Inequality and Trade Policy: The Pro‐Poor Bias of Contemporary Trade Restrictions

This paper studies the pro‐poor bias of trade policy in India by estimating the household welfare effects of removing the current protection structure. The elimination of a pro‐poor trade policy is expected to have a negative differential welfare effect at the low end of the distribution. The paper first constructs trade restrictiveness indexes for household consumption items and industries using both tariffs and non‐tariff barriers. The results indicate that Indian trade policy is regressive through the expenditure channel as it disproportionately raises the cost of consumption for poorer households, while it is progressive through the earnings channel. Based on the net welfare effects, the elimination of the current trade protection structure is estimated to reduce inequality. These results indicate that a trade policy that is progressive through the earnings channel may induce a price effect that is regressive through the expenditure channel.     

地理资本视角下村级多维贫困测度及贫困类型划分*——基于重庆市1 919个市级贫困村调研数据

[目的]精确测度村级多维贫困以及划分贫困类型,是当前提高贫困识别精准度,进一步推进农村精准脱贫的战略需求。[方法]文章基于重庆市1 919个市级贫困村的调研数据,构建地理资本视角下村域多维贫困测度指标体系,并采用多维贫困测度模型、指标贡献度模型和最小方差方法系统揭示了重庆市贫困村多维贫困程度、贫困类型及其空间分布特征。[结果](1)重庆市贫困村多维贫困程度呈两端大中间小的"哑铃状"结构,贫困程度极化特征显著,区域发展具有不平衡性。空间分布上,贫困村多维贫困程度呈从渝东北、渝东南分别向渝西地区逐渐减轻的特征,贫困村多维贫困程度存在明显的地域性差异;(2)重庆市贫困村贫困类型主要分为单资本缺失型、双资本缺失型、三资本缺失型、四资本缺失型4个类型,其占比分别为9.07%、20.27%、66.91%、3.75%,三资本缺失型是最主要的贫困类型。[结论]重庆市贫困村致贫因素复杂多样,需要根据各自的贫困特征,因地制宜地开展差别化的帮扶工作。科学推进精准扶贫战略,力争实现2020年全面脱贫。     

Is green growth relevant for poor economies?

To be relevant to developing countries, green growth must be reconciled with the two key structural features of natural resource use and poverty in these countries. First, primary products account for the majority of their export earnings, and they are unable to diversify from primary production. Second, many economies have a substantial share of their rural population located on less favored agricultural land and in remote areas, thus encouraging “geographic” poverty traps. If green growth is to be a catalyst for economy-wide transformation and poverty alleviation in developing countries, then it must be accompanied by policies aimed directly at overcoming these two structural features. Policies and reforms should foster forward and backward linkages of primary production, enhance its integration with the rest of the economy, and improve opportunities for innovation and knowledge spillovers. Rural poverty, especially the persistent concentration of the rural poor on less favored agricultural lands and in remote areas, needs to be addressed by additional targeted policies and investments, and where necessary, policies to promote rural-urban migration.     

Where to donate: The geographical distribution of corporate philanthropy in China

An emerging body of literature has demonstrated that corporate philanthropy can be an important part of a company’s business strategy. However, we know relatively little about how companies allocate philanthropic resources to achieve their strategic targets. Using geographical distribution data on corporate philanthropy in China from 2009 to 2016, we provide robust evidence of companies’ revenue-driven regional favoritism. Specifically, companies donate more to regions where they obtain revenue than to other regions. Further evidence suggests that this revenue-driven regional favoritism may have both reputational and political motivations. Further analysis suggests that China’s targeted poverty alleviation policy has compromised revenue-driven regional favoritism while increasing the amount of money donated to poor regions. Overall, we enrich understanding of decision-making on corporate philanthropy. We also demonstrate that companies can use the geographical distribution of corporate philanthropy strategically to obtain consumer and government favor in regions where they operate. The results also provide evidence at the micro company level of the effect of China’s implementation of a targeted poverty alleviation policy.     

湘鄂赣特困山区乡村振兴路径探析

［目的］湘鄂赣山区是重要的革命老区，也是连片特困地区。根据党和政府精准脱贫要求，把握现状，明确目标，实现湘鄂赣特困山区精准脱贫攻坚与乡村振兴的相结合。［方法］运用实证分析法，分析湘鄂赣山区的致贫与发展因素，创新因山致富路径，实现山区乡村振兴目标。［结果］截止“十三五”，初步构建特色支柱产业体系； 全面解决无电人口用电问题； 推进农村主要道路硬化，不断提高山区农村防灾抗灾能力，农村的居住条件得到显著改善； 实现山区基础教育、公共卫生和基本医疗服务更加均等； 农村公共文化服务体系逐步健全，农村社会保障和服务水平进一步提升。［结论］扬其优势，补其短板。坚定绿色发展，把后发优势做成强劲发展优势； 坚持创新发展，把短腿产业做成产业链条； 坚持特色发展，把山区特色产品做成致富产业； 坚持长远发展，把薄弱基础变成坚实基础，如期全面建成小康社会。     

Asset indexes and the measurement of poverty,inequality and welfare in Southeast Asia

Using data on household consumer durables from the Asian Barometer Survey, this paper examines the evolution of inequality, poverty and welfare in six countries of South East Asia: Cambodia, Indonesia, Malaysia, the Philippines, Thailand and Vietnam. We start by deriving the most common order of acquisition of these durables, using first an algorithm proposed by Paroush (1965), and then Item Response Theory. We also compute the frequency distribution of the number of durables owned by households. We then use these results to compute inequality, poverty and achievement or welfare indices adapted to the case of ordinal variables.Our empirical results confirm the existence of an order of acquisition. The results show that inequality was higher in Cambodia, Indonesia and the Philippines and lower in Vietnam, Thailand and Malaysia. A similar classification of countries was obtained when computing multidimensional poverty indices.Finally, using the welfare or achievement index recently introduced by Apouey et al. (2019), we found that welfare was generally higher in Vietnam, Thailand and Malaysia and lower in Cambodia, Indonesia and the Philippines.     

产权性质、企业精准扶贫行为与资本市场反应

以2015~2018年A股上市公司为研究对象，考察企业精准扶贫行为动因与方式选择及所引起的市场反应。结果发现：国有企业和政治关联民营企业精准扶贫更积极，但两者精准扶贫方式存在差异，国有企业更倾向整合型精准扶贫，政治关联民营企业则倾向慈善型精准扶贫。进一步，企业参与精准扶贫产生了积极市场反应；相较国有企业，民营企业精准扶贫产生的市场反应更积极，尤其体现在政治关联民营企业中。同时，扶贫方式及扶贫持续性对精准扶贫信息披露的市场反应有影响。     

Measurements and determinants of multifaceted poverty in South Africa

Poverty, despite being a multifaceted concept, is commonly measured in either absolute or relative monetary terms. However, it can also be measured subjectively, as people form perceptions on their relative income, welfare and life satisfaction. This is the first study that uses the National Income Dynamics Study data to analyse poverty across various objective and subjective methods. The paper finds that while respondents' poverty status varies across methods, blacks remain the racial group most likely to be defined as poor by at least one method. The multivariate analysis reveals that the impact of some explanatory variables, such as experience of negative events, frequency of crime victimisation, health status and importance of religious activities, is mixed across methods.