The Mechanism and Countermeasures of the Impact of State Subsidy Backslide on the Efficiency of Waste-to-Energy Enterprises—A Case Study in China

Huo-Gen Wang and Han Rao ()
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Huo-Gen Wang: College of Economics and Management, Jiangxi Agriculture University, Nanchang 330045, China
Han Rao: College of Economics and Management, Jiangxi Agriculture University, Nanchang 330045, China

Sustainability, 2023, vol. 15, issue 19, 1-15

Abstract: The scientific investment decision model of waste incineration power generation is helpful in providing a scientific basis for the government and environmental protection enterprises to formulate reasonable waste prices. The waste incineration power generation project revenue and cost composition framework, based on the project net present value of factors affecting causality analysis, the construction of a waste incineration power generation PPP project net present value system dynamics model, and the use of Vensim PLE software, version 7.3.5, combined with the garbage power generation of listed companies, was built, and we put into use the enterprise’s financial data and the author’s research of the case of the BOT (Build–Operate–Transfer) project data to examine the validity of the model test, simulation, and sensitivity analysis. The results show that the regression of a national subsidy does not necessarily lead to a price adjustment of the waste disposal fee, and when a change in tariff subsidy occurs, the loss brought by the reduction in a feed-in tariff can be compensated by increasing the income from carbon sinks, decreasing the intensity of investment through technological advancement, improving the coefficient of waste power generation through garbage classification, and increasing the utilization of production capacity through the treatment of multiple wastes in a single or a combination of ways.

Keywords: electricity tariff rebate; waste disposal fees; carbon emission reduction; system dynamics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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