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建立旅游、能源消耗、污染物排放和城市化之间的相互作用模型:面板 VAR 的新证据。

Modelling the interaction between tourism, energy consumption, pollutant emissions and urbanization: renewed evidence from panel VAR.

机构信息

Department of Accounting, Finance and Economics, Bournemouth University, Poole, UK.

Faculty of Economics and Administrative Sciences, Istanbul Gelisim University, Istanbul, Turkey.

出版信息

Environ Sci Pollut Res Int. 2020 Nov;27(31):38881-38900. doi: 10.1007/s11356-020-09869-9. Epub 2020 Jul 7.

DOI:10.1007/s11356-020-09869-9
PMID:32638306
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7525282/
Abstract

In less than two decades, the global tourism industry has overtaken the construction industry as one of the biggest polluters, accounting for up to 8% of global greenhouse gas emissions as reported by the United National World Trade Organization (UNWTO 2018). This position resonates the consensus of the United Nations Framework Convention on Climate Change (UNFCCC). Consequently, research into the causal link between emissions and the tourism industry has increased significantly focusing extensively on top earners from the industry. However, few studies have thoroughly assessed this relationship for small island economies that are highly dependent on tourism. Hence, this study assessed the causal relationship between CO emissions, real GDP per capita (RGDP) and the tourism industry. The analysis is conducted for seven tourism-dependent countries for the period 1995 to 2014 using panel VAR approach, with support from fully modified ordinary least square and pooled mean group-autoregressive distributed lag models. Unit root tests confirm that all variables are stationary at first difference. Our VAR Granger causality/block exogeneity Wald test results show a unidirectional causality flowing from tourism to CO emission, RGDP and energy consumption, but a bi-directional causality exists between tourism and urbanization. This implies that in countries that depend on tourism, the behaviour of CO emission, RGDP and energy consumption can be predicted by the volume of tourist arrivals, but not the other way around. The impulse response analysis also shows that the responses of tourism to shocks in CO appear negative within the 1st year, positive within the 2nd and 3rd years but revert to equilibrium in the fourth year. Finally, the reaction of tourism to shocks in energy consumption is similar to its reaction to shocks in RGDP. Tourism responds positively to shocks in urbanization throughout the periods. These outcomes were resonated by the Dumitrescu and Hurlin causality analysis where the growth-induced tourism hypothesis is validated as well as feedback causality observed between tourism and pollutant emission and urbanization and pollutant emission in the blocks over the sampled period. Consequently, this study draws pertinent energy and tourism policy implications for sustainable tourism on the panel over their growth trajectory without compromise for green environment.

摘要

在不到二十年的时间里,全球旅游业已经超过建筑业成为最大的污染者之一,根据联合国世界贸易组织(UNWTO 2018)的数据,旅游业占全球温室气体排放量的 8%。这一地位与《联合国气候变化框架公约》(UNFCCC)的共识相呼应。因此,关于排放与旅游业之间因果关系的研究显著增加,广泛关注该行业的高收入者。然而,很少有研究彻底评估对高度依赖旅游业的小岛屿经济体的这种关系。因此,本研究评估了 CO 排放、人均实际国内生产总值(RGDP)和旅游业之间的因果关系。该分析使用面板 VAR 方法对 1995 年至 2014 年期间的七个旅游业依赖国家进行,同时得到完全修正的普通最小二乘法和均值组自回归分布滞后模型的支持。单位根检验证实所有变量在一阶差分上都是平稳的。我们的 VAR Granger 因果关系/块外生性 Wald 检验结果表明,从旅游业到 CO 排放、RGDP 和能源消耗的单向因果关系,但旅游业和城市化之间存在双向因果关系。这意味着在依赖旅游业的国家,CO 排放、RGDP 和能源消耗的行为可以通过游客到达量来预测,但反之则不行。脉冲响应分析还表明,旅游业对 CO 冲击的反应在第一年为负,第二年和第三年为正,但在第四年恢复到均衡。最后,旅游业对能源消耗冲击的反应与对 RGDP 冲击的反应相似。旅游业对城市化冲击的反应在整个时期都是积极的。这些结果与 Dumitrescu 和 Hurlin 因果分析相呼应,该分析验证了增长引起的旅游业假说以及在样本期内,旅游业和污染排放以及城市化和污染排放之间在块中的反馈因果关系。因此,本研究在不影响绿色环境的情况下,为可持续旅游业在整个增长轨迹上制定了相关的能源和旅游政策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/697b0311dcac/11356_2020_9869_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/da9a09876e0b/11356_2020_9869_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/dc2e1f401568/11356_2020_9869_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/46f168248390/11356_2020_9869_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/d7ba47b1604d/11356_2020_9869_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/6b0653db51ad/11356_2020_9869_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/697b0311dcac/11356_2020_9869_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/da9a09876e0b/11356_2020_9869_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/dc2e1f401568/11356_2020_9869_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/46f168248390/11356_2020_9869_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/d7ba47b1604d/11356_2020_9869_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/6b0653db51ad/11356_2020_9869_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fc/7525282/697b0311dcac/11356_2020_9869_Fig6_HTML.jpg

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