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The Influence of Foreign Direct Investment and Tourism on Carbon Emission in China

The aim of this research is to examine the potential influence of FDI inflows and tourism industry on carbon dioxide emissions in China using System GMM models for a sample period of 1980–2019. Using FMOLS and DOLS models, this research examines the long-term relationship between the variables, as well as the long-term association among components. Co-joining the boards of FMOLS and DOLS models shows a general correlation between the investigation elements and CO2 emissions in China. FDI, tourism sector, and environment-friendly electricity use have all been major contributors to rising CO2 emissions in China for a long time. Using System GMM, FMOLS, and DOLS models in China, we examined the influence of the travel sector on carbon dioxide emissions as well as environment-friendly electricity usage and foreign direct investment. The government of China is being pushed to attract more foreign direct investment in order to improve the system and expand the transportation industry. As a reasonable responsibility to an unnatural climate change, methods for developing the movement business and theories relating to the movement business should be adopted.
- Southeast Asia University Thailand
- Shandong University of Technology China (People's Republic of)
- Hazara University Pakistan
- Princess Nourah bint Abdulrahman University Saudi Arabia
- Coventry University United Kingdom
Economics, FOS: Political science, Macroeconomics, Social Sciences, Economic Impact of Environmental Policies and Resources, Tourism, Engineering, Electricity, Natural resource economics, Government (linguistics), GE1-350, Business, Rebound Effect on Energy Efficiency and Consumption, Political science, Energy, Geography, Politics, FOS: Philosophy, ethics and religion, Economics, Econometrics and Finance, multivariate analysis, Archaeology, tourism industry, environmental changes, Physical Sciences, fully modified ordinary least square model, Foreign direct investment, Economics and Econometrics, China, Environmental Engineering, foreign direct investment, FOS: Law, Investment (military), CO2 emissions, FOS: Economics and business, Life Cycle Assessment and Environmental Impact Analysis, CO2 Emissions, Order (exchange), Renewable Energy, Sustainability and the Environment, FOS: Environmental engineering, Linguistics, Environmental sciences, Philosophy, Electrical engineering, Environmental Science, FOS: Languages and literature, Law, Finance
Economics, FOS: Political science, Macroeconomics, Social Sciences, Economic Impact of Environmental Policies and Resources, Tourism, Engineering, Electricity, Natural resource economics, Government (linguistics), GE1-350, Business, Rebound Effect on Energy Efficiency and Consumption, Political science, Energy, Geography, Politics, FOS: Philosophy, ethics and religion, Economics, Econometrics and Finance, multivariate analysis, Archaeology, tourism industry, environmental changes, Physical Sciences, fully modified ordinary least square model, Foreign direct investment, Economics and Econometrics, China, Environmental Engineering, foreign direct investment, FOS: Law, Investment (military), CO2 emissions, FOS: Economics and business, Life Cycle Assessment and Environmental Impact Analysis, CO2 Emissions, Order (exchange), Renewable Energy, Sustainability and the Environment, FOS: Environmental engineering, Linguistics, Environmental sciences, Philosophy, Electrical engineering, Environmental Science, FOS: Languages and literature, Law, Finance
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).3 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
