A Dynamic Latent Model for Poverty Measurement

The main purpose of this paper is the longitudinal analysis of the poverty phenomenon. By interpreting poverty as a latent variable, we are able to resort to the statistical methodology developed for latent structure analysis. In particular, we propose to use the mixture latent Markov model which allows us to achieve two goals: (i) a time-invariant classification of households into homogenous groups, representing different levels of poverty; (ii) the dynamic analysis of the poverty phenomenon which highlights the distinction between transitory and permanent poverty situations. Furthermore, we exploit the flexibility provided by the model in order to achieve the measurement of poverty in a multidisciplinary framework, using several socio-economic indicators as covariates and identifying the main relevant factors which influence permanent and transitory poverty. The analysis of the longitudinal data of the Survey on Households Income and Wealth of the Bank of Italy provides the identification of two groups of households which are characterized by different dynamic features. Moreover, the inclusion of socio-economic covariates such as level of education, employment status, geographical area and residence size of the household head shows a direct association with permanent poverty.     

安徽省城镇贫困线的测度及贫困状况分析——基于ELES方法

贫困线度量是贫困研究的关键步骤和政府制定扶贫政策的重要依据。本文利用安徽省统计年鉴数据,采用"扩展线性支出法(ELES)",对安徽省1996-2005年的贫困线做了测度,并以此为标准与其他数据进行了比较分析。结果显示,贫困线整体上保持了一个上升的趋势,但是其中在1999、2001和2004年出现比往年低的情况;低收入群体贫困状况在恶化,现有贫困线距离扶贫的标准还很遥远。     

贫困测度指标及其评价

一、引言一般来说,研究贫困问题主要涉及三个方面:一是贫困的识别;二是贫困程度测定;三是反贫困效果判定以及相应的战略选择。贫困识别问题主要指贫困的基本范畴及贫困线的合理确定,关系到贫困集合的准确界定;贫困程度的测定主要指贫困指数的定义和计算,关系到贫困程度大小的判     

构建贫困购买力平价的两个关键点

目前，国际上出现了一种全新的测量贫困程度的方法——贫困购买力平价法。将这种新方法与原有的贫困线和贫困指数等进行对比分析，并尝试性地归纳出构建贫困PPP的两个关键点——汇总方法和数据收集。同时，汇总方法和数据收集也是构建贫困PPP的难点。     

中国居民家庭的主观贫困感受研究

主观贫困包含着大量客观贫困无法体现的信息，是客观贫困测度的一种有效补充。本文提出了一种基于半参数广义可加模型的主观贫困效应的测度方法，利用中国社会状况综合调查（CSS）的微观调研数据，对影响我国居民主观贫困感受的决定因素以及主、客观贫困间的关系进行了实证研究。首先，按照CSS数据中居民对自身经济地位的自我评价，将居民划定为主观贫困和非主观贫困两种状态；其次，为了更加灵活的捕捉连续变量的影响，利用所提方法对影响主观贫困的因素进行了计量分析，并对主、客观贫困测度间的关系进行了分析。研究发现，居民主观上的贫困感受不仅受到家庭收入水平的影响，家庭规模、人口结构、教育水平、资产积累、医疗支出、家庭遭遇困境事件、居住位置等因素均会显著改变主观贫困发生的概率。因而居民主观贫困的脱离不仅依赖于经济条件的改善，教育、医疗保障等公共服务水平的提升、居民生活环境的改善、从政策上提高贫困人口应对困境的能力都对提升居民安全感和获得感具有重要的影响。     

Poverty comparisons with common relative poverty lines

Relative poverty lines are increasingly being used in poverty comparison studies. Existing methods assume that the distributions being compared are distinct with independent relative poverty lines. However, this practice may be problematic when comparing two subgroups of a population. We follow up on a recent proposal for the usage of common relative poverty lines in such cases, and develop a test for comparing poverty between subgroups of a single population, using inequality restrictions. Monte Carlo experiments are conducted in order to examine the size and power of our proposed test. We illustrate our procedure using some U.S. household income data.     

健康在多大程度上引致贫困脆弱性——基于CHNS农村数据的经验分析

贫困脆弱性的产生,很大程度上归因于居民健康水平的下降.在阐述健康引致贫困理论机制的基础上,基于CHNS在2000-2009年间追踪调查数据,对贫困脆弱性和健康效用指数HUI进行测度,估计并分析健康对贫困脆弱性的影响与内在机制.研究发现:居民健康水平的恶化会使其面临更高的贫困脆弱性,居民健康水平每下降10％,贫困脆弱性大约会上升6％；健康影响贫困脆弱性的作用机制中,物质资本和社会资本渠道被证明是相对有效的,而人力资本渠道尽管体现出微弱效应,但尚未在统计上得到显著性验证.因此,制订前瞻性的反贫政策应着眼于建立健康风险防范机制,包括提高农村医疗保障水平和重大疾病救助力度,并增加农村公共服务的投入,以促进其均衡化发展.     

Empirical Likelihood-Based Inference for Poverty Measures with Relative Poverty Lines

In this article, we propose an empirical likelihood-based method of inference for decomposable poverty measures utilizing poverty lines which are some fraction of the median of the underlying income distribution. Specifically, we focus on making poverty comparisons between two subgroups of the population which share the same poverty line. Our proposed method is assessed using a Monte Carlo simulation and is applied to some Canadian household income data.     

A multidimensional view on poverty in the European Union by partial order theory

Poverty can be seen as a multidimensional phenomenon described by a set of indicators, the poverty components. A one-dimensional measure of poverty serving as a ranking index can be obtained by combining the component indicators via aggregation techniques. Ranking indices are thought of as supporting political decisions. This paper proposes an alternative to aggregation based on simple concepts of partial order theory and illustrates the pros and cons of this approach taking as case study a multidimensional measure of poverty comprising three components – absolute poverty, relative poverty and income – computed for the European Union regions. The analysis enables one to highlight conflicts across the components with some regions detected as controversial, with, for example, low levels of relative poverty and high levels of monetary poverty. The partial order approach enables one to point to the regions with the most severe data conflicts and to the component indicators that cause these conflicts.     

Poverty and inequality in European regions

The European Union Statistics on Income and Living Conditions (EU-SILC) is the main source of information about poverty and economic inequality in the member states of the European Union. The sample sizes of its annual national surveys are sufficient for reliable estimation at the national level but not for inferences at the sub-national level, failing to respond to a rising demand from policy-makers and local authorities. We provide a comprehensive map of median income, inequality (Gini coefficient and Lorenz curve) and poverty (poverty rates) based on the equivalised household income in the countries in which the EU-SILC is conducted. We study the distribution of income of households (pro-rated to its members), not merely its median (or mean), because we regard its dispersion and frequency of lower extremes (relative poverty) as important characteristics. The estimation for the regions with small sample sizes is improved by the small-area methods. The uncertainty of complex nonlinear statistics is assessed by bootstrap. Household-level sampling weights are taken into account in both the estimates and the associated bootstrap standard errors.     

边疆地区农村贫困程度的测度与模拟分析——以新疆维吾尔自治区为例

利用2000-2009年新疆农村收入分组数据,首先计算历年新疆农村FGT贫困指数,分析新疆农村贫困程度的变化情况;其次对新疆农村FGT贫困指数进行分解,探讨经济增长、收入分配和贫困线变动对新疆农村贫困程度的影响;最后模拟分析各个贫困指标对贫困线变动的敏感程度。研究结果表明：新千年开始后新疆农村贫困程度变化具有一定的阶段性特点,大体经历了大幅下降、平缓变动、小幅上扬三个阶段;FGT贫困指数分解后发现,各期影响因素作用不一,经济增长的减贫效应最为明显,收入分配状况的改善或者恶化产生了不一样的减贫作用,贫困线上调最明显的效应是新疆农村贫困面扩大;模拟贫困线上调后发现各贫困指标对贫困线较小幅度的变动具有较高的敏感性。新疆农村的贫困问题比较复杂,最近有进一步加重的趋势,尤其是最贫困人口的境况需要获得更多的关注,基于此提出了相关政策建议。     

我国农村贫困的动态转化、持续时间与状态依赖研究——基于收入贫困与多维贫困的双重视角

本文使用中国健康与营养调查2000—2015年跟踪数据,比较分析了农村家庭收入贫困与多维贫困的长期变动情况。在此基础上,使用Cox比例风险与动态Probit模型实证研究了跨期贫困的动态转化概率、状态依赖及其影响因素等问题。研究发现,农村多维贫困发生率下降幅度比收入贫困发生率下降幅度高出近20个百分点,但未脱贫的多维贫困家庭比收入贫困家庭具有更明显的贫困适应性。随着贫困持续时间的增加,无论是收入贫困还是多维贫困,中断当前贫困状态的可能性都下降了。进一步分析发现,子代职业地位、子代教育、城镇化水平和交通便捷度等因素显著降低了贫困家庭的贫困适应性与状态依赖,而贫困补贴对部分贫困家庭产生了补贴依赖效应,从而一定程度上促进了其贫困适应性。本研究在理论上丰富了有关贫困动态性的探讨,为有效破解低收入群体的贫困状态依赖提供了经验证据。     

农村正规金融与非正规金融的减贫效应——基于PVAR模型的经验分析

采用面板向量自回归模型(PVAR)来研究农村正规金融、非正规金融发展的减贫效应。研究发现,农村正规金融发展存在一定的当期减贫效应,但持续减贫效应不显著。具体表现为仅在缓解农村贫困人口之间收入不平等程度上发挥了积极效应,而对减少农村绝对贫困人口数量和缓解农村贫困人口的收入短缺程度上没有发挥积极效应。农村非正规金融发展不仅具有较强的当期减贫效应,而且具有长期持续的减贫效应。其降低农村绝对贫困程度的效应要大于降低农村贫困人口相对收入短缺和收入不平等程度的效应。     

贫困缺口总指数的构造、分解与应用

本文构造了一个新贫困指数 ,通过对 指数的因素分解及衍生指数的构造,提出了一些重要贫困指标的预测和推算办法。基于CHNS1991-2011年跨度20年的8轮调查数据进行实证分析,结果表明,我国农村近20年来总贫困缺口率呈现年均6.39%的缩减率,其贡献全部来自贫困人口总规模递减这一因素的影响,而另外两个因素,即平均贫困缺口水平和贫困差异度则呈现年均小幅上升趋势,表明减贫质量不容乐观;以现有减贫模式对我国农村2020年的平均贫困缺口水平、贫困不平等程度、贫困规模等指标进行预测显示,减贫目标依然任重道远;提出了采用精准减贫,重心在于提升贫困人口获取收入的能力和缩小贫困不平等程度的相关建议。     

Fuzzy measures of the incidence of relative poverty and deprivation: a multi-dimensional perspective

In this paper we present a methodology for the study of multi-dimensional aspects of poverty and deprivation. The conventional poor/non-poor dichotomy is replaced by defining poverty as a matter of degree, determined by the place of the individual in the income distribution. The fuzzy poverty measure proposed is in fact also expressible in terms of the generalised Gini measure. The same methodology facilitates the inclusion of other dimensions of deprivation into the analysis: by appropriately weighting indicators of deprivation to reflect their dispersion and correlation, we can construct measures of non-monetary deprivation in its various dimensions. These indicators illuminate the extent to which purely monetary indicators are insufficient in themselves in capturing the prevalence of deprivation. An important contribution of the paper is to identify rules for the aggregation of fuzzy sets appropriate for the study of poverty and deprivation. In particular, we define a ‘composite’ fuzzy set operator which takes into account whether the sets being aggregated are of a ‘similar’ or a ‘dissimilar’ type. These rules allow us to meaningfully combine income and the diverse non-income deprivation indices at the micro-level and construct what we have termed ‘intensive’ and ‘extensive’ indicators of deprivation. We note that mathematically the same approach can be carried over to the study of persistence of poverty and deprivation over time.     

A risk set calibration method for failure time regression by using a covariate reliability sample

Regression parameter estimation in the Cox failure time model is considered when regression variables are subject to measurement error. Assuming that repeat regression vector measurements adhere to a classical measurement model, we can consider an ordinary regression calibration approach in which the unobserved covariates are replaced by an estimate of their conditional expectation given available covariate measurements. However, since the rate of withdrawal from the risk set across the time axis, due to failure or censoring, will typically depend on covariates, we may improve the regression parameter estimator by recalibrating within each risk set. The asymptotic and small sample properties of such a risk set regression calibration estimator are studied. A simple estimator based on a least squares calibration in each risk set appears able to eliminate much of the bias that attends the ordinary regression calibration estimator under extreme measurement error circumstances. Corresponding asymptotic distribution theory is developed, small sample properties are studied using computer simulations and an illustration is provided.     

中国城乡多维贫困的测度及比较

传统的仅用收入或消费来衡量贫困的方法只能提供单一的信息,从多维角度则能够较全面地认识贫困。本文利用CHNS数据库中2000年和2009年数据,借鉴了多维贫困指数的构造及分解方法,对近十年来中国城乡多维贫困进行了测度、分解及分析,认为总体上城乡贫困程度均有所减轻,农村贫困严重于城市,应重视医疗健康保险、卫生设施、城市住房、做饭燃料等维度上的贫困,同时降低中西部省份的贫困。     

借助外部介入提升贫困家庭的脱贫决心——基于CHIP数据的实证分析

扶贫实践中发现有一些贫困家庭对脱贫没有决心,完全寄希望于政策支持和别人的帮扶,该现象成为扶贫攻坚中的一个难题。使用2013年中国家庭收入调查(CHIP)数据,集中分析了脱贫决心如何影响农村贫困家庭的行为,进而影响其收入增长。研究结果表明:缺乏脱贫决心是制约农村贫困家庭难以摆脱贫困的重要原因,解决贫困问题需要关注农村贫困家庭的脱贫决心,通过多种手段对这些贫困家庭进行心理沟通,提高贫困家庭对致贫原因及脱贫办法的认知能力,将会使他们产生脱贫信心。     

District-level poverty estimation: a proposed method

This paper develops a method of estimating micro-level poverty in cases where data are scarce. The method is applied to estimate district-level poverty using the household level Indian national sample survey data for two states, viz., West Bengal and Madhya Pradesh. The method involves estimation of state-level poverty indices from the data formed by pooling data of all the districts (each time excluding one district) and multiplying this poverty vector with a known weight matrix to obtain the unknown district-level poverty vector. The proposed method is expected to yield reliable estimates at the district level, because the district-level estimate is now based on a much larger sample size obtained by pooling data of several districts. This method can be an alternative to the “small area estimation technique” for estimating poverty at sub-state levels in developing countries.     

农村贫困、收入不平等与城镇化关系的实证研究——基于2000—2012年省际面板数据

城镇化进程对经济和社会产生了巨大影响。通过计算中国省际层面2000—2012年城镇化率、农村贫困发生率和农村基尼系数,利用面板数据固定效应模型,研究中国农村贫困、农村不平等和城镇化的关系。研究发现:农村贫困发生率随着城镇化率提高而下降,城镇化率每提高1%,农村贫困发生率会降低2.87%;农村收入不平等随城镇化水平提高呈弱倒U型变化。同时,不同地区城镇化对农村贫困、农村收入不平等的影响也呈现不同趋势。在未来城镇化战略中,实施农村减贫政策时应兼顾调整收入分配政策,降低农村收入不平等。