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市场分割、资源错配与劳动收入份额

王宋涛1,2 温思美3 朱腾腾1

(1.汕头大学商学院)
(2.汕头大学粤台企业合作研究院)
(3.华南农业大学经济管理学院)

【摘要】要素市场分割是当前中国市场经济发展进程中的一个重要问题,其不但影响经济增长,也影响收入分配。本文通过一个基于市场分割的新古典生产模型研究得出:要素市场分割会加剧资源错配程度,在资本-劳动呈替代关系时,会降低劳动收入份额。利用1998-2007年中国工业企业数据库构建279个城市的要素市场分割指数和资源错配指数面板数据,实证研究发现:要素市场分割显著加剧中国工业企业的资源错配,并降低了劳动收入份额。即便考虑可能存在的内生性以及采用省级区域的数据,上述研究结论依然成立。本文研究意味着,通过深化体制改革,破除阻碍生产要素流动的壁垒,有利于提高劳动收入份额,完善要素收入分配。

【关键词】 要素市场分割;资源错配;劳动份额;收入分配;

【DOI】

【基金资助】 广东省哲学社会科学规划项目“市场分割对国民劳动收入份额变动的影响研究”(项目编号:GD13YLJ01); 国家自然科学基金项目“中国劳动收入份额决定的微观机制:基于转型背景和企业要素收入分配视角的理论和实证研究”(项目编号:71473089); 广东省软科学研究计划项目“粤东地区传统产业升级路径及其绩效评价研究”(项目编号:2015A070704057); 汕头大学科研启动项目“中国居民收入不平等的宏观效应研究”(项目编号:STF13011); 汕头大学文科科研基金项目“市场分割对国民劳动收入份额的影响研究”(项目编号:SR13004);

Market segmentation, resource misallocation and labor share of income

WANG Songtao1,2 WEN Simei3 ZHU Tengteng1

(1.Business School of Shantou University )
(2.Research Institute for Guangdong-Taiwan Business Cooperation of Shantou University)
(3.College of Economics & Management, South China Agricultural University)

【Abstract】Factor market segmentation is an important problem in current economic development of Chinese market that not only affects economic growth, but also income distribution. In this paper, we establish a neoclassical production model based on market segmentation and conclude that the factor market segmentation will aggravate resource misallocation, and when the capital-labor relationship is substitutive, it will reduce labor share of income. Using Chinese industrial enterprises databases(1998–2007) to build the panel data of factor market segmentation indexes and resource misallocation indexes of 279 cities and through empirical study, we find that factor market segmentation significantly exacerbates resource misallocation of Chinese industrial enterprises and reduces the labor share of income.

【Keywords】 factor market segmentation; resource misallocation ; labor share of income; income distribution;

【DOI】

【Funds】 Philosophy and Social Sciences Planning Project of Guangdong Province (GD13YLJ01); National Natural Science Foundation of China (71473089); Project of Soft Science Research Project of Guangdong Province (2015A070704057); Scientific Research Project of Shantou University (STF13011); Art and Human Sciences Research Fund Project of Shantou University (SR13004);

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    Footnote

    [1]. (1) he meaning of segmentation, in this article, is not totally in a physical sense; instead, wherever there is market fraction or flow cost can be called market segmentation. [^Back]

    [2]. (1) This is an ideal situation, that is, it is assumed that there are no other factors influencing price changes. [^Back]

    [3]. (2) Factor market segmentation is only one factor that causes resource misallocation; in real life, total factor productivity in different regions is different, which will also cause different capital stock per capita. The model in this article assumes that each region’s total factor productivity is the same, but in the empirical analysis, we regard the real return on capital as the control variable, which helps to control differences in total factor productivity to some extent. [^Back]

    [4]. (3) As return on capital is higher in regions with low capital stock per capita, the order of regions should be inversed when calculating return on capital Gini coefficient (Lorenz curve). [^Back]

    [5]. (1) As the sample size is quite large across the cities, the Gini coefficient calculated by Lorenz curve fitting (then calculating integration or parameter) is nearly the same with the Gini coefficient calculated by the discrete method; since the calculation volume of 2,780 samples is relatively big, in real practices, the discrete method is used uniformly for programming calculation. [^Back]

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This Article

ISSN:1005-3425

CN: 42-1348/F

Vol , No. 01, Pages 13-25+79

January 2016

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Article Outline

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Abstract

  • 1 Introduction and literature review
  • 2 Theoretical analysis
  • 3 Econometric specification and data description
  • 4 Empirical results
  • 5 Conclusion and implication
  • Appendix:
  • Footnote

    References