【作者】 张奇勇；

【导师】 熊广星；

【作者基本信息】 广西师范大学 ， 教育经济与管理， 2003， 硕士

【摘要】 20世纪80年代以来，随着世界经济的结构性变化，教育经济学研究开始在更广泛的领域内取得新的进展。如下观点已经或应该成为大家的共识：教育和经济增长之间存在密切的正相关关系；应合理测算教育对经济增长的贡献以确定教育的投资比例；教育政策和教育投资必须适应新的国际分工的要求。本论文采用计量研究的方法说明了教育对我国经济增长的影响，充分证实了教育较固定资本投资对经济增长具有更大的贡献作用。由于内生经济增长模型研究过于微观化及采集数据存在很大的难度，文中采用的经济增长模型总体上依然是外生经济增长模型，不过对每一种外生经济增长模型都有一定的改进，使得计算过程更加合理，结论更加令人信服。具体计算方法叙述如下。马克思主义认为复杂的劳动等于多倍的简单劳动，但是如何将复杂的劳动倍加成简单的劳动却是新古典经济增长模型计量教育对经济增长贡献的瓶颈问题。以往涉及到对劳动的同质化处理时方法单一，不能充分地反映事物本质，如工资简化法、教育年限法、总课时数法等等，会造成有的方法高估劳动简化率，有的方法低估劳动简化率，得不到比较客观的结论。本论文第二章第一节介绍了前苏联和我国一些学者劳动简化的研究成果，同时提出了劳动的利率简化法。为了扬长避短，综合各种简化分析方法，第二章第二节采用了灰色关联度分析对这些劳动简化法进行了综合。一般地，我们把信息完全明确的系统称为白色系统，信息完全不明确的系统称为黑色系统，信息模糊的系统称为灰色系统，劳动简化分析就属于灰色系统分析。灰色关联度分析是较常用的一种综合评价模型，具有客观、公正的特点，可以有效地综合来自各单一评价模型所带来的信息。在第三章第一节中，对丹尼森的“因素分析法”作了一定的改进。丹尼森根据不同教育年限的劳动者的年收入指数来确定劳动简化系数，而本论文采用劳动简化系数的灰色关联度分析的结果。在劳动产出弹性系数β的确定上，本论文采用的是历年来回归统计分析的结果。把β看作是因变量为国内生产总值年增长率，在产出量的回归方程中劳动投入量年增长率的回归系数，或许更具有科学性。丹尼森在计算教育对国民收入增长率的贡献时考虑到了知识进展的作用，其计算知识进展采用的是“余数法”，并认为知识进展中有3/5是教育的作用。而本论文将科技进展（包括知识进展在内的更为广泛的科技）作为时间的函数，放入回归方程中，得出科技的产出弹性系数，通过综合评估认为科技进展中有40%是教育的作用。在第三章第二节中，采用了多因素的教育贡献率综合评判法对教育对经济增长速度的贡献率作<WP=4>了分析，该计量模型不同于以往的任何一个新古典经济增长模型，是一个全新的研究领域，本节在计算过程中做了很多尝试性的工作。随着模糊数学的发展，这种方法可能是今后估算教育与经济增长关系的一个很有潜力的研究方向。因为教育与经济增长关系的现象本身就是一个复杂的现象，复杂的现象必然会涉及大量的模糊概念。当一个系统复杂性增大时，我们使它精确化的能力就越低。复杂性意味着因素众多，以致于人们无法全部地、认真地进行考察，也就必须借助于模糊数学的发展与应用了。在第四章第一节中，运用舒尔茨的“余值分析法”对教育对经济增长额的贡献率作了分析，其中对人力资本增量的计算方法与传统方法有些不同。由于考虑到相同的人才应该是同质的，不会因为培养费用的改变而所不同，所以本文先是计算各教育程度从业员在考察期内的增量，而后根据各教育程度生均教育总成本计算出考察期内人力资本的增量。在计算平均年教育投资收益率时，本文采用的是教育的社会收益率，而不同于舒尔茨采用教育的个人收益率，这样更符合教育与收益关系的社会现实。在第四章第二节中，首先运用前苏联及我国的一些学者提出的公式对教育对经济增长额的贡献率作了分析，发现采用不同的劳动简化法计量公式计算教育的经济效益所得的结果是不一样的。本节充分分析了每个公式的构造原理，指出了它们的缺陷，并提出了一个改进后的计量公式。本论文在结论部分，采用相关性分析分析了我国教育与经济增长的关系。通过分析表明，人均受教育年限与人均GDP存在很大的相关性，尤其是每百万人中高校学生数与人均GDP的相关性更大。这充分证实了经济增长越来越依靠教育，尤其是高等教育。对各种计量模型的改进，以及采用改进后的计量模型计算我国教育对经济增长的贡献，构成了本论文的主体内容。教育与经济增长的关系一直是西方经济学研究的一个热点，它是指导政府投资行为和教育行为的依据，对于揭露知识经济的发展规律具有重要的作用。因此，撰写本论文的意义也就不言而喻了。本论文计算教育对经济增长的贡献均选用1980—2001年间的统计数据，所有的统计数据均已公开发表，所有经济类数据均按1978年可比价计算。统计采用SPSS软件完成。更多还原

【Abstract】 With the structure changes of the world economy since the 1980’s, research on educational economics has begun to make new progress in wider fields. The following viewpoints have already been or should be universally accepted by everyone: there exists a close positive relationship between education and economic growth; we should properly reckon the contributions of education to economic growth in order to plan investment proportion of education; educational policies and investment must meet the need of the new international division of labor.In this paper, I adopt calculating methods to account for the influence of education on economic growth in our country and fully prove that investment on education is more efficient than investment on fixed capital in accelerating economic growth. Since the studies of endogenous growth models are more microcosmic than those of exogenous growth models, and it exists multitudes of difficulties to obtain sample data. This paper adopts exogenous growth models to calculate economic growth. However, this paper innovates every neoclassic growth model, therefore calculating process is more reasonable, and conclusion more convincible. The concrete calculating methods are as follows.Marxism claims that the complex labor is equal to multi-times of the simple labor, but it is a crucial problem to transform the complex labor into multi-times of the simple labor when neoclassical economics of education studies the contributions of education to economic growth. In the past, it was so simple and far from truth that transforming the complex labor into multi-times of the simple labor, such as simplification approach of salary, simplification approach of education in fixed number of year, simplification approach of total school hours, etc. So it is inevitable to overestimate or underestimate the rate of simplified labor if we only adopt one simplification approach. In Section 1, Chapter 2, I present different calculating<WP=6>method of simplified labor studied by the former Soviet and Chinese scholars and bring forward simplification approach of interest rate. At the end of the Chapter 2, I adopt correlation analysis of gray system to synthesize coefficients of simplified labor. Usually, we call system with clear information as the white system, system with entirely ambiguous information as the black system and system with half ambiguous information as the gray system. Correlation analysis of coefficients of simplified labor belongs to the gray system analysis. The gray system analysis is a synthesized evaluating model, which is characterized by objectivity and impartiality. This model can synthesize all information from every single simplification approach.In Section 1, Chapter 3, I improve Edward F. Denison’s "element analysis approach of economic growth". Denison calculated coefficients of simplified labor according to annual earning per worker who has different educational level. By contrast, this paper adopts the results of correlation analysis of gray system.In terms of calculating coefficient of output elasticity of labor, which is called as ?, this paper uses regressive results that are obtained by statistical analysis of figures from past years. It maybe more reasonable that ? is regarded as regressive coefficient of annual labor investment rate, which is considered as independent variable in the equation with GDP growth rate as dependent variable. When Denison calculated the contributions of education to NI growth, he considered knowledge improvement, and he adopted the method of residual value analysis to analyse the function of knowledge improvement which affects economic growth. He reckoned that education accounts for three fifths of knowledge improvement. But this paper takes technological improvement-a more comprehensive concept of technology including knowledge improvement-as a function of time t and puts it into regressive equation, so I get the output elasticity coefficient, λ by name. Through synthesized appraisement, I estimate that 40 percent of technologica更多还原