The JRC supported the United Nations' International Fund for Agricultural Development (IFAD) to develop the Multidimensional Poverty Assessment Tool (MPAT), launched today at the UN IFAD premises in Rome. MPAT is an innovative tool for assessing, understanding and addressing rural poverty. It provides data that can inform all levels of decision-making by providing a clearer understanding of rural poverty at household and village level. As a result, MPAT can significantly strengthen the planning, design, monitoring and evaluation of a project, and thereby contribute to rural poverty reduction.
MPAT is an open source, multi-purpose, survey-based, thematic indicator designed to support monitoring and evaluation, targeting and prioritising efforts at local level. It 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 JRC contributed to this initiative with a thorough statistical analysis and improvement of the surveys and the framework. It also co-authored an academic paper with IFAD, and designed the Excel spreadsheet of MPAT, which allows users to simply enter the survey data and automatically get the MPAT results. The JRC analysis statistically confirmed the suitability of using a ten-dimensional thematic indicator, as opposed to a final composite indicator, and verified the overall robustness of MPAT’s architecture.
MPAT is the result of a collaborative, international initiative that started in 2008. 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.