【作者】 李昕；

【导师】 孙焱林；

【作者基本信息】 华中科技大学 ， 数量经济学， 2015， 硕士

【摘要】 中国经济进入新常态,通过技术进步提升劳动生产率以保持经济稳定增长的必要性越来越高,但技术进步带来的收入不平等现象同样不容忽视。收入不平等会导致社会分化、贫富阶层对立和资源配置失衡等后果,是不少社会、经济、甚至政治问题的根本原因。研究技术进步对收入不平等的影响机制,有助于更科学有效地处理经济发展的过程中遇到的公平和效率的问题,有助于保持社会经济的稳定和活力。收入不平等的问题一直是学者们研究的热点,现有文献大多利用技能溢价衡量收入不平等,只有很少的文献研究了基尼系数与技术进步和创新之间的关系,但只限于回归分析,为能提出理论模型。本文利用基尼系数衡量收入不平等,在现有研究的基础上从理论上探究了技术进步对收入不平等的影响,推导了技术进步和基尼系数的关系式,利用2005至2012年中国安徽、重庆、福建、湖北等19个省的城镇相关数据,建立了时间固定效应面板回归模型。运用R软件(版本3.1.1)回归发现技术进步会提高基尼系数,其他影响基尼系数的指标有:失业率,与基尼系数呈正相关;城镇人口密度,与基尼系数呈负相关;人均GDP,与基尼系数呈正相关,但显著性水平不高,需要更深入研究。本文提出了深化收入分配制度改革,加大人力资本投资,积极推进城市化进程的政策建议。更多还原

【Abstract】 China’s economy has entered a new normal stage, technical change plays a more and more important role in raising labor productivity and maintaining stable economic growth rate, income inequality caused by technical change can`t be ignored. Income inequality will lead to consequences like social stratification, rich and poor classes opposition and resource misallocation, inequality is the source of many social, economic, political problems. Research on the mechanism of how technical change affect income inequality will help us tackle the dilemma of justice and efficiency caused by economic development, and keep a stable and active economy.Income inequality has always been a research hotspot, existing literatures usually measure income inequality by skill premium, few have considered the relationship between Gini index and technical change, and they`ve all concentrated on empirical analysis, failed to provide a theoretical framework. This paper analyzed the relationship between technical change and income inequality on the basis of Gini index, established a framework of technical change and Gini index based on skill-biased technical change. With a time-fixed effect panel regression model using 2005 to 2012 urban data of 19 Chinese provinces, the empirical analysis result indicates that technological progress leads to income inequality, unemployment rate and GDP per capita are positively related to Gini coefficient, population dense are negatively related to Gini index.更多还原