This file contains data on Ugandan households from six nationwide surveys conducted between 1992 and 2013. Data is available on aggregate household consumption, earnings activities, location of the household, and characteristics of the household head. The file also contains cohort level data where household have been aggregated into cohorts for pseudo-panel analysis. 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).

Data is taken from nationwide household surveys conducted by the Ugandan Bureau of Statistics.