基于劳动效率的中国全要素生产率的再测量  

Re-estimation of China's Total Factor Productivity Based on Labor Efficiency of Province and Industry

作　　者：王芳[1] 李健[2] 

机构地区：[1]北京理工大学管理与经济学院,北京100081 [2]北京理工大学人文学院,北京100081

出　　处：《现代财经（天津财经大学学报）》2015年第12期74-87,共14页Modern Finance and Economics：Journal of Tianjin University of Finance and Economics

基　　金：教育部人文社科基金(10YJC790402)

摘　　要：准确地度量变量和正确地选择模型是有效测量全要素生产率的关键。采用修正的RD—Malmquist指数分解模型,并将劳动效率加入劳动投入变量中,分省份和行业两层面重新估算中国全要素生产率。研究发现:1993-2012年中国全要素生产率呈正增长态势,主要得益于技术的快速进步,但自2005年起技术效率的潜力得到挖掘,成为中国全要素生产率增长又一驱动要素;仅以就业人数度量劳动投入变量将拉低技术进步和技术效率的增长速度,这可能是现有研究认为中国全要素生产率下降并出现负增长的原因;工业行业的全要素生产率增长速度高于全国平均水平2.8个百分点,说明工业行业的快速发展为中国经济的增长做出了重要贡献,然而电子电器等高新技术产业的全要素生产率增长缓慢。Accurate measure of variables and choosing a right model are key factors of having a correct measurement of Total Factor Productivity （TFP）. The current paper adapt a revised version of RD-Malmquist index model and incorporated the influence of labor efficiency measured by labor capital on labor input to re-estimate TFP of China based on provinces and industries. Our research found the following three results： first, TFP of China was increasing from 1993 to 2012, which was caused mainly by technical advance, but since 2005 technical efficiency has become another driving force＇ Second, the increasing rate of technical advance and technical efficiency would be underestimated if we use only the number of employment to measure labor input, which might be the cause of the decreasing in TFP of China reported in literatures, and at the same time; Third, the increasing rate of TFP of industries was 2.8 % higher than the national average, which showed that technical advances in industries has a great contribution to the grows of our economies.

关 键 词：MALMQUIST指数 全要素生产率变化 技术效率 技术进步率 劳动效率 平均受教育水平 

分 类 号：F062.6[经济管理—政治经济学]