期刊文献+

用“已知”倒推“未知”:中国全要素生产率研究展望 被引量:14

Revealing the Unknown with the Known:Implications for Total Factor ProductivityResearches in China
原文传递
导出
摘要 本文简要回顾和评述了国内外关于'全要素生产率'方面的研究,对照中国研究进展,本文指出,尽管从方法论和可行性操作层面上进一步完善,对中国全要素生产率的估算有极其重要的学术和政策指导价值,但考察中国全要素生产率的影响因素,分析其波动的内在影响机制,也将为深入理解中国过去的'经济增长'的源泉,并寻求未来的增长引擎提供重要借鉴。本文发现,经验研究中的'全要素生产率'远比所谓的'技术进步'要复杂,它既包括通常意义上的'技术进步'所带来的社会整体生产力的提高,也包括社会经济运行环境变迁、要素更为有效使用以及资源重新配置导致的潜在生产力的进一步释放,更包括数据方面的'测量性误差'波动的影响。此外,囿于中国现有数据基础,基于垂直分解的统计分析思想来分析中国全要素生产率变化的影响因素孰轻孰重,可以成为相关研究的次优之选。 This paper briefly reviews researches related to total factor productivity(TFP)and mainly focuses on those related to China.It indicates that although perfecting exercises on estimating China’s TFP both from methodological and applicable aspects are important for academic studies and policy implications,to further reveal its internal influences will also be valuable for understanding China’s economic miracle in the past and provide hints for future growth.This paper also finds that the"total factor productivity"in empirical studies is far more complex than the so-called"technological progress",which includes not only the productivity growth caused by the usual technological progress,and also further release of potential productivity due to changes in socio-economic environment,more effective usage and\or reallocation of resources.In addition,changes in data measurement error will also be reflected in estimated TFP fluctuations.Finally,this paper argues that,with restrictions to availability of detailed data,the orthogonal decomposing approach would be a suboptimal choice to account which influences would contribute more to changes in China’s TFP.
作者 白重恩 张琼 BAI Chong-en;ZHANG Qiong(School of Economics and Management,Tsinghua University;School of Economics,Central University of Finance and Economics)
出处 《新金融评论》 2014年第1期135-151,共17页 New Finance Review
关键词 全要素生产率 影响因素 数据 垂直分解 Total Factor Productivity Influence Data Orthogonal Decomposition
  • 相关文献

同被引文献200

引证文献14

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部