权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

The generation and distribution of rural prosperity: insights from longitudinal survey data.

乡村繁荣的产生与分配：来自纵向调查数据的见解。

基本信息

批准号：
ES/L012413/1
负责人：
Daniel Brockington
金额：
$ 54.46万
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2015
资助国家：
英国
起止时间：
2015 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=ES%2FL012413%2F1
关键词：
generation distribution rural prosperity insights

项目摘要

Numerous African economies are growing rapidly and there are signs of prosperity in rural and urban regions. Cheaper technology (mobile phones, motorbikes and improved seed varieties) are reaching all but the remotest parts of many countries. However it is not always clear how inclusive and pro-poor this growth is. It is all too easy for the benefits of improved agricultural production, for example, to be concentrated on relatively few wealthy farmers and even to be instrumental in creating rural deprivation and landlessness. The greater returns the wealthy enjoy enable them to concentrate land and resources. Those without land become a rural proletariat, their livelihoods part of the general trend towards deagrarianisation, but in the absence of viable alternatives to agriculture they are not characterized by prosperity and long term prospects. In this context the key issue is what assets the rural poor can build up during periods of national economic growth. Growth which is accompanied by loss of assets (loss of farmland or livestock), or a failure to accrue new assets (such as help children earn educational qualifications) among the poor, either across households, or within households (according to their gender dynamics) will not be inclusive. Panel data-sets can provide some insights into these dynamics. However these are few, they can suffer from attrition, and they remain the almost exclusive preserve of quantitative analysis and modeling. The insights of qualitative data have rarely been brought to bear on panel data. Their absence reduces the scope for hypothesis generation, and the in-depth and emic insights into poverty dynamics that qualitative data can provide. Conversely the flaws of qualitative data are their idiosyncrasy and their small scale and the difficulties they present for extrapolation. Their presence is not always insightful beyond their immediate case studies.This study will make use of unusually good records of survey data in Tanzania to provide the insights of qualitative data across a sufficiently large area to overcome the normal failings of qualitative data and contribute constructively to the findings of quantitative panel data. Tanzania has unique records of foreign researchers active in the country through the records of the Commission for Science and Technology. The East Africana collection contains theses written by masters and doctoral students in Tanzania. These, together with the strong networks that exist of researchers in and from Tanzania, provide a unique resource from which to identify former surveys. We will revisit a number of communities in different parts of Tanzania for whom data on household assets were collected in the 1990s. We will revisit a sample of these households, re-survey their assets and then explore through a detailed qualitative interview the reasons behind the changes (or lack of changes) in their fortunes. These data will provide a rich and detailed picture into the village and household and sub-household level dynamics of poverty and poverty reduction. These methods have already been piloted. The PI has, this year, revisited a community surveyed by Loiske (co-I) in the early 1990s. This work has proved that the method is possible, and that it produces valuable insights. We need, however, a stronger comparative framework and data from other regions for this to be a powerful tool. That is the purpose of the proposed research. This work will be important methodologically and substantively, providing a toolkit and database for other researchers to use, as well as insights into the nature and factors that lie behind inclusive growth.

非洲众多经济体快速增长，农村和城市地区出现繁荣迹象。更便宜的技术（手机、摩托车和改良种子品种）正在普及到许多国家除最偏远地区之外的所有地区。然而，这种增长的包容性和有利于穷人的程度并不总是清楚。例如，农业生产改善的好处很容易集中在相对较少的富裕农民身上，甚至会造成农村贫困和无土地。富人享有的更高回报使他们能够集中土地和资源。那些没有土地的人成为农村无产阶级，他们的生计是非农业化总趋势的一部分，但由于缺乏农业的可行替代方案，他们的特点是不繁荣和长期前景。在这种情况下，关键问题是农村贫困人口在国民经济增长期间能够积累哪些资产。伴随着贫困人口资产损失（农田或牲畜损失）或无法积累新资产（例如帮助儿童获得教育资格）的增长，无论是跨家庭还是家庭内部（根据其性别动态）都不会具有包容性。面板数据集可以提供对这些动态的一些见解。然而，这些数量很少，它们可能会受到磨损，并且它们仍然几乎是定量分析和建模的专有领域。定性数据的见解很少应用于面板数据。它们的缺失减少了假设生成的范围，也减少了定性数据可以提供的对贫困动态的深入和普遍的洞察。相反，定性数据的缺陷在于它们的特质、规模小以及它们给外推带来的困难。除了直接案例研究之外，他们的存在并不总是具有洞察力。本研究将利用坦桑尼亚异常良好的调查数据记录，提供足够大区域内定性数据的见解，以克服定性数据的正常缺陷，并为定量面板数据的发现做出建设性贡献。通过科学技术委员会的记录，坦桑尼亚拥有在该国活跃的外国研究人员的独特记录。东非馆藏包含坦桑尼亚硕士和博士生撰写的论文。这些，再加上坦桑尼亚国内外研究人员的强大网络，为识别以前的调查提供了独特的资源。我们将重新访问坦桑尼亚不同地区的一些社区，这些社区的家庭资产数据是在 20 世纪 90 年代收集的。我们将重新审视这些家庭的样本，重新调查他们的资产，然后通过详细的定性访谈探讨他们的财富发生变化（或没有变化）背后的原因。这些数据将为村庄、家庭和亚家庭层面的贫困和减贫动态提供丰富而详细的信息。这些方法已经进行了试点。今年，PI 重新访问了 Loiske（co-I）在 20 世纪 90 年代初调查的一个社区。这项工作证明了该方法是可行的，并且它产生了有价值的见解。然而，我们需要一个更强大的比较框架和来自其他地区的数据，才能使其成为一个强大的工具。这就是拟议研究的目的。这项工作在方法论和实质上都很重要，为其他研究人员提供了使用的工具包和数据库，并深入了解包容性增长背后的本质和因素。