11:15am, Schlich Lecture Theatre, Department of Plant Sciences, South Parks Road, Oxford, OX1 3RB
This seminar considers the two main approaches that have been used to address the measurement of multi-dimensional poverty (MDP) in the developing world: the Alkire-Foster method and the ‘categorical counting’ method as exemplified by UNICEF poverty indices using methodologies by Gordon et al and De Neubourg et al.
Discussion begins with the sources of survey micro-data that have been extensively used for these indices, the Multiple Indicator Cluster Surveys (MICS) and the Demographic and Health Surveys (DHS) and the resulting constraints on indices constructed from these sources on measurement and coverage of MDP for children.
Two important constraints are identified as affecting measurement of MDP across both indices: a) the inclusion of both household level and individual level indicators, b) the age-specificity of individual indicators for children and representation in survey data. Analysis then moves to consider the underlying differences between the two methodologies in two stages.
First, using Monte Carlo simulations of hypothetical data we consider the differences in measurement properties that arise from axiomatic construction of indices, and the effects that ‘household and individual’ mixed level data and ‘age specificity’ have on such axiomatic properties.
Second, we use harmonized MICS and DHS data from five countries to examine how those axiomatic differences in measurement properties affect MDP prevalence within and across countries, and the ability of indices to monitor changes in MDP prevalence using basic tests of robustness and sensitivity.
The paper concludes by considering the findings from the analysis and how they could be taken forward in the future collection and analysis of survey data for estimating MDP for children, given recent developments in the content of household surveys with the adoption of global SDG indicators, particularly in the MICS programme.