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GCRF: Pseudo-Panels for Long Period Analysis of African Household Surveys

GCRF：非洲家庭调查长期分析的伪面板

基本信息

批准号：
ES/P003389/1
负责人：
Oliver Morrissey
金额：
$ 20.15万
依托单位：
University of Nottingham
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=ES%2FP003389%2F1
关键词：
GCRF Pseudo Panels Long Period

项目摘要

National household surveys have become the standard source of data for analysis of poverty in developing countries. A major limitation of these surveys for Africa, in terms of the potential to analyse poverty dynamics, is that they are not a panel - different households are surveyed in each wave so they constitute repeated cross sections. It is therefore not possible to track the same households over time to investigate the drivers of poverty reduction. This creates challenges for analysis with endogenous variables, such as interactions between household size and poverty or migration, remittances and household income. The absence of a panel also limits analysis of determinants of household welfare over long periods.The strategy we propose to address this data restriction is to identify representative household types to construct pseudo panels making use of the repeated cross section household surveys (see the Case for Support). Analysis of the pseudo panel allows one to track similar households and complements household-level analysis for each survey. The project will develop methods for constructing pseudo-panels that can be applied, with suitable modifications for specific features of the surveys, in any country with three or more national household surveys. In principle, the methods are also applicable to census and Demographic and Health Survey data. Although the project focuses on Uganda (1992-2012 using eight existing surveys), the methods for constructing and analysing pseudo-panels can be applied to other African countries. Utilising established links with local research partners, hence largely 'off-budget', the pseudo-panel method will be applied to Ghana (1991-2013 using 6 surveys) and Tanzania (1991-2012 using 4 surveys).These three countries all have managed to roughly halve headcount poverty since the early 1990s.We use the repeated cross-section survey data to form a pseudo panel of 'representative' households by grouping individual households (the observational units) into cohorts on the basis of time invariant characteristics (location, gender and birth cohort of household head). The cohorts are then traced over time as they appear in successive surveys, forming a pseudo panel with 'lagged values'. As the cohort fixed effect is correlated with cohort (household) characteristics that are unobserved and not constant over time due to the changing membership of the cohorts in each survey, an errors-in-variables estimator is used to correct the cohort means as estimates of the unobservable population means. The lagged dependent variable is constructed from an auxiliary regression with an augmented instrumental variables estimator using time-invariant instruments. The pseudo panel therefore permits a long (20 years or more) analysis of determinants of household welfare and poverty reduction, with the potential to generate internal instruments for endogenous variables and to identify effects of policy changes (such as Universal Primary Education in Uganda). The project is expected to make a number of contributions. First, methods for constructing and using pseudo-panels will be developed, tried and tested generating a transferable method of potential use for most developing countries, especially in Africa where there are many surveys but few panels. Second, the pseudo-panel will be used to provide new insights on the drivers of poverty reduction in Uganda, with more limited applications (during the life of this project) to Ghana and Tanzania. Third, through training and research collaboration we will support building research capacity in Africa (specifically Uganda). To support these aims, an inception workshop in Kampala will include a variety of stakeholders with focus groups to identify the important research and policy issues; there will be dissemination in country and through AERC; and training will be provided to local researchers.

国家住户调查已成为发展中国家贫穷分析的标准数据来源。就分析贫困动态的潜力而言，这些非洲调查的一个主要局限性是，它们不是一个小组--不同的家庭在每一波调查中被调查，因此它们构成了重复的横截面。因此，不可能在一段时间内追踪相同的家庭，以调查减贫的驱动因素。这给使用内生变量进行分析带来了挑战，例如家庭规模与贫困或移民、汇款与家庭收入之间的相互作用。我们建议解决这一数据限制的策略是确定具有代表性的家庭类型，以利用重复的横断面住户调查来构建伪面板(见支持案例)。对伪面板的分析使人们能够跟踪类似的家庭，并补充了每项调查的家庭层面的分析。该项目将开发可应用于拥有三个或三个以上全国住户调查的任何国家的伪面板的方法，并对调查的具体特征进行适当的修改。原则上，这些方法也适用于人口普查和人口与健康调查数据。虽然该项目侧重于乌干达(1992-2012年使用8项现有调查)，但构建和分析伪小组的方法也可适用于其他非洲国家。利用与当地研究伙伴建立的联系，因此主要是“预算外”，伪面板方法将应用于加纳(1991-2013年使用6项调查)和坦桑尼亚(1991-2012年使用4项调查)。这三个国家自20世纪90年代初以来都设法将贫困人口减半。我们使用重复的横断面调查数据，通过根据时间不变的特征(家庭户主的位置、性别和出生单位)将个别家庭(观察单位)分组，形成一个具有代表性的家庭的伪小组。然后，随着时间的推移，这些队列会被追踪，因为他们出现在连续的调查中，形成了一个具有“滞后值”的伪小组。由于队列固定效应与队列(家庭)特征相关，这些特征没有被观察到，并且由于每次调查中队列成员的变化而不是随时间变化而恒定的，因此使用变量中误差估计器来校正队列平均值，将其作为不可观测总体平均值的估计。滞后因变量由辅助回归和使用时不变工具的增广工具变量估计器构成。因此，伪小组可以对家庭福利和减贫的决定因素进行长时间(20年或更长时间)的分析，有可能为内生变量产生内部工具，并确定政策变化的影响(如乌干达普及初等教育)。预计该项目将做出一些贡献。首先，将开发、试验和测试建造和使用伪板的方法，为大多数发展中国家提供一种可转让的潜在使用方法，特别是在调查多但板少的非洲。其次，伪小组将被用来提供关于乌干达减贫驱动因素的新见解，在加纳和坦桑尼亚的应用范围更有限(在本项目的生命周期内)。第三，通过培训和研究合作，我们将支持非洲(特别是乌干达)的研究能力建设。为支持这些目标，将在坎帕拉举办一次启动讲习班，包括各种利益攸关方和重点小组，以确定重要的研究和政策问题；将在国内和通过AERC进行传播；并将向当地研究人员提供培训。