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

许多非洲经济体正在迅速增长，农村和城市地区出现了繁荣的迹象。便宜的技术（移动的电话、摩托车和改良的种子品种）正在普及到许多国家的所有地区，除了最偏远的地区。然而，这种增长的包容性和扶贫性并不总是很清楚。例如，提高农业生产的好处很容易集中在相对少数的富裕农民身上，甚至在造成农村贫困和无土地方面起了推波助澜的作用。富人享有的更大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，但在缺乏农业的可行替代品的情况下，他们没有繁荣和长期前景。在这方面，关键问题是农村穷人在国家经济增长期间能够积累哪些资产。伴随着资产损失（农田或牲畜损失）的增长，或伴随着穷人无法积累新资产（如帮助子女获得教育资格）的增长，无论是在家庭之间，还是在家庭内部（根据其性别动态），都不会具有包容性。小组数据集可以提供一些关于这些动态的见解。然而，这些都是少数，他们可以遭受磨损，他们仍然是定量分析和建模的几乎独家保留。定性数据的洞察力很少被运用到面板数据上。缺少这些数据，就缩小了提出假设的范围，也缩小了定性数据对贫穷动态所能提供的深入和感性的见解。相反，定性数据的缺陷是它们的特质和规模小，以及它们给外推带来的困难。他们的存在并不总是有见地超越他们的直接案例研究，这项研究将利用在坦桑尼亚的调查数据的异常良好的记录，提供在一个足够大的区域，以克服定性数据的正常故障的定性数据的见解，并作出建设性的贡献定量面板数据的结果。坦桑尼亚通过科学和技术委员会的记录，对在该国开展活动的外国研究人员有独特的记录。东非收藏品包含坦桑尼亚硕士和博士生撰写的论文。这些资料，加上坦桑尼亚国内外现有的强大研究人员网络，为查明以前的调查提供了独特的资源。我们将重新审视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1990年代收集的。我们将重新访问这些家庭的样本，重新调查他们的资产，然后通过详细的定性访谈探索他们财富变化（或缺乏变化）背后的原因。这些数据将丰富而详细地反映村庄、家庭和次级家庭一级的贫穷和减贫动态。这些方法已经试行。PI今年重新访问了Loiske（co-I）在20世纪90年代初调查的社区。这项工作证明了这种方法是可行的，而且它产生了有价值的见解。然而，我们需要一个更强有力的比较框架和来自其他区域的数据，使其成为一个强有力的工具。这就是拟议研究的目的。这项工作在方法上和实质上都很重要，为其他研究人员提供了一个工具包和数据库，并深入了解包容性增长背后的性质和因素。

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.