基于DEA模型和Malmquist指数的贵州省旅游扶贫效率评价
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摘要
扶贫效率是评价减贫效果的重要指标。贵州省是国家重点贫困区域,旅游业是贵州扶贫重点产业,研究贵州旅游扶贫效率具有重要意义。运用DEA模型和Malmquist指数,从静态变化和跨期动态变化两方面就2013—2017年贵州省旅游扶贫效率进行研究分析。结果表明,贵州省旅游扶贫综合效率接近DEA有效,旅游扶贫效果显著,但也存在旅游业规模报酬递减,对经济带动作用呈下降趋势的情况。要进一步提高旅游扶贫资源与技术配置效率,优化旅游产业结构,维持和推动区域经济发展,应对2020年全面脱贫后的返贫挑战、完成乡村振兴战略任务。
Poverty alleviation efficiency is an important indicator to evaluate the effect of poverty reduction.Guizhou Province is a national key poverty-stricken area.Tourism is a major poverty-stricken industry in Guizhou.It is of great significance to study Guizhou's tourism poverty alleviation efficiency.This paper uses DEA model and Malmquist index to discuss the poverty-alleviation efficiency of tourism in Guizhou Province from 2013 to 2017 in two aspects:static change and inter-temporal dynamic change.The results show that the overall comprehensive efficiency of tourism poverty alleviation is highly close to DEA effectiveness and the effect of tourism poverty alleviation is significant.However,there are still some problems such as is a decline in the scale of tourism and a downward trend in economic driving forces.Therefore,it is necessary to further optimize the efficiency of tourism poverty alleviation resources and technology allocation,optimize the tourism industry structure,continue to maintain and promote regional economic development,respond to the challenge of returning to poverty after comprehensive poverty alleviation in 2020,and complete the strategic task of rural revitalization.
Poverty alleviation efficiency is an important indicator to evaluate the effect of poverty reduction.Guizhou Province is a national key poverty-stricken area.Tourism is a major poverty-stricken industry in Guizhou.It is of great significance to study Guizhou's tourism poverty alleviation efficiency.This paper uses DEA model and Malmquist index to discuss the poverty-alleviation efficiency of tourism in Guizhou Province from 2013 to 2017 in two aspects:static change and inter-temporal dynamic change.The results show that the overall comprehensive efficiency of tourism poverty alleviation is highly close to DEA effectiveness and the effect of tourism poverty alleviation is significant.However,there are still some problems such as is a decline in the scale of tourism and a downward trend in economic driving forces.Therefore,it is necessary to further optimize the efficiency of tourism poverty alleviation resources and technology allocation,optimize the tourism industry structure,continue to maintain and promote regional economic development,respond to the challenge of returning to poverty after comprehensive poverty alleviation in 2020,and complete the strategic task of rural revitalization.
引文
[1]王凯,甘畅,王梦晗,等.湖北省旅游扶贫效率时空格局及其影响因素[J].长江流域资源与环境,2019(4):863-871.
[2]黄渊基.连片特困地区旅游扶贫效率评价及时空分异——以武陵山湖南片区20个县(市、区)为例[J].经济地理,2017(11):229-235.
[3]SOFIELD T H B,BAUER J,DE LACY T,LIPMAN G,DAUGHERTY S.Sustainable tourism-eliminating poverty(ST-EP):an overview[Z].World Tourism Organization(WTO).2004.
[4]BABALOLA A B,AJEKIGBE P G.Poverty alleviation in Nigeria:need for the development of archaeo-tourism[J].Anatolia,2007(2):223-242.
[5]MUTANA S,CHIPFUVA T,MUCHENJE B.Is tourism in Zimbabwe developing with the poor in mind assessing the pro-poor involvement of tourism operators located near rural areas in Zimbabwe[J].Asian Social Science,2013(5):154-161.
[6]ANDERSON W.Cultural tourism and poverty alleviation in rural Kilimanjaro,Tanzania.[J].Journal of Tourism & Cultural Change,2014(3):1-17.
[7]张伟,张建春,魏鸿雁.基于贫困人口发展的旅游扶贫效应评估——以安徽省铜锣寨风景区为例[J].旅游学刊,2005(5):43-49.
[8]秦其文.湘鄂渝黔边旅游扶贫开发研究[J].地域研究与开发,2004(4):68-72.
[9]王永莉.旅游扶贫中贫困人口的受益机制研究——以四川民族地区为例[J].经济体制改革,2007(4):92-96.
[10]李国平.基于政策实践的广东立体化旅游扶贫模式探析[J].旅游学刊,2004(5):56-60.
[11]向延平,彭晓燕.旅游扶贫开发的思考与建议[J].宏观经济管理,2012(4):66-67.
[12]龙祖坤,杜倩文,周婷.武陵山区旅游扶贫效率的时间演进与空间分异[J].经济地理,2015(10):210-217.
[13]曹妍雪,马蓝.基于三阶段DEA的我国民族地区旅游扶贫效率评价[J].华东经济管理,2017(9):91-97.
[14]宋瑞.我国旅游业全要素生产率研究——基于分行业数据的实证分析[J].中国社会科学院研究生院学报,2017(6):72-80.
[15]黎巧荣,杨效忠.基于DEA模型的安徽省大别山贫困片区旅游扶贫效率[J].皖西学院学报,2017(2):119-124.
[16]李光明,马磊.旅游精准扶贫效率测度及空间分异研究——以新疆阿勒泰地区为例[J].新疆社科论坛,2016(5):22-28;43.
[17]王松茂,郭英之.旅游扶贫效率评价模型构建及实证研究——来自中国的经验证据[J].社会科学家,2018(6):88-97.
[18]李银昌.中国旅游扶贫效率:基于DEA视窗分析和非线性门槛效应的研究[D].南宁:广西大学,2018.
[19]邓小海,曾亮,罗明义,等.云南乌蒙山片区所属县旅游扶贫效应分析[J].生态经济,2015(2):134-338.
①见中华人民共和国国务院新闻办公室网站,2019年8月9日《国新办举行“决战脱贫攻坚中的多彩贵州”发布会》(http://www.scio.gov.cn/xwfbh/xwbfbh/wqfbh/39595/41294/index.htm.)。
②数据包络分析法(DEA)是研究多投入、多产出的决策单元(DMU)间相对有效性的一种系统分析方法。DEA具有不需考虑投入产出之间生产函数、可处理不同类型数据、不需预先估计任何参数与权重等优点。
③参考有关学者将旅游总收入与国内生产总值(GDP)的比值作为旅游经济贡献率的做法[19],运用旅游经济贡献率这一指标计算得出旅游贡献额。
[2]黄渊基.连片特困地区旅游扶贫效率评价及时空分异——以武陵山湖南片区20个县(市、区)为例[J].经济地理,2017(11):229-235.
[3]SOFIELD T H B,BAUER J,DE LACY T,LIPMAN G,DAUGHERTY S.Sustainable tourism-eliminating poverty(ST-EP):an overview[Z].World Tourism Organization(WTO).2004.
[4]BABALOLA A B,AJEKIGBE P G.Poverty alleviation in Nigeria:need for the development of archaeo-tourism[J].Anatolia,2007(2):223-242.
[5]MUTANA S,CHIPFUVA T,MUCHENJE B.Is tourism in Zimbabwe developing with the poor in mind assessing the pro-poor involvement of tourism operators located near rural areas in Zimbabwe[J].Asian Social Science,2013(5):154-161.
[6]ANDERSON W.Cultural tourism and poverty alleviation in rural Kilimanjaro,Tanzania.[J].Journal of Tourism & Cultural Change,2014(3):1-17.
[7]张伟,张建春,魏鸿雁.基于贫困人口发展的旅游扶贫效应评估——以安徽省铜锣寨风景区为例[J].旅游学刊,2005(5):43-49.
[8]秦其文.湘鄂渝黔边旅游扶贫开发研究[J].地域研究与开发,2004(4):68-72.
[9]王永莉.旅游扶贫中贫困人口的受益机制研究——以四川民族地区为例[J].经济体制改革,2007(4):92-96.
[10]李国平.基于政策实践的广东立体化旅游扶贫模式探析[J].旅游学刊,2004(5):56-60.
[11]向延平,彭晓燕.旅游扶贫开发的思考与建议[J].宏观经济管理,2012(4):66-67.
[12]龙祖坤,杜倩文,周婷.武陵山区旅游扶贫效率的时间演进与空间分异[J].经济地理,2015(10):210-217.
[13]曹妍雪,马蓝.基于三阶段DEA的我国民族地区旅游扶贫效率评价[J].华东经济管理,2017(9):91-97.
[14]宋瑞.我国旅游业全要素生产率研究——基于分行业数据的实证分析[J].中国社会科学院研究生院学报,2017(6):72-80.
[15]黎巧荣,杨效忠.基于DEA模型的安徽省大别山贫困片区旅游扶贫效率[J].皖西学院学报,2017(2):119-124.
[16]李光明,马磊.旅游精准扶贫效率测度及空间分异研究——以新疆阿勒泰地区为例[J].新疆社科论坛,2016(5):22-28;43.
[17]王松茂,郭英之.旅游扶贫效率评价模型构建及实证研究——来自中国的经验证据[J].社会科学家,2018(6):88-97.
[18]李银昌.中国旅游扶贫效率:基于DEA视窗分析和非线性门槛效应的研究[D].南宁:广西大学,2018.
[19]邓小海,曾亮,罗明义,等.云南乌蒙山片区所属县旅游扶贫效应分析[J].生态经济,2015(2):134-338.
①见中华人民共和国国务院新闻办公室网站,2019年8月9日《国新办举行“决战脱贫攻坚中的多彩贵州”发布会》(http://www.scio.gov.cn/xwfbh/xwbfbh/wqfbh/39595/41294/index.htm.)。
②数据包络分析法(DEA)是研究多投入、多产出的决策单元(DMU)间相对有效性的一种系统分析方法。DEA具有不需考虑投入产出之间生产函数、可处理不同类型数据、不需预先估计任何参数与权重等优点。
③参考有关学者将旅游总收入与国内生产总值(GDP)的比值作为旅游经济贡献率的做法[19],运用旅游经济贡献率这一指标计算得出旅游贡献额。
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