In recent years, the transportation industry has enjoyed the benefits brought about by changes in the national tax policy. The purpose of this paper is to analyze the impact of the change from Business Tax to Value-Added Tax (BT-to-VAT) on the tax burden of transport enterprises in various regions of China. Based on the cross-regional characteristics of the transportation industry, China is divided into four regions: eastern, central, western and northeast. Research hypothesis – the tax reduction effect of the BT-to-VAT tax burden is not only related to the characteristics of the enterprise itself, but also related to the regional environment and market integration factors of China. Using the Difference in differences (DID) method, the data covers 22 listed companies from 2009 to 2020. The paper analyzes the internal characteristics of the enterprise itself, the influence of the external environment and the degree of industrial integration on the enterprise, and the reasons for the difference. Empirical research shows that BT-to-VAT reduces the tax burden of enterprises, the eastern region has the least impact on the ratio of corporate income tax expenses to operating income, while the central and western regions have relatively greater impacts. The scale of the enterprise and the level of economic development have a positive effect on the financial efficiency of the enterprise, while the non-current assets ratio and the degree of market integration have a negative effect on the tax burden. This research is beneficial to provide reference for enterprises in different regions to improve their management and to formulate macro policies by relevant national departments.
In order to promote the high-quality and sustainable development of the alternative fuel vehicle industry, the Chinese government has given strong tax policy support. In China, the corporate income tax rate is uniformly 25%, and the government gives tax incentives to high-tech enterprises that meet the relevant appraisal standards: the tax rate is reduced by 15%. The purpose of this work is to analyze the impact of China's tax policy on the production of vehicles using alternative fuels and to assess the significance of tax incentives for the formation of significant incentives for the development of this production. The hypothesis of the study is to confirm the need to provide incentives for high-tech production of vehicles using alternative fuel to maintain a positive financial result of such production. This paper uses the OLS analysis model. Deriving data from the annual financial reports of BYD, Geely, SAIC Motor and Great Wall Motor from 2011 to 2020, analysis is carried out of the impact of income tax rate and debt ratio on net profit margin. Research has confirmed that income tax is positively correlated with net profit margin, and the debt ratio is negatively correlated with the corporate net profit margin. The higher the debt ratio, the less conducive to the improvement of the company's net profit margin. Corporate net profit margins are more sensitive to changes in income tax. This also provides an effective way to improve the tax policy to promote the development of new energy vehicles. Tax policy is the most effective tool for the government to carry out macro-control, helping to avoid the harm caused by "market failure" and guiding the development direction of the production of vehicles using alternative fuels.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.