| 中国旅游业全要素碳生产率动态演进及其影响因素 |
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| 引用本文： | 王凯,马月琴,甘畅,张淑文,刘浩龙.中国旅游业全要素碳生产率动态演进及其影响因素[J].环境科学研究,2020,33(10):2388-2398. |
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| 作者姓名： | 王凯 马月琴 甘畅 张淑文 刘浩龙 |
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| 作者单位： | 1.湖南师范大学旅游学院, 湖南 长沙 410081 |
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| 基金项目： | 湖南省社会科学基金项目（No.18YBA318） |
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| 摘 要： | 为探清中国旅游业全要素碳生产率（total factor carbon productivity，TFCP）增长演化特征及影响因素，运用Malmquist-Luenberger指数测算2000—2017年中国30个省（自治区、直辖市）旅游业TFCP及其分解（不含港澳台及西藏自治区数据，下同），借助核密度估计揭示其动态演进趋势，并建立面板数据模型探究影响旅游业TFCP的关键因素.结果表明:①2000—2017年，中国旅游业TFCP平均增长率为6.2%，呈现中部高于东部、东部高于西部的空间增长格局，且技术进步是其增长的主要驱动力.②中国共有28个省份的旅游业TFCP呈现正增长，其中吉林省的增幅最高，而青海省、宁夏回族自治区旅游业TFCP出现下降；旅游业碳排放技术“创新者”主要为天津市、河南省、山西省、上海市和内蒙古自治区.③旅游业累积TFCP和累积技术进步均存在明显提升，但二者省际差距有所扩大；而累积技术效率虽然省际差距在缩小，但效率提高幅度不明显，且呈一定倒退趋势.④全国范围内，旅游业经济规模、产业结构和对外开放程度分别在1%、1%和10%的显著性水平上正向促进旅游业TFCP，旅游业能源强度、旅游业碳排放结构及城镇化水平在1%的显著性水平上负向影响旅游业TFCP，环境规制对其影响不显著.研究显示，中国旅游业TFCP虽波动性较大，但整体呈增长趋势，技术进步的贡献高于技术效率的贡献，今后在依靠技术进步提升旅游业TFCP的同时，更要注重改善技术效率.
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| 关 键 词： | 旅游业 全要素碳生产率 Malmquist-Luenberger指数 核密度估计 |
| 收稿时间： | 2019/10/5 0:00:00 |
| 修稿时间： | 2020/6/19 0:00:00 |
Dynamic Evolution and Influencing Factors of Total Factor Carbon Productivity in China's Tourism Industry |
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| WANG Kai,MA Yueqin,GAN Chang,ZHANG Shuwen,LIU Haolong.Dynamic Evolution and Influencing Factors of Total Factor Carbon Productivity in China's Tourism Industry[J].Research of Environmental Sciences,2020,33(10):2388-2398. |
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| Authors: | WANG Kai MA Yueqin GAN Chang ZHANG Shuwen LIU Haolong |
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| Affiliation: | 1.Tourism College of Hunan Normal University, Changsha 410081, China2.Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China |
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| Abstract: | In order to explore the growth characteristics and influencing factors of total factor carbon productivity (TFCP) in China's tourism industry, this paper uses the Malmquist-Luenberger index to calculate the tourism TFCP and its decomposition in 30 provinces in China from 2000 to 2017(excluding the data of Hong Kong, Macao, Taiwan and Tibet Autonomous Region). Then dynamic evolution is revealed by the kernel density estimation, and a panel data model is established to explore the key factors of tourism TFCP. The results show that:(1) From 2000 to 2017, the average growth rate of China's tourism TFCP is 6.2%, indicating a growth pattern in which the central region is higher than eastern region and the east is higher than the west. The technology progress is the main driving force for the tourism TFCP. (2) The tourism TFCP in 28 provinces show positive growth, among which Jilin Province has the highest growth rate, while Qinghai Province and Ningxia Hui Autonomous Region decline. The 'innovators' of tourism carbon emission frontier technology are mainly Tianjin City, Henan Province, Shanxi Province, Shanghai City and Inner Mongolia Autonomous Region. (3) The accumulated TFCP and accumulated technology progress in tourism have been significant improved, while the inter-provincial gap is widening. Although the accumulated technology efficiency is narrowing, the efficiency improvement is not obvious and it has a certain backward trend. (4) Across the country, the scale of tourism economy, industrial structure and opening degree have promoted the tourism TFCP to the significant levels of 1%, 1% and 10%, respectively. The energy intensity of tourism, the tourism carbon emission structure and urbanization level all negatively affect the tourism TFCP at a significant level of 1%, while the environmental regulations have no obvious impact on it. The research shows that although the TFCP in China's tourism is relatively volatile, the overall trend is increasing. The contribution of technology progress is higher than that of technology efficiency. In the future, China should pay more attention to improving the efficiency while relying on technology progress to promote the tourism TFCP. |
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| Keywords: | tourism total factor carbon productivity Malmquist-Luenberger index kernel density estimation |
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