黄河流域旅游业碳排放效率综合测度及影响因素研究

doi:10.12118/j.issn.1000-6060.2023.193

Abstract

Abstract:

The quantification and assessment of carbon emission efficiency and its influencing factors in the tourism sector are crucial for advancing environmentally-friendly development in the tourism economy of Yellow River Basin, China. This study develops an input-output table for evaluating the carbon emission efficiency of tourism. In addition to traditional factors such as capital, labor, and energy, we incorporate technological innovation. The desired output is the total tourism revenue, while the non-desired output is the carbon emission during tourism, integrated into the Super-Slack-Based Measure (SBM). Employing the Malmquist-Luenberger index and the kernel density estimation method, we analyzed tourism carbon emission efficiency from both static and dynamic perspectives. Furthermore, we established a spatial Durbin model to examine spatial spillover effects. Our results revealed the following: (1) During 2000—2019, the carbon emission efficiency of tourism in the Yellow River Basin initially experienced an upward fluctuation followed by a subsequent downward trend. Provinces and regions exhibited a diminishing difference, with a spatial distribution pattern that indicated lower efficiency in the west and higher efficiency in the east. (2) Regarding dynamic efficiency, both the Malmquist-Luenberger index and kernel density estimation trends indicated a weakening polarization phenomenon in carbon emission efficiency. Technological progress significantly contributed to changes in the tourism industry’s carbon emission efficiency. (3) Influencing factors that include positive spillover effects from environmental regulation and urbanization, enhanced local tourism carbon emission efficiency. Conversely, industrial structure, openness, technology level, and tourism industry agglomeration were found to have adverse effects. Economic development levels hindered the improvement of carbon emission efficiency in tourism; however, they exhibited a notable positive spillover effect on surrounding regions. These findings aim to establish a theoretical foundation for governments to formulate targeted policies for energy-saving and carbon-emission reduction in the tourism sector.

Key words: tourism carbon emission efficiency, Super-SBM, spatial Durbin model, Yellow River Basin

DU Yaming, BAI Yongping, LIANG Jianshe, ZHANG Chunyue, JING Linxiang, WANG Liguo, ZOU Jiacheng. Comprehensive measurement and influencing factors of carbon emission efficiency of tourism in the Yellow River Basin[J].Arid Land Geography, 2023, 46(12): 2074-2085.

Figures/Tables 12

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References 41

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类型	一级指标	二级指标
投入	资本	旅游业固定资本存量/10⁸元
	劳动力	旅游业年末从业人员/10⁴人
	能源消耗	旅游业能源消耗量/MJ
	技术创新	旅游相关专利累计申请数量/个
产出	期望产出	旅游业总收入/10⁸元
产出	非期望产出	旅游业CO₂排放量/kg

省份	ML指数均值	技术效率变化指数	技术进步指数
山西	1.277	1.115	1.277
内蒙古	1.293	1.200	1.293
山东	1.206	0.994	1.206
河南	1.067	0.953	1.067
四川	1.138	1.036	1.138
陕西	1.157	1.100	1.157
甘肃	1.216	1.083	1.216
青海	1.099	0.987	1.099
宁夏	1.090	0.992	1.090
平均值	1.171	1.051	1.171

年份	全局莫兰指数	年份	全局莫兰指数
2000	0.144^**	2010	0.417^***
2001	0.169^**	2011	0.456^***
2002	0.189^**	2012	0.406^***
2003	0.211^**	2013	0.401^***
2004	0.056^**	2014	0.320^***
2005	0.236^***	2015	0.283^***
2006	0.245^***	2016	0.267^***
2007	0.392^***	2017	0.250^**
2008	0.349^***	2018	0.200^**
2009	0.422^***	2019	0.190^**

变量类型	变量名称	变量解释
被解释变量	旅游业碳排放效率（TCEE）	Super-SBM模型计算得到
解释变量	经济发展水平（ED）	人均GDP/元
	产业结构（IS）	第三产业产值占比/%
	对外开放程度（Open）	进出口总额占GDP比重/%
	环境规制（ER）	环境污染治理投资额占GDP 比重/%
	城镇化水平（Urb）	城镇人口比重/%
	技术水平（TL）	万元GDP能源消耗量（标准煤）/t·(10⁴元)^-1
	旅游产业集聚（TA）	区位熵计算得到^[37]

检验方法	特征值	检验方法	特征值
空间滞后最大似然（LM-Lag）	15.880^***	空间误差似然比（LR-Error）	156.090^***
Robust LM-Lag	52.003^***	Wald-Error	55.840^***
空间误差最大似然（LM-Error）	0.626	豪斯曼（Hausman）	22.450^***
Robust LM-Error	36.749^***	LR-time	169.59^***
空间滞后似然比（LR-Lag）	128.550^***	LR-ind	53.14^***
Wald-Lag	50.060^***

Comprehensive measurement and influencing factors of carbon emission efficiency of tourism in the Yellow River Basin

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变量	影响系数（Main）	空间滞后项系数（Wx）
经济发展水平（ED）	-0.007（0.13）	0.004^***（0.01）
产业结构（IS）	-0.364（0.17）	-6.390^***（0.00）
对外开放程度（Open）	-0.191（0.73）	-0.901（0.63）
环境规制（ER）	1.987（0.32）	6.301^*（0.08）
城镇化水平（Urb）	0.147（0.93）	19.246^***（0.00）
技术水平（TL）	-0.245^***（0.00）	-0.291（0.19）
旅游业产业集聚（TA）	-0.078^***（0.00）	-0.342^***（0.00）
拟合优度（R²）	0.3650
空间溢出效应系数（rho）	-0.1645^*
误差项（sigma2_e）	0.0225^***
时间固定	是
空间固定	是

变量	直接效应	间接效应	总效应
经济发展水平（ED）	-0.000^*（0.09）	0.004^**（0.01）	0.003^**（0.05）
产业结构（IS）	-0.150（0.62）	-5.693^***（0.00）	-5.843^***（0.00）
对外开放程度（Open）	-0.101（0.84）	-0.660（0.68）	-0.761（0.67）
环境规制（ER）	1.828（0.35）	5.270^*（0.09）	7.098^*（0.08）
城镇化水平（Urb）	-0.570（0.74）	17.597^***（0.00）	17.028^***（0.00）
技术水平（TL）	-0.235^***（0.00）	-0.226（0.28）	-0.461^***（0.00）
旅游业产业集聚（TA）	-0.068^***（0.00）	-0.293^***（0.00）	-0.361^***（0.00）

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