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应用随机前沿分析(SFA)和数据包络分析(DEA)两种方法,结合Malmquist指数,基于2002-2010年中国31个省份的健康面板数据,比较分析了中国健康生产效率及其变化状况。结果表明:两方法测算结果差异较大但各有特点,效率方面DEA高于SFA,在全要素生产率、前沿技术进步率和规模效率变动率方面测算值相反,并且SFA方法对前沿技术进步率的测算更符合现实;SFA对省域个体差异更敏感,能较好反映实质,而DEA能反映出现实随机波动性。考察期内中国健康生产效率总体上表现出缓慢上升的良好态势,但仍有较大的提升空间,且省域间差异较大;总体生产效率对技术前沿呈现追赶态势,其中管理因素促进了这一态势。
Using SFA (randomized frontier analysis) and data envelopment analysis (DEA), combined with Malmquist index, we compared and analyzed the health productivity and its changes in China based on the health panel data of 31 provinces in China from 2002 to 2010. The results show that the calculated results of the two methods are quite different but have their own characteristics. The efficiency of DEA is higher than that of SFA, and the measured values of total factor productivity, cutting edge technology progress rate and scale efficiency change rate are opposite. SFA is more sensitive to individual differences in the province, better reflect the essence, and DEA can reflect the real random volatility. During the study period, the overall efficiency of China’s health production showed a good trend of slow increase, but there was still much room for improvement, with large differences between provinces and regions. The overall production efficiency had catches up with the technological frontier, and management factors promoted this A situation.