As in many developing countries, in Mali, generating reliable and up-to date data beyond national averages to uncover geographic and other inequalities is one of the major challenges for rigorous monitoring of progress towards achieving the SDGs. Mali’s National Observatory for Human Development has set up a mechanism to generate socio-economic and poverty metrics for 703 municipalities based on the small area estimation procedure. The generated metrics shed light on poverty inequalities among municipalities while providing information on SDG acceleration integrated policies. This experience of data processing shows that existing data at the supra-communal level can be used to infer useful indicators that uncover the most deprived people, inform local development policies and offer reliable inputs for predictive modelling for anticipatory governance.

Localizing Multidimensional Poverty Assessments for Inclusive Public Policies: The Case for a Communal Poverty Profile in Mali

Resource Key: 6I7G3I3Z

Document Type: Report

Creator:

Author:

  • Ademonkoun Rodolphe Missinhoun

Creators Name: {mb_resource_zotero_creatorsname}

Place: Washington D.C.

Institution: United Nations Development Programme

Date: April 2024

Language: en

As in many developing countries, in Mali, generating reliable and up-to date data beyond national averages to uncover geographic and other inequalities is one of the major challenges for rigorous monitoring of progress towards achieving the SDGs. Mali’s National Observatory for Human Development has set up a mechanism to generate socio-economic and poverty metrics for 703 municipalities based on the small area estimation procedure. The generated metrics shed light on poverty inequalities among municipalities while providing information on SDG acceleration integrated policies. This experience of data processing shows that existing data at the supra-communal level can be used to infer useful indicators that uncover the most deprived people, inform local development policies and offer reliable inputs for predictive modelling for anticipatory governance.

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