我国经济增长因素的实证分析——基于索洛模型

根据我国1994～2008年的相关数据,对我国国内生产总值Y、固定资本投资K、从业人员数量L时间序列数据运用计量经济方法建立计量模型,利用索洛经济增长理论实证研究了资本、劳动力投入和技术进步对我国经济增长的影响,说明资金投入在我国经济增长中占据主导地位,劳动投入和技术进步的作用相对较小。     

我国经济增长因素的实证分析——基于索洛模型

根据我国1994~2008年的相关数据,对我国国内生产总值Y、固定资本投资K、从业人员数量L时间序列数据运用计量经济方法建立计量模型,利用索洛经济增长理论实证研究了资本、劳动力投入和技术进步对我国经济增长的影响,说明资金投入在我国经济增长中占据主导地位,劳动投入和技术进步的作用相对较小。     

我国各要素对经济增长贡献率的实证研究

文章采用1978～2007年的数据,用索洛余值法分析各要素对经济增长的影响情况,将我国的经济增长分解为资本投入的贡献,劳动力投入的贡献,全要素生产率的贡献。实证表明:我国总产出中资本投入的贡献最大,年均达到57%;全要素生产率的贡献较大,对总产出的贡献达到28%;劳动力投入的贡献最小,只有15%左右。     

从索洛增长模型看金融危机如何影响实体经济

金融危机如何影响实体经济,一般有以下几个主要观点：一是金融危机重创金融行业;二是金融危机导致需求下降;三是金融危机抑制投资意愿。以上第二点和第三点归纳概括为金融危机将导致消费和投资的下降,而第一点金融业基本功能的弱化最终结果实质也表现为投资的下降。消费和投资的下降如何影响实体经济增长,可以从索洛增长模型中得到直观的结果。     

自然资源约束下经济增长的动力机制——基于索洛模型的分析

自然资源是经济增长的重要因素,但经济增长理论却没有充分重视自然资源的影响作用.我国目前对自然资源的消耗日益增加,近年来出现的资源短缺问题,引起我们对资源问题的极大关注.本文借鉴索洛模型进行自然资源对经济增长影响的研究分析,具有积极的理论和现实意义.     

1991-2010年宜宾市经济增长因素的实证分析

根据C-D生产函数及索洛余值法,以第三产业劳动力人数占总就业人口的比重的一定指数作为技术水平改变量的替代变量,在作者以前研究基础上估算了1990—2010年宜宾市资本存量,并结合相关统计数据,估算出宜宾市1991—2010年间的总量生产函数及各要素贡献率。分析结论为宜宾市经济增长模式还处于严重的资本驱动型,最后提出了相关建议。     

江苏省全要素生产率与经济增长研究

采用全要素生产率的分析方法对江苏省经济增长源泉进行了定量分析,探讨了资本、劳动力和广义的技术进步对江苏经济增长的贡献,发现全要素生产率对江苏经济增长起着重要作用,江苏经济增长属于资本和技术双推动型。     

中国西部地区经济增长源泉——基于人力资本与能源消费的双重约束

文章以中国经济发展相对落后的西部地区为研究对象,运用DEA方法将考虑人力资本与能源消费的经济增长分解为人力资本、复合物质资本、效率改善和技术进步四部分,探寻其经济增长的源泉,并对西部大开发前后进行了比较研究。发现以人力资本、物质资本和能源消费为代表的要素投入和以技术进步、效率提高为代表的全要素生产率对经济增长的推动作用几乎相等;但在西部大开发以后,以技术进步、效率提高为代表的全要素生产率对经济增长的推动作用呈现逐年上升的良好趋势。采用绝对收敛方程考察了中国西部地区经济增长与四类因素的收敛效应,发现中国西部地区出现了显著地经济收敛,而这种结果是技术效率、技术进步和物质资本积累的共同结果。采用Tobit模型深入分析了能源投入和人力资本对经济增长约束的传导机制,结果表明,中国西部地区经济增长可持续发展的重要源泉和动力在于转变经济增长方式。     

全要素生产率对上海市经济增长贡献的实证研究

全要素生产率是衡量一个经济体效率的重要指标,文章运用索洛残差法估算出上海市1979-2011年的全要素生产率,并对上海市全要素生产率增长和经济增长源泉进行定量分析。分析发现1992-2011年间全要素生产率年均增长率为6.06%,对经济增长的平均贡献率达到50.56%;说明全要素生产率对上海经济增长发挥着日益重要的作用。     

我国经济增长的源动力:“三驾马车”对我国经济增长拉动作用的实证研究

改革开放以来,我国持续、高速的经济增长令世人瞩目。本文依据西方经济学各种经济增长理论,建立了扩展的索洛模型,对影响我国经济增长的主要因素:消费、投资、出口———即"三驾马车"在我国经济增长中的作用进行了实证分析,结果显示消费、投资、出口是推动我国经济又好又快持续高速增长的源动力。针对实证结果,本文提出了相应的对策与建议。     

The Solow model in the empirics of growth and trade

Translated to a cross-country context, the Solow model (Solow,1956) predicts that international differences in steady-stateoutput per person are due to international differences in technologyfor a constant capital–output ratio. However, most ofthe empirical growth literature that refers to the Solow modelhas employed a specification where steady-stateifferences inoutput per person are due to international differences in thecapital–output ratio for a constant level of technology.My empirical results show that the former specification cansummarize the data quite well by using a measure of institutionaltechnology and treating the capital–output ratio as partof the regression constant. This reinterpretation of the cross-countrySolow model provides an implication for empirical studies ofinternational trade. Harrod-neutral technology differences,as presumed by the Solow model, can explain why countries havedifferent factor intensities and may end up in different conesof specialization.     

Solow vs. Solow: Notes on Identification and Interpretation in the Empirics of Growth and Development

Most empirical studies of long-run growth refer to one of the two seminal contributions by Robert Solow in 1956 and 1957. His work shows that in order to estimate the relative roles of factor accumulation and technology in development, an a priori identification assumption is needed about the nature of technical change. This specific assumption differs across the two Solow papers. I show that starting with the identification assumption made by Solow in 1956, one should expect to find that differences in technology rather than differences in factor accumulation explain most if not all of the observed long-run differences in output per worker. The opposite interpretation appears to prevail in parts of the recent literature on the empirics of growth. JEL no. O4     

Human capital and economic growth in Spain, 1850–2000

We investigate human capital accumulation in Spain using income- and education-based alternative approaches. We, then, assess human capital impact on labor productivity growth and discuss the implications of its alternative measures for TFP growth. Trends in human capital are similar with either measure but the skill-premium approach fits better Spanish historical experience. As education is a high income elastic good, human capital growth computed with the education-based approach seems upward biased for the recent past. Human capital provided a positive albeit small contribution to labor productivity growth facilitating technological innovation.     

新疆建筑业发展与经济增长关系的实证研究

本文运用格兰杰因果关系检验、协整检验以及误差修正模型,对新疆建筑业与经济增长的关系进行研究和分析。结果表明,新疆建筑业与经济增长之间存在长期均衡和短期波动的关系,经济增长长期拉动建筑业的增长,且经济增长对建筑业的长期影响比其短期影响大。     

Human capital quality and the regional economic growth: Evidence from China

China's economic development has advanced from a high-speed to a high-quality growth stage in recent years. The optimization and upgrading of the economic structure require high-quality human capital to support an innovation-driven economy. In this paper, a general equilibrium model of human capital (Xiang & Yeaple, 2018) is applied to estimate the cognitive and non-cognitive productivities based on Chinese provincial-level macro-data and individual labor's micro-data from 2008 to 2017. The weighted power mean of cognitive and non-cognitive productivities helps calculate the provincial-level human capital quality index (HCQI), which provides a realistic estimate of human capital quality. We find that the improvement of the HCQI leads to convergence in economic growth in China's provinces. HCQI can help explain the differences in economic growth levels in different regions of China. Our study provides a constructive step in understanding cognitive and non-cognitive abilities and HCQI in China, which could help guide education investment policy in China and its provinces.     

THE ROLE OF HUMAN CAPITAL IN CHINA'S TOTAL FACTOR PRODUCTIVITY GROWTH: A CROSS‐PROVINCE ANALYSIS

This paper studies the role of human capital in China's provincial total factor productivity (TFP) growth over 1985–2004. The stochastic frontier approach is employed to measure the productivity growth of Chinese provinces. Human capital is measured both qualitatively and quantitatively. In particular, enrolment rates at various levels of schooling are used to represent human capital composition. After controlling for endogeneity, we find that human capital has significant and positive effects on the TFP growth of Chinese provinces. However, when education quality is incorporated, productivity growth appears to be significantly enhanced by quality improvements in primary education only. Regional impacts of human capital are found to differ at various levels of schooling. In the eastern region of China, productivity growth is significantly associated with secondary education. TFP growth in the central region is mainly promoted by primary and university education. Yet in the western region, primary education plays the most prominent role.     

The Panda that grew

China, the Panda, ranks among the world's fastest growing economies. Describing that growth, identifying and quantifying its causes, and examining international competitiveness, a growth corollary, on the assumption that China is structurally similar to a sample of 121 countries, are the purposes of this paper. The inquiry presents economic statistics, including those on convergence, by half decade from the prereform years through the Asian currency crisis. It then sketches a model that links growth to determinants that include total factor productivity (TFP). After estimating parameters it quantifies the growth contributions from the separate causes. On international competitiveness, it studies China's historical record and projects competitiveness into the near term. The paper closes with policy implications.