Introducing the Mind-the-Gap Index: A Tool to Understand Urban Spatial Inequality

Authored by: Jeni Klugman and Matthew Moore

Categories: Human Rights
Sub-Categories: Democratization and Political Participation, Economic Participation, Economic Recovery, Human Development
Region: No Region
Year: 2021
Citation: Jeni Klugman and Matthew Moore. "Introducing the Mind-the-Gap Index: A Tool to Understand Urban Spatial Inequality." The Grand Challenge on Inequality and Exclusion. February 2021.

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Executive Summary

Where people live exerts a strong influence on multiple aspects of their well-being, including their access to economic opportunities, education, health and other services and to their security, as well as other goals envisioned in the 2030 Agenda. It is well known that inequalities related to location – also known as “spatial inequalities” – can be extreme between rural and urban areas, and this has been a focus of much attention in development over recent decades. On average, people in rural areas continue to have worse job opportunities and less access to education, safe drinking water, health services and high-quality infrastructure than urban residents. The World Bank and UN estimate that at least 80 per cent of people living in income poverty are found in rural areas.1 A strong focus on easing the rural-urban divide is needed to ensure that no one is left behind.

This paper is a synthesis of several research papers which provide more detail on the evidence, data and methods, which are available on request.5 The synthesis outlines what we know–drawing on recent research from UNDESA6 and others–to outline the extent of spatial disparities and the ways that spatial inequality shapes today’s cities and the key factors driving spatial disparities. (A separate note discusses how the COVID-19 pandemic is worsened by spatial disparities.) Section 3 introduces a new index designed to capture key dimensions of spatial inequality. Section 4 presents results from three pilot applications in Addis Ababa, Jakarta, and Mexico City drawing on existing neighborhood and sub-district data. The work highlights the importance of granular and up-to-date data, as well as the accumulating nature of disadvantage in poor neighborhoods. Section 5 provides the conclusion.