Investigating the asymmetric impact of tourism, green fiscal policy, and fintech on environmental emissions and coastal water quality: an empirical study using the method of moments quantile regression
IntroductionThe factors that significantly and negatively impact carbon dioxide (CO2) emissions and coastal water quality (CWQ) must be continuously monitored and thoroughly evaluated. Among these, tourism (TR) volume stands out as one of the primary contributors to such effects. In contrast, green...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2024.1499558/full |
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| author | Mengqi Yang Xing Tang |
| author_facet | Mengqi Yang Xing Tang |
| author_sort | Mengqi Yang |
| collection | DOAJ |
| description | IntroductionThe factors that significantly and negatively impact carbon dioxide (CO2) emissions and coastal water quality (CWQ) must be continuously monitored and thoroughly evaluated. Among these, tourism (TR) volume stands out as one of the primary contributors to such effects. In contrast, green fiscal policy (GFP) and fintech (FT) can be considered proactive and modern efforts contributing to the improvement of these environmental indicators. Exploring whether the impacts of these factors exhibit uniformity across quantiles will greatly benefit strategic solutions aimed at avoiding resource waste.MethodsThis paper aims to calibrate procedures to apply the method of moment quantile regression (MMQR) model to address this issue. Firstly, cross-sectional dependence (CSD) among the variables is examined. Next, a stable long-term relationship between the variables is assessed using stationarity analysis. Finally, the MMQR estimation is conducted to thoroughly investigate the impact of independent variables on CWQ and CO2 across different quantiles.ResultsThe results from both the fixed effects (FE-OLS) and dynamic ordinary least squares (D-OLS) models reveal stable and significant correlations between the regressors and response variables. The research findings indicate that GFP and FT exert a significant impact on improving both CWQ and reducing CO2. In contrast, the favorable growth of the TR sector contributes negatively to CWQ and CO2.DiscussionThe paper recommends that the government increase spending and investment in green projects utilizing renewable energy, green transportation, blockchain technology, and advanced techniques. It also advocates for a strategic approach to controlling TR, focusing on enhanced waste management, in order to improve CWQ and CO2 indicators across most quantiles. |
| format | Article |
| id | doaj-art-7437484dd14c4dcb9d2b87e92e2a7ef1 |
| institution | Kabale University |
| issn | 2296-665X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Environmental Science |
| spelling | doaj-art-7437484dd14c4dcb9d2b87e92e2a7ef12025-01-07T06:50:33ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2025-01-011210.3389/fenvs.2024.14995581499558Investigating the asymmetric impact of tourism, green fiscal policy, and fintech on environmental emissions and coastal water quality: an empirical study using the method of moments quantile regressionMengqi Yang0Xing Tang1Fintech Department of CCCC Capital Holdings Co., Ltd., Beijing, ChinaInstitute of Traffic Engineering, Nanjing Vocational University of Industry Technology, Nanjing, Jiangsu, ChinaIntroductionThe factors that significantly and negatively impact carbon dioxide (CO2) emissions and coastal water quality (CWQ) must be continuously monitored and thoroughly evaluated. Among these, tourism (TR) volume stands out as one of the primary contributors to such effects. In contrast, green fiscal policy (GFP) and fintech (FT) can be considered proactive and modern efforts contributing to the improvement of these environmental indicators. Exploring whether the impacts of these factors exhibit uniformity across quantiles will greatly benefit strategic solutions aimed at avoiding resource waste.MethodsThis paper aims to calibrate procedures to apply the method of moment quantile regression (MMQR) model to address this issue. Firstly, cross-sectional dependence (CSD) among the variables is examined. Next, a stable long-term relationship between the variables is assessed using stationarity analysis. Finally, the MMQR estimation is conducted to thoroughly investigate the impact of independent variables on CWQ and CO2 across different quantiles.ResultsThe results from both the fixed effects (FE-OLS) and dynamic ordinary least squares (D-OLS) models reveal stable and significant correlations between the regressors and response variables. The research findings indicate that GFP and FT exert a significant impact on improving both CWQ and reducing CO2. In contrast, the favorable growth of the TR sector contributes negatively to CWQ and CO2.DiscussionThe paper recommends that the government increase spending and investment in green projects utilizing renewable energy, green transportation, blockchain technology, and advanced techniques. It also advocates for a strategic approach to controlling TR, focusing on enhanced waste management, in order to improve CWQ and CO2 indicators across most quantiles.https://www.frontiersin.org/articles/10.3389/fenvs.2024.1499558/fullgreen fiscal policycoastal water qualitytourismenvironmental emissionsmethod of moment quantile regressioncross-sectional dependence |
| spellingShingle | Mengqi Yang Xing Tang Investigating the asymmetric impact of tourism, green fiscal policy, and fintech on environmental emissions and coastal water quality: an empirical study using the method of moments quantile regression Frontiers in Environmental Science green fiscal policy coastal water quality tourism environmental emissions method of moment quantile regression cross-sectional dependence |
| title | Investigating the asymmetric impact of tourism, green fiscal policy, and fintech on environmental emissions and coastal water quality: an empirical study using the method of moments quantile regression |
| title_full | Investigating the asymmetric impact of tourism, green fiscal policy, and fintech on environmental emissions and coastal water quality: an empirical study using the method of moments quantile regression |
| title_fullStr | Investigating the asymmetric impact of tourism, green fiscal policy, and fintech on environmental emissions and coastal water quality: an empirical study using the method of moments quantile regression |
| title_full_unstemmed | Investigating the asymmetric impact of tourism, green fiscal policy, and fintech on environmental emissions and coastal water quality: an empirical study using the method of moments quantile regression |
| title_short | Investigating the asymmetric impact of tourism, green fiscal policy, and fintech on environmental emissions and coastal water quality: an empirical study using the method of moments quantile regression |
| title_sort | investigating the asymmetric impact of tourism green fiscal policy and fintech on environmental emissions and coastal water quality an empirical study using the method of moments quantile regression |
| topic | green fiscal policy coastal water quality tourism environmental emissions method of moment quantile regression cross-sectional dependence |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2024.1499558/full |
| work_keys_str_mv | AT mengqiyang investigatingtheasymmetricimpactoftourismgreenfiscalpolicyandfintechonenvironmentalemissionsandcoastalwaterqualityanempiricalstudyusingthemethodofmomentsquantileregression AT xingtang investigatingtheasymmetricimpactoftourismgreenfiscalpolicyandfintechonenvironmentalemissionsandcoastalwaterqualityanempiricalstudyusingthemethodofmomentsquantileregression |