Poverty is relative and multidimensional. Given its complexity, multidimensional nature and the connections with history, context, politics and power, understanding and measuring poverty is by no means straightforward. A recent study co-authored by the JRC and the University of Berkley and published at the Journal of Development Studies, discusses the participatory creation of the Multidimensional Poverty Assessment Tool (MPAT).

The paper describes MPAT’s purpose and architecture, delves into how expert input was elicited to create purpose-built household and village surveys, assign cardinal scores and aggregation rules to survey item responses, and to finally arrive at a weighting scheme for aggregating the subcomponents. The paper also addresses how expertise in development frames problems and solutions in certain ways, why MPAT does not distil all the information into a single number, and offer ideas on how to use MPAT to create local level poverty lines.

The JRC contributed to this initiative also through a thorough statistical analysis and improvement of the surveys and the framework. Additionally, the JRC underpinned the design of the Excel spreadsheet of MPAT, which allows users to simply enter the survey data and automatically get the MPAT results.

With about 75% of the world's poor living in rural areas, one question is: How do we assess and measure rural poverty in order to be more effective at eradicating it? MPAT is a simple and innovative tool to help answer this question. MPAT is a survey-based thematic indicator, developed by an international consortium led by the International Fund for Agricultural Development (IFAD), a specialised agency of the United Nations. The MPAT is sufficiently universal to be relevant to most rural areas around the world, yet specific enough to provide project managers and others with a detailed overview of ten key dimensions relevant to rural poverty alleviation: (1) food & nutrition security, (2) domestic water supply, (3) health & health care, (4) sanitation & hygiene, (5) housing, clothing & energy, (6) education, (7) farm assets, (8) non-farm assets, (9) exposure & resilience to shocks, (10) gender & social equality. The tool went through extensive field testing in several countries (China, India, Mozambique, Bangladesh and Kenya) and was independently validated and peer-reviewed. MPAT is relatively easy to use, requires limited resources to implement, and provides users with a reliable and comprehensive picture of a community’s poverty situation.