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基于随机前沿分析(SFA)方法的中国旅游业全要素生产率研究 被引量:7

Research on Tourism Industry Total Factor Productivity in China—— Based on Stochastic Frontier Analysis(SFA)
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摘要 以我国1997—2009年旅游业相关数据为样本,基于随机前沿分析方法,运用Malmquist指数模型对我国各省份、东中西及全国的旅游业全要素生产率指数进行了测算,并进一步分解为技术进步指数和技术效率指数。得到以下结论:样本期内,各省份旅游业全要素生产率呈现不断增长趋势,增长较快的省份主要来自中西部地区,东部地区的省份增长较慢。东中西地区的旅游业全要素生产率增长存在差异性,西部增长最快,东部最慢,三大区域旅游业全要素生产率的增长主要得益于技术进步,西部技术进步水平仍快于中东部地区。全国旅游业全要素生产率年均增长7.6449%,技术进步起了主要作用,技术进步年均增长6.9933%,而技术效率增长仅为0.609%,其影响较小。 This paper estimated the Chinese provincial, three regional and national tourism TFP index, and further decomposed into technical progress index and technical efficiency index, using the Malmquist index and the stochastic frontier production function model from 1997 to 2009. The following conclusions were:During the sample period, the provincial tourism TFP showed a growing trend, faster growing provinces were mainly from central and western regions, while the slower growing provinces were mainly in the eastern regions. Three regional tourism total factor productivity growth had differences, the fastest was the west, the east was the slowest, three regional tourism TFP growth was mainly due to technological progress, the western technological progress level was still faster than the central and eastern regions. National tourism TFP was 7. 6449 % annual growth rate, technological progress played a major role, which was 6. 9933 % annual growth rate, while technical efficiency growth rate was only 0. 609 %, which had less affected.
作者 张丽峰
出处 《资源开发与市场》 CAS CSSCI 2014年第2期221-224,共4页 Resource Development & Market
基金 国家自然科学基金项目(编号:71373023)
关键词 全要素生产率 MALMQUIST指数 随机前沿函数 旅游业 total factor productivity Malmquist index stochastic frontier analysis tourism industry
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  • 1朱承亮,岳宏志,师萍.环境约束下的中国经济增长效率研究[J].数量经济技术经济研究,2011,28(5):3-20. 被引量:98
  • 2Malmquist S. Index Numbers and Indifference Curves[J].Trabajos de Estatistica,1953,(4):209-242.
  • 3Caves D W,Christensen L R,Diewert W E. The Economic Theory of Index Numbers and the Measurement of Input and Output,and Productivity[J].{H}ECONOMETRICA,1982,(6):1393-1414.
  • 4Aigner D J,Lovell C A K,Schmidt P. Formulation and Estimation of Stochastic Frontier Produc-tion Function Models[J].{H}Journal of Econometrics,1977,(1):21-37.
  • 5Meeusen W,Van den Broeck J. Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error[J].{H}International Economic Review,1977,(2):435-444.
  • 6Battese E,Coelli T. Frontier Production Functions,Technical Efficiency and Panel Data:With Application to Paddy Farmers in India[J].{H}JOURNAL OF PRODUCTIVITY ANALYSIS,1992,(1/2):153-169.
  • 7Hailu A,Veeman T S. Environmentally Sensitive Productivity Analysis of the Canadian Pulp and PaperIndustry,1959-1994:An Input Distance Function Approach[J].{H}Journal of Environmental Economics and Management,2000,(3):251-274.
  • 8Karagiannis G,Midmore P,Tzouvelekas V. Parametric Decomposition of Output Growth Using aStochastic Input Distance Function[J].{H}JOURNAL OF AGRICULTURAL ECONOMICS,2004,(4):1044-1057.
  • 9张丽峰.碳排放约束下中国全要素生产率测算与分解研究——基于随机前沿分析(SFA)方法[J].干旱区资源与环境,2013,27(12):20-24. 被引量:15
  • 10Coelli T J,Perelman S. Technical Efficiency of European Railways:A Distance Function Approach[J].{H}Applied Economics,2000,(5):1967-1976.

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