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。除了许多国家最偏远的地区，更便宜的技术(移动电话、摩托车和改良的种子品种)正在普及。然而，这种增长的包容性和有利于穷人的程度并不总是明朗的。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，甚至造成农村贫困和无地。富人享有的更大回报使他们能够集中土地和资源。那些没有土地的人变成了农村无产阶级，他们的生计是去农业化总趋势的一部分，但在没有可行的农业替代方案的情况下，他们的特征不是繁荣和长期前景。在这方面，关键问题是农村贫困人口在国家经济增长期间可以积累什么资产。伴随着资产损失(农田或牲畜的损失)或穷人未能积累新资产(如帮助儿童获得教育资格)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)，都将不包括在内。面板数据集可以为这些动态提供一些见解。然而，这些数量很少，它们可能会受到磨损，而且它们仍然几乎是定量分析和建模的专属领域。定性数据的洞察力很少被运用于面板数据。它们的缺乏减少了假设生成的范围，以及定性数据可以提供的对贫困动态的深入和乏力的洞察。相反，定性数据的缺陷在于它们的特殊性和小范围，以及它们给外推带来的困难。这项研究将利用坦桑尼亚异常良好的调查数据记录，提供足够大范围内的定性数据的洞察力，以克服定性数据的正常缺陷，并对定量小组数据的结果作出建设性的贡献。坦桑尼亚通过科学和技术委员会的记录记录了活跃在该国的外国研究人员的独特记录。东非文集收录了坦桑尼亚硕士和博士生撰写的论文。这些，再加上坦桑尼亚境内和来自坦桑尼亚的研究人员现有的强大网络，提供了一个独特的资源，可以从中确定以前的调查。我们将重新访问坦桑尼亚不同地区的一些社区，1990年代收集了这些社区的家庭资产数据。我们将再次访问这些家庭中的一个样本，重新调查他们的资产，然后通过详细的定性访谈来探索他们财富变化(或没有变化)背后的原因。这些数据将为村、户和分户一级的贫困和减贫动态提供丰富和详细的图景。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。这项工作证明了这种方法是可能的，并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，才能使这一工具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，以及对包容性增长背后的性质和因素的洞察。

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.