Social Change is currently edited by Fred Phillips
More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().