The global Multidimensional Poverty Index (MPI) 2026: disaggregation results and methodological note

Working paper

This methodological note presents the methodology and technical decisions that underlie the published disaggregation results (age groups, urban and rural areas, subnational regions and gender of household head) of the global Multidimensional Poverty Index (MPI) 2026. The 2026 MPI disaggregation results are based on the most recent data from 108 countries, covering 6.3 billion people. We estimate the MPI and its associated statistics by four age categories (0–9 years, 10–17 years, 18–59 years, and 60 years and over) as well as two broad age categories covering children aged 0–17 years and adults 18 years and older, by urban and rural areas and by the gender of the household head. The MPI is also computed for 1,360 subnational regions across 100 countries to show disparities in poverty within countries. Subnational disaggregations are published when the survey used for the global MPI is representative at the subnational level, and the retained sample permits such disaggregation. This note is structured as follows. Section 2 presents the global MPI structure and indicator definitions and Section 3 outlines the global MPI and its partial indices that we estimate and publish. Section 4 details the disaggregation methodology, while Section 5 outlines the principles and decisions that underlie our disaggregation work. Section 6 summarises the country-specific decisions applied to the new or updated datasets in this round. Section 7 concludes.

Authors: Alkire, S; Mishra, R; Suppa, N

• Publication status: Published
• Peer review status: Reviewed (other)
• Publisher: Oxford Poverty and Human Development Initiative (OPHI)
• Host title: OPHI MPI Methodological Notes
• Pages: 1-16
• Series: OPHI MPI Methodological Notes
• Place of publication: Oxford, UK
• Publication date: 2026-10-12
• Paper number: 65
• Language: English
• Keywords: Global MPI; disaggregation; methodology; Alkire-Foster method; poverty measurement; Multidimensional Poverty Index (MPI)