制造业全要素生产率测算及影响因素研究  

A study on the total factor productivity and its influence factors of the manufacturing industry in China

作　　者：郭春娜[1,2] GUO Chunna(School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471000, P. R. China;Graduate School of Chinese Academy of Social Sciences, Beijing 102488, P. R. China)

机构地区：[1]河南科技大学数学与统计学院,河南洛阳471000 [2]中国社会科学院研究生院,北京102488

出　　处：《重庆大学学报（社会科学版）》2019年第2期49-58,共10页Journal of Chongqing University(Social Science Edition)

基　　金：国家自然科学基金项目"中国建设制造强国的行动路径研究"(71673296);河南科技大学青年基金项目"河南省投资结构优化问题研究"(2013QN027)

摘　　要：Hsieh和Klenow提出了一种测算全要素生产率与资源配置效率的模型,龚关和胡关亮对该模型进行了扩展。文章在龚关和胡关亮研究的基础上,突破了投入要素的产出弹性只与行业有关的假设,构建了一个新的异质产品的垄断竞争模型。然后结合企业的微观数据,测算了中国制造业的资本配置效率、劳动配置效率和全要素生产率。最后,根据Olley和Pakes的方法测算了制造业的技术进步水平,并从技术进步和资源配置的视角分析了中国制造业全要素生产率的影响因素。研究发现:2001—2007年制造业全要素生产率平均每年增长4. 93%;由于资本配置效率和劳动配置效率的双重下降,2007年以后全要素生产率明显下降;就全要素生产率的地区差异看,中西部地区越来越高,而东部地区越来越低。Hsieh and Klenow proposed a model to measure the efficiency of total factor productivity and resource allocation in 2009, and Gong Guan and Hu Guanliang expanded the model in 2013.This paper extends Hsieh and Klneow’s model further and constructs a new model of monopolistic competition for heterogeneous product. Based on this model, this paper studies TFPs of manufacturing industry and explores deep factors affecting the overall TFP growth from the point of the efficiency of resource allocation and technological progress with the methods of Olley and Pakes. The following conclusions are made. First, the overall TFP growth rate is 4.93% in the period from 2001 to 2007, and TFPs are relatively high in central and Western China while TFPs in eastern China are relatively low. Second, because of the declining of both the capital allocation efficiency and the labor allocation efficiency, there is a significant decrease of TFP after 2007.

关 键 词：制造业 全要素生产率 资源配置效率 技术进步 

分 类 号：F426[经济管理—产业经济]