基于EKC框架的旅游发展对区域碳排放的影响分析——基于1995-2015年中国省际面板数据

doi:10.11821/dlyj201804008

地理研究 ›› 2018, Vol. 37 ›› Issue (4): 742-750.doi: 10.11821/dlyj201804008

基于EKC框架的旅游发展对区域碳排放的影响分析——基于1995-2015年中国省际面板数据

王凯¹(), 邵海琴¹, 周婷婷¹, 邓楚雄²()

1. 湖南师范大学旅游学院,长沙 410081
2. 湖南师范大学资源与环境科学院,长沙 410081

收稿日期:2017-10-19 修回日期:2018-01-30 出版日期:2018-04-20 发布日期:2018-04-20
作者简介:
作者简介：王凯（1969- ）,男,湖南新宁人,博士,教授,主要从事低碳经济、区域旅游发展规划研究。E-mail: kingviry@163.com
基金资助:
湖南省教育厅科学研究重点项目（14A088）;国家社会科学基金项目（16BJL063）

EKC framework analysis of the effects of tourism development on regional carbon emissions: Based on China's 1995-2015 panel data

Kai WANG¹(), Haiqin SHAO¹, Tingting ZHOU¹, Chuxiong DENG²()

1. Tourism College of Hunan Normal University, Changsha 410081, China
2. Resource and Environment Science College of Hunan Normal University, Changsha 410081, China

Received:2017-10-19 Revised:2018-01-30 Online:2018-04-20 Published:2018-04-20
About author:
Author: Shi Zhenqin (1988-), PhD, specialized in regional development and land space management in mountain areas. E-mail: kevinszq@163.com

^*Corresponding author: Deng Wei (1957-), Professor, specialized in mountain environment and regional development.

E-mail: dengwei@imde.ac.cn

摘要/Abstract

摘要：

基于扩展的环境库兹涅茨曲线（EKC）,利用1995-2015年中国省际面板数据探讨旅游发展对区域碳排放的影响,同时分析了经济增长、贸易开放程度、失业率、受教育程度和城市化水平等因素对碳排放的影响作用。研究表明：① 传统经济增长与碳排放之间的倒“U”型EKC假说成立,受教育程度（-0.061）、失业率（-0.062）和贸易开放程度（-0.170）的提升有利于降低人均CO₂排放量,其中,贸易开放程度的减排作用最为明显;城市化水平（2.113）的提高会增加人均CO₂排放量。② 旅游发展对区域碳排放的影响显著,具体表现为：旅游接待人次与人均CO₂排放量拟合曲线呈正“U”型,而人均旅游消费与人均CO₂排放量则呈现典型的倒“U”型曲线良性发展状态。③ 旅游专业化水平的提高会使得EKC向下方移动,经济发展的环境压力得到减轻,且高旅游专业化区域旅游接待人次与人均CO₂排放量之间关系的转折点相对较高,而其人均旅游消费与人均CO₂排放量之间关系的转折点则相对较低。

关键词: 环境库兹涅茨曲线, 旅游发展, 碳排放, 中国

Abstract:

In the context of global warming, it is of great significance to analyze the impact of tourism development on regional carbon emissions regarding promotion of the sustainable development of tourism. Based on EKC Theory and related literatures, this paper tried to develop the EKC Theoretical Model by introducing tourism development variables and exploring the effects of tourism development on regional carbon emissions on the basis of the provincial panel data of China during 1995-2015. Meanwhile, we examined the effects of economic growth, opening degree of trade, unemployment rate, education level and urbanization level on carbon emissions. Results show that the inverse U-shaped EKC relationship exists between per capita CO₂ emissions and per capita GDP. In addition, the education level (-0.061), unemployment rate (-0.062) and opening degree of trade (-0.170) would be conductive to per capita CO₂ emissions reduction, among which the biggest contributor is the opening degree of trade, while the urbanization level (2.113) would tend to increase the per capita CO₂ emissions. Moreover, the development of tourism has a significant impact on per capita CO₂ emissions. To be specific, the fitting curve of tourist reception and per capita CO₂ emissions shows a positive "U"-type, while that of per capita tourism consumption and per capita CO₂ emissions is a typically inverted "U"-shaped curve. Furthermore, the level of tourism specialization has a significant effect on the peak and position of EKC. More specifically, the improvement of tourism specialization level will cause the EKC to move downward so that environmental pressures of economic development will be alleviated, and the turning point of the curve reflecting the relationship between tourism arrivals and per capita CO₂ emissions in the regions with high-level specialization of tourism is relatively higher than in other regions, while that of per capita tourism consumption and per capita CO₂ emissions is at lower levels. Finally, some policies for the low-carbon tourism economy are recommended.

Key words: environmental Kuznets curve, tourism development, carbon emissions, China

王凯, 邵海琴, 周婷婷, 邓楚雄. 基于EKC框架的旅游发展对区域碳排放的影响分析——基于1995-2015年中国省际面板数据[J]. 地理研究, 2018, 37(4): 742-750.

Kai WANG, Haiqin SHAO, Tingting ZHOU, Chuxiong DENG. EKC framework analysis of the effects of tourism development on regional carbon emissions: Based on China's 1995-2015 panel data[J]. GEOGRAPHICAL RESEARCH, 2018, 37(4): 742-750.

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变量符号	名称	变量说明
PCO₂	人均CO₂	CO₂/年末总人口（kg/人）
α	截距项	-
GDPPC	人均GDP	实际人均GDP（元）
TUR	旅游接待人次	旅游接待总人次（万人次）
TUREXPIND	人均旅游消费	旅游收入/旅游接待人次（元/人）
D	虚拟变量-旅游专业化水平	旅游专业化水平高于全国平均水平时等于1
TRADE	贸易开放程度	进出口总额占GDP比例（%）
UNEMP	失业率	城镇登记失业率（%）
EDU	受教育程度	每万人口中在校高中生占比（%）
URB	城市化水平	城镇人口占总人口比重（%）

Variables	Model 1		Model 2		Model 3		Model 4
Variables	Cofficient	t-Statistic	Cofficient	t-Statistic	Cofficient	t-Statistic	Cofficient	t-Statistic
c	-5.157^***	-4.640	-3.063^***	-2.692	-6.397^***	-5.282	-4.664^***	-3.278
LNGDPPC	2.257^***	9.492	1.879^***	7.637	2.046^***	8.194	2.072^***	6.613
LNGDPPC^2	-0.084^***	-6.602	-0.070^***	-5.508	-0.075^***	-5.216	-0.061^***	-3.995
UNEMP			-0.062^***	-4.473	-0.081^***	-6.536	-0.085^***	-6.893
EDU			-0.061^**	-2.065	-0.067^**	-2.556	-0.058^**	-2.190
TRADE			-0.170^***	-3.516	-0.226^***	-5.217	-0.229^***	-5.276
URB			2.113^***	6.629	2.185^***	6.956	2.285^***	7.294
LNTUR					-0.593^***	-6.948	-0.479^***	-5.047
LNTUR^2					0.047^***	10.551	0.039^***	6.697
LNTUREXPIND					0.635^***	3.104	0.522^**	2.398
LNTUREXPIND^2					-0.037^**	-2.114	-0.029^*	-1.538
DLNTUR*							-0.954^***	-4.084
DLNTUR^2*							0.053^***	4.193
DLNTUREXPIND*							1.238^***	3.841
DLNTUREXPIND^2*							-0.090^***	-3.702
Adjusted R-squared	0.823		0.848		0.884		0.888
F值	134.130		120.900		135.360		123.530

基于EKC框架的旅游发展对区域碳排放的影响分析——基于1995-2015年中国省际面板数据

EKC framework analysis of the effects of tourism development on regional carbon emissions: Based on China's 1995-2015 panel data

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