five

Descriptive statistical results.

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NIAID Data Ecosystem2026-05-01 收录
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https://figshare.com/articles/dataset/Descriptive_statistical_results_/24691376
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资源简介:
The implementation of tax reduction policies in China represents a significant and effective strategy. Accordingly, this strategy has been designed to facilitate the development of a green economy by establishing a market-oriented allocation system for environmental and resource elements, while simultaneously invigorating microeconomic entities. As the nation navigates towards the adoption of green, low-carbon production, and lifestyles, the role of clean and green energy emerges as a vital necessity. Therefore, to explain the impact of tax reduction policies on the green energy industry, this study collected and compiled financial indicator data from 100 listed companies in the green energy sector, utilizing the China Stock Market Accounting Research database (CSMAR) as a source for research samples. A Panel Vector Auto Regression (PVAR) model was employed to observe the effects of tax reduction policies on the energy industry, while the dosage effects Difference in Difference (DID) model was utilized to verify and supplement the findings. In summary, the findings of this study can be summarized as follows: firstly, tax reduction policies exert a positive impact on the green energy industry by effectively mitigating the financial cost burden on green energy enterprises, thereby reducing production expenses and amplifying their profitability. Secondly, such policies bolster the capital turnover rate of enterprises in the short term, thereby enabling augmented research and development investments, refining production efficiency, and enhancing competitiveness. Through rigorous analysis and demonstration, the research findings accentuate the stimulative and propulsive impacts of tax reduction policies on the flourishing development of the green energy industry. Furthermore, this study provides relevant fiscal and tax policy recommendations, thoughtfully derived from the research findings.
创建时间:
2023-11-30
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