摘要
贫困,一个既古老又现实的问题,贯穿着人类社会发展的始终。它具有自我强加的持续性,类似于一个陷阱,使得处于该陷阱中的人们长期处于一种低水平的均衡状态。打破低水平均衡、跳出陷阱、终结贫困一直是人类的一个梦想,有无数的学者对这个问题进行了深入的探讨和研究。本论文旨在前人研究基础上进一步探讨贫困陷阱形成机制以及由此带来的家户福利变动问题,具体研究了技术引致的人力资本升级和风险冲击下的人力资本传递如何影响国家在技术选择、人力资本积累以及家户在子女教育获取、人力资本传递方面的决策,进而讨论了这些决策反过来将如何影响国别发展差异以及家户福利及脆弱性,最后对家户脆弱性的特征和贡献因素进行了分析,并尝试探讨了异质性个体对经济政策实施有效性的影响。
在第三章中,本文尝试通过一个宏观经济模型考察技术引致、人力资本升级与发展陷阱之间的关系。文章认为技术水平的高低是通过技术的掌握者和使用者在发挥作用,因此技术水平对人力资本积累具有引致性。模型假设发展中国家的人力资本水平是随着所选择的更新技术水平在进行升级,从而技术的分阶段更迭使得引致的人力资本分阶段累积。据此定义了一类非平滑的、周期性的生产函数,在每个阶段内人力资本是教育投入的凹函数,各阶段内的技术水平是该阶段人力资本水平所能达到的上限,通过R&D的投入实现技术的更新,最终人力资本转型升级推动经济持续增长。模型根据两种差异化的人力资本升级形式得出了两种不同的经济增长方式：持续式增长模式和颤抖式增长模式,以此可以解释发展中国家中存在的低水平均衡陷阱。我们通过数值模拟考虑了“循序渐进”式的技术引致和“跨越”式的技术引致这两种极端的技术引致方式引起的人力资本升级的情形并验证了模型中的主要命题。本章的结论是,发展中国家一味的学习和模仿领先国家的高新技术可能无法成为赶超后者的途径,因为前者的人力资本水平和潜在技术水平差距太大将使得发生转型升级的人力资本临界值过高,从而使其陷入低水平均衡状态。发展中国家要赶上经济发达国家,可以采取提高人力资本积累率、选择更为适宜的技术水平引致这两种途径实现人力资本的升级,从而摆脱发展陷阱。
在第四章中,本文试图通过一个微观经济模型考察风险、人力资本代际传递和贫困陷阱之间的关系并解释贫困家庭的孩子为什么不读书的问题。文章发现,人力资本积累对于改善家庭持续性贫困是如此重要,但是数据表明相比于高收入家庭,低收入家庭无法选择或者并不愿意让自己的子女继续接受教育。本章基于Galor和Zeira(1993)构建了一个教育投资决策的微观模型,从教育投资风险阻碍人力资本代际传递的角度解释了低收入家户持续性贫困的问题。模型分析得到了人力资本投资的成本、预期收益和风险、机会成本和风险水平之间的三条关系假说,我们利用中国健康与营养调查(CHNS)八个年度的数据通过非平衡面板的离散选择模型和分位数回归分析对影响个体接受教育进行人力资本投资意愿的因素进行了实证检验,结论如下：第一,分样本处理和Chow式检验的结果表明,在低收入家户中,个体进行人力资本投资的意愿与其收入水平正相关,这意味着越是贫穷的家户进行人力资本投资的意愿会越低；在高收入家户中,个体进行人力资本投资的意愿与其收入水平负相关,但关系较弱。同样,关键变量的虚拟变量模型和二次型回归的结果也印证了上述结论。第二,与通常的直观认识相悖,人力资本投资意愿与地区的经济发展水平之间并没有表现出显著的统计关系。在地区特征上,农村和城市之间并未表现出显著的差异；在省份的差异上,各省之间个体的人力资本投资意愿并未有明显的差异。本章的实证分析结果也从侧面说明了经济强省未必就是教育大省,学校匮乏、师源缺少地区的个体未必不愿意接受教育。第三,通过分位数回归分析发现,个体收入对于个体接受高中教育的分位数回归系数呈现先降后升的趋势,这说明了对于决定接受或不接受人力资本投资意愿特别强烈的个体,个体收入的变动对他们原来意愿的改变有很强的影响；处于中间意愿的个体,人力资本投资的预期收益和机会成本对其意愿改变的影响更大。
在第五章中,我们重点关注了家户脆弱性导致贫困陷阱的问题。脆弱性衡量了家户或个体在冲击后复原的能力,在遭受冲击后有的家户能够尽快复原,而有的家户却永久性致贫,因而陷入了贫困陷阱。本文基于VEP法提出了一种反向的脆弱性测度方法,用个人或家户在将来维持于某一返贫概率之上的最小福利水平来描述家户脆弱性。基于CHNS中2000、2004和2006共三年的调查数据为样本,以2009年的家户数据作为检验样本,本章分别计算了在水平为0.1、0.3、0.5、0.7和0.9基础上的家户脆弱性值,并根据不同时期、户主性别、所处地区和户主职业类型等分类考察了家户脆弱性的特征,我们主要发现：第一,家户的收入和其脆弱性之间的正向关系比较显著,但随着家户的收入水平上升,这些较高收入家户的脆弱性差异很大。这表明,贫穷的家户总是很脆弱,高收入家户有时也是脆弱的。第二,不同时间段和地区间的家户脆弱性程度有所区别。从时间趋势上来看,全国家户的整体脆弱性水平随着时间的推进都在改善,东部地区的家户脆弱性水平要好于中部和西部地区的家户,城市地区的家户的脆弱性水平要远好于农村地区的家户。第三,不同户主特征的家户的脆弱程度也有所差异。男性户主家庭的脆弱性水平略优于女性户主家庭,家中拥有老人和子女越多的家户会越脆弱,拥有青壮年越多的家户的脆弱性会改善。第四,户主职业类型对家户脆弱性程度影响不同。从事农业类的家户最弱、从事技术工人类的家户脆弱性水平居中,高级技术人员家户的脆弱性最强。为了考察不同因素对家户脆弱性差距及变动的定量影响,本文主要分析了家户脆弱性的变动和家户脆弱性的差距这两类分解问题。对于前者,我们选取了在2004年和2006年这两个时段间脆弱性发生恶化的家户为样本,通过分解成均值变动和方差变动进行分析发现,导致家户脆弱性发生恶化的原因既有均值或方差的单向变动,但是绝大多数是由两者同等幅度的变动导致的。对于后者,我们根据上、下1/3分位数线为标准选取脆弱性强弱不同的两组家户为样本,通过使用Oaxaca分解、Shapley分解和Fields分解法将两组变量之间的差异分解为各种不同要素对于造成家户脆弱性差异的贡献度。从分解结果中可以看出,家户压力方面的信息,即家户规模、家户支出和家庭负担导致了家户脆弱性的差距,其中家户支出是强弱脆弱性差距最重要的贡献因素,其Shapley分解贡献程度达到了73.10%!
在第六章中,本文试图通过货币模型中时间偏好和经济稳定性的分析重点考察异质性、非理性的个体对于宏观经济政策实施可能产生的影响。既有的实证结果表明个体的时间偏好和个人的收入水平密切相关,统计数据也表明富人更有耐心。贫困主体的“习惯形成”与“追赶效应”会使传统的“平滑消费理论”失效,因此异质性个体的行为可能会使政策实施的效果大打折扣。本文放松了传统的经济理论假设“经济人”是完全理性的,具有完备记忆、稳定的偏好的假设,并假定个体的时间偏好依赖于整个经济的收入、平均消费和货币量,运用动态法在一个货币管理机构采取利率反馈规则的货币模型中研究了具有社会属性的时间偏好是如何影响经济长期均衡处的稳定性的。结论是异质的时间偏好对于货币政策的实现效果起着重要作用,因而在制定经济政策时,弄清楚消费者的效用评价变化是有必要的,也是很重要的。
Poverty is one of the most important topics concerned in the process of development all the time. Breaking the low-level equilibrium and escaping from the poverty traps has always been a dream of humankind. Thousands of scholars paid great attention to this issue and made discussion and research related to it. Aiming to further explore the mechanism of poverty traps and the resulting changes associated with household welfare, this thesis focus on the research of human capital upgrade induced by technology and human capital transition under shock and risk, resulting with the impact of country's choice on technology selection as well as human capital accumulation and households'choice on access to their children's education as well as human capital transition. Based upon these two kinds of choice, we also try to analyze household's characteristics and factors of welfare and vulnerability resulted from the mechanism of poverty traps discussed above. Finally, we attempt to explore the impact of the heterogeneity of individuals on the effectiveness of implementation of the economic policy.
In the third chapter, we attempt to analyze the relationship among induced technology, human capital upgrade and development traps through a macroeconomic model. We consider that the technical level is demonstrated by technology users so that the human capital accumulation can be induced by technology upgrade. The model assumes that the level of human capital in developing countries is proceeding with the upgrade process of technical level, which means that the step by step human capital cumulation should be induced by step by step technology upgrade. Based upon this consideration, we define a class of non-smooth and periodic production function, where human capital is a concave function of the investment in education. Within each upgrade stage, the potential maximum level of human capital is the upper limit of technical level during that stage.Through the R&D investment and technology upgrade, sustained economic growth is driven by human capital accumulation. According two different types of human capital accumulation, we obtain two different types of economic growth, the sustained growth mode and trembling growth mode, which can explain the existence of low-level equilibrium trap in developing countries. Through numerical simulation we also consider about human capital accumulation induced by two extremes of technology upgrade, the mode of sustaining induced technology and the mode of trembling induced technology. Conclutions are that technology update by blindly learning and imitating in developing countries may not be able to help them to catch up with the leaders. Because the gap between current human capital in developing countries and potential upper limit of technology in developed countries is too huge and as a result, human capital upgrade threshold is too big to make it fall into the low-level equilibrium. In order to get rid of the traps, developing countries can take methods to improve the rate of human capital accumulation and to choose a more appropriate level of technology for human capital upgrade.
In the fourth chapter, we attempt to analyze the relationship among the risk, intergenerational human capital transition and poverty traps in a microeconomic model. Statistical results indicate that human capital accumulation is of great importance for a family to improve their persistent poverty. But in fact, compared with high-income families, low-income families are reluctant to allow their children to accept education. Based on Galor and Zeira (1993), we construct a microeconomic model to study the role of risk played in education decisions and explain the problem of persistent poverty in low-income families. Based upon the analysis of this model we get three hypotheses regarding the relationship among the cost of human capital investment, expected return and risk of human capital investment, opportunity cost and risk of human capital investment. By using eight years' survey data of the China Health and Nutrition Survey (CHNS), we empirically test the hypotheses through unbalanced panel discrete choice model and quantile regression model. The main conclusions are summarized as follows. Firstly, results from sub-sample processing and Chow-test show that the aspiration of human capital investment is positive related to their income, which means that willingness of education will be lower in the poorer family, but the willingness of human capital investment in richer family is weakly negative related to their income. Similarly, the dummy variable model and quadratic regression based upon the key variable also confirm the conclusions above. Secondly, contrary to the common sense, there're not strong statistically significant relationships between the willingness of education and the regional economic development. There're no significant differences between the rural areas and urban areas, and also no significant differences among different provinces. Thirdly, quantile regression results show an inversed-U shape relationship between willingness of high school education and household's income, which means that the changes of household's income have a strong impact on their willingness to accept or not to accept the human capital investment, especially for those with strongest or weakest willingness to accept human capital investment. For those with average willingness to accept human capital investment, the expectation of benefits and the opportunity cost from human capital investment are the main power to impact their willingness.
In the fifth chapter, we focus on the issues that household vulnerability leads to poverty traps. Mostly poverty is transient for external shock, and this kind of poverty is not easy to identify, vulnerability is a key method to measure the recover ability of households under a shock. Based on the VEP method, we propose a reverse measure to calculate vulnerability, by which the vulnerability of a household is defined as the minimum level of welfare maintaining at a given probability of returning to poverty in the future. Based on a total of three years sample from CHNS survey in2000,2004and2006, we calculate households' vulnerability at the level of0.1,0.3,0.5,0.7and0.9, and examine the characteristics of household vulnerability according to different household characters, such as the gender of the head of household, their locations and their occupations. The main results are summarized as follows. Firstly, there is a significant positive relationship between household income and their vulnerability and the vulnerability of high income household differences a lot as their income rising, which suggests that low-income households are always very vulnerable but high-income households sometimes vulnerable. Secondly, the degree of household vulnerability in different periods and regions is quite different. The overall vulnerability of the whole country are improving as time expans, the vulnerability of the household in eastern area are better than those in central and western area and the vulnerability of the households in urban area are better than those in rural area. Thirdly, the vulnerability of the household with different households'characters also varies. The vulnerability of male-headed households is slightly better than female-headed households, the households with more elders and children are more vulnerable than those with younger adults. Forthly, vulnerability of household with different occupation also varies. Households living by agriculture are the most vulnerable and the least vulnerable households are those living by senior skill. In order to investigate the impact of different factors on households vulnerability, we've also analyzed two types of factor decomposition problem, the within change and the between change. For the former, we selecte the deteriorating households in two periods of2004and2006, and then decompose their vulnerability into mean changes and variance changes. The analysis shows that the main cause for the vulnerability deteriorating is from changes both in mean and variance, and with equal magnitude. For the latter, according to a selected sample divided by the upper and lower1/3quantile line, by using the methods of Oaxaca decomposition, Shapley decomposition and Fields decomposition, results show that the burden information of a household, such as the household's size, household's expenditure and household's structure are the main factors for households'vulnerability gap. Specifically, household expenditure is most important factor contributed to the vulnerability gap and its Shapley decomposition contribution is73.10%!
In the sixth chapter, since empirical results indicate that individual income is closely related to their time preference and the rich are more patient than the poor, we consider an infinite and continuous time model, based upon the analysis of Meng(2006) to check how the impatience affects the economic stability, by postulating that individual agents'time preference depends on the economy-wide total income, average consumption and money balance, which are social factors taken as external by individual agents. Within extended neoclassical one-sector optimal growth model, our focus on the average social level is to check its effect on the macroeconomic stability, mainly using dynamic methods. We assume that labor supply is inelastic and the role that physical capital plays in stabilizing the real side of the economy by ensuring uniqueness of equilibrium in alternative environments if the monetary authority follows interest-rate feedback rules. The analysis shows that with the socially determined individual time preference, the macroeconomic stability of the long run equilibrium can arise under a set of sufficient conditions which is derived in this context.
引文
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3童星,林闽钢,我国农村贫困标准线研究,中国社会科学,1994年第3期。
15统计数据来自《中国农村监测报告2009》第9-10页。
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