Scenario-Based Forecasting of the Impact of Tax Incentives on Green R&D in China’s Wind Power Industry in a Complex Network Environment

Ying Wang and Igor Mayburov ()
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Ying Wang: Institute of Economics and Management, Ural Federal University Named After the First President of Russia B.N. Yeltsin, Yekaterinburg 620002, Russia

Sustainability, 2025, vol. 17, issue 4, 1-33

Abstract: Due to the deteriorating ecological environment in recent years, many countries have introduced relevant policies to support the development of clean energy. This paper focuses on wind power generation as the subject for examining green R&D diffusion. Many enterprises take advantage of the information asymmetry between them and the government to carry out fake research and development and cheat taxes, resulting in a large loss of fiscal revenue for the state. The aim of the study is to simulate different scenarios for the diffusion of green R&D in China’s wind energy industry under different tax rates, incentives, and penalties. The results of the study show that the state’s ability to increase penalties can inhibit firms’ behavior of camouflaging R&D. Under the current tax incentives, the introduction of green R&D quotas in the electricity market, coupled with strong penalties, can increase the real green R&D capability of enterprises. The government’s implementation of zero R&D tax incentives and strong penalties do not increase firms’ green R&D capabilities. The diffusion effect of green R&D is more significant in the context of strong market demand. This suggests that the introduction of a quota system can encourage firms to accelerate the pace of technological innovation, while a strict regulatory environment is necessary to avoid policy abuse and optimize resource allocation.

Keywords: wind power industry; diffusion of green R&D; tax incentives; complex network environment (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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