Abstract: Total factor productivity is an important indicator to measure the economic growth of cotton, and green total factor productivity determines the sustainable development of cotton industry. Based on the inputoutput data of cotton in 12 major cotton producing provinces in China, the Malmquist index of green total factor productivity of cotton was calculated and decomposed. The Tobit model was used to estimate the effects of core variables of cotton target price policy and regional economic development level, cotton income per hectare, cotton industry aggregation degree and regional environmental investment on green total factor productivity of cotton. The research shows that Chinas green total factor productivity of cotton is 1.02, the highest green total factor productivity in Anhui is 1.92, and the lowest green total factor productivity in Hunan is 0.91. Target price policy has no significant indigenous effect on cotton green total factor productivity, while regional economic development level, cotton earnings per hectare, cotton industrial agglomeration degree and regional environmental investment intensity have significant indigenous positive effects on cotton green total factor productivity.

Key words: cotton, green total factor productivity, target price, inputoutput data, MalmquistTobit model

摘要： 全要素生产率是衡量棉花经济增长的重要指标，而绿色全要素生产率则决定棉花产业的可持续发展。运用中国12个棉花主产省的棉花投入产出数据，测算棉花绿色全要素生产率的Malmquist指数并对其进行分解，采用Tobit模型估计棉花目标价格政策核心变量及区域经济发展水平、棉花每公顷收益、棉花产业聚集程度和区域环境投资力度等控制变量对棉花绿色全要素生产率的影响。研究表明：我国棉花绿色全要素生产率为1.02，安徽地区绿色全要素生产率最高为1.92，湖南地区棉花全要素生产率最低为0.91。目标价格政策对棉花绿色全要素生产率无显著影响，而区域经济发展水平、棉花每公顷收益、棉花产业聚集程度和区域环境投资力度则对棉花绿色全要素生产率有显著正向影响。

关键词: 棉花, 绿色全要素生产率, 目标价格, 投入产出数据, MalmquistTobit模型