中国经济增长动力分解:有偏技术进步与要素投入增长

发布时间：2018-04-29 17:52

本文选题：经济增长 + 动力分解　；参考：《数量经济技术经济研究》2017年09期

【摘要】：研究目标:从有偏技术进步和要素投入增长视角分解中国经济增长动力。研究方法:基于标准化供给面系统方法对中国1978~2015年的要素增强型CES生产函数进行估计,并扩展Solow增长核算方程重构中国经济增长动力分解框架。研究发现:国内研究在技术进步偏向识别、生产函数参数设定及估计方法应用方面存在部分偏误;修正偏误后本文发现考察期内有偏技术进步对于中国经济增长的动力支持总体强于要素投入增长,且有偏技术进步和要素投入增长内部发生了明显的动力转换;中国经济增速近期下滑主要由资本增强型技术进步减缓、资本累积速度下降和人口红利消失引致。研究创新:基于多种要素替代关系、市场假设和技术进步率框架,对中国要素替代弹性、有偏技术进步进行全面再评估,通过打开技术进步率的"黑箱"进一步分解中国经济增长动力。研究价值:为有偏技术进步识别和经济增长动力分解提供可靠框架。
[Abstract]:Research objective: to decompose China's economic growth power from the perspective of biased technological progress and factor input growth. Methods: based on the standardized supply-side system method, the factor enhanced CES production function in China from 1978 to 2015 was estimated, and the Solow growth accounting equation was extended to reconstruct the dynamic decomposition framework of China's economic growth. It is found that there are some errors in the identification of technological progress bias, the parameter setting of production function and the application of estimation method in domestic research; After correcting the bias, this paper finds that the dynamic support of biased technological progress to China's economic growth is generally stronger than that of factor input growth, and there is a significant internal power conversion between biased technological progress and factor input growth. The recent slowdown in China's economic growth is mainly due to the slowdown in capital-enhanced technology, the decline in the rate of capital accumulation and the disappearance of the demographic dividend. Research and innovation: based on the multi-factor substitution relationship, market hypothesis and technological progress rate framework, a comprehensive reassessment of Chinese factor substitution elasticity and biased technological progress is carried out. By opening the "black box" of the rate of technological progress, China's economic growth momentum will be further decomposed. Research value: provides a reliable framework for biased technological progress identification and economic growth dynamics decomposition.
【作者单位】：西南大学经济管理学院;
【基金】：中央高校基本科研业务费专项资金项目“中国农业偏向型技术进步及其生产率增长效应研究”(SWU1609236)的资助
【分类号】：F124.1;F224

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