Measuring Regional Ethnolinguistic Diversity in Sub-Saharan Africa - Surveys vs. GIS - Supplementary Article

Jul 19, 2026

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This paper compares two ways to measure subnational ethnolinguistic diversity in Sub-Saharan Africa: survey and census-based approaches versus geographic information system (GIS) methods. Both strategies produce regional fractionalization indices that are moderately positively correlated, with differences that are more pronounced in rural areas. In a shared sample, survey-based indices capturing deep-rooted diversity show a stronger negative relationship with multiple development indicators than higher-quality GIS-based counterparts. The findings highlight how measurement error and data construction affect empirical conclusions about diversity and development.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages6

Reading Time15 min

Introduction

The Survey-Based Approach

Pub lic Disclosure Authorized Pub lic Disclosure Authorized The World Bank Economic Review, 34(Supplement), 2020, S40–S45 doi: 10.1093/wber/lhz032 Supplementary Article Measuring Regional Ethnolinguistic Diversity in Sub-Saharan Africa: Surveys vs. GIS Boris Gershman and Diego Rivera Abstract This paper compares two approaches to measuring subnational ethnolinguistic diversity in Sub-Saharan Africa, one based on censuses and large-scale population surveys and the other relying on the use of geographic information systems (GIS). The two approaches yield sets of regional fractionalization indices that show a moderately positive correlation, with a stronger association across rural areas. These differences matter for empirical analysis: in a common sample of regions, survey-based indices of deep-rooted diversity show a more strongly negative association with a range of development indicators relative to their highest-quality GIS-based counterparts. JEL classification: O10, O15, Z13 Keywords: African development, ethnolinguistic diversity, GIS, household surveys, public goods provision, subnational analysis 1. Introduction Ethnolinguistic diversity has long been viewed as an important determinant of various development outcomes, including income per capita, public goods provision, quality of governance, and violent conflict. Given the extraordinary diversity of its population, the political salience of ethnicity, and the relatively low rates of economic growth, the African continent occupies a special place in this line of research. Naturally, reliable data are the key ingredient in any empirical study. While there are several datasets on ethnic and linguistic diversity commonly used in cross-country analyses, there are no similarly established sources at the subnational level. This paper examines two approaches to constructing such a dataset fora large sample of regions within Sub-Saharan African countries. First, this study briefly discusses the contribution of Gershman and Rivera (2018), who employ censuses and large-scale household surveys to measure subnational ethnolinguistic diversity. Second, this study shows how the GIS approach, based on combining digital maps of ethnolinguistic groups with disaggregated population data, may be used to accomplish the same goal. Finally, this article compares the sets of fractionalization indices resulting from the two strategies, discusses the likely sources of measurement error, and demonstrates that the choice of approach matters for the empirical analysis of the relationship between regional diversity and development outcomes. Boris Gershman (corresponding author) is an associate professor of economics at American University; his email address is [boris.gershman@american.edu. Diego Rivera](boris.gershman@american.edu. Diego Rivera) is an adjunct instructor in the School of International Service at American University; his email address [is hr6106a@american.edu](is hr6106a@american.edu). © The Author(s) 2019 . Published by Oxford University Press on behalf of the International Bank for Reconstruction and Development / THE WORLD BANK. All rights reserved. For permissions, please e-mail: [journals.permissions@oup.com](journals.permissions@oup.com) Downloaded from [https://academic.oup.com/wber/article/34/Supplement_1/S40/5648241](https://academic.oup.com/wber/article/34/Supplement_1/S40/5648241) by guest on 23 June 2021 2. The Survey-Based Approach A standard approach to constructing any dataset on regional sociodemographic characteristics is to compile the information from relevant population surveys. Gershman and Rivera (2018) introduce and describe the product of a comprehensive effort to compile the data on subnational ethnolinguistic composition of Sub-Saharan Africa based on this approach. The dataset contains 36 countries, almost 400 first-level administrative units, and 750 unique ethnolinguistic groups. For each country, the study picked the best

FAQs

What two approaches does the paper compare for measuring subnational ethnolinguistic diversity?

It compares a survey/census-based approach and a GIS-based approach that combines digital maps of ethnolinguistic groups with disaggregated population data.

How do the two approaches relate in terms of the resulting fractionalization indices?

The regional fractionalization indices show a moderately positive correlation overall, with a stronger association across rural areas.

Why does the choice of approach matter for empirical development analysis?

Because, in the same regional sample, survey-based indices of deep-rooted diversity relate more negatively to development indicators than the closest GIS-based counterparts, reflecting differences in measurement error and data construction.

Jul 19, 2026

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