Published September 8, 2024 | Version v3

Assessing Grid Affordability for Universal Electricity Access in Sub-Saharan Africa

Authors/Creators

Description

This repository contains the data and tools used in the paper Assessing Grid Affordability for Universal Electricity Access in Sub-Saharan Africa. It includes tariff structure documents for 48 Sub-Saharan African (SSA) countries, together with population data, Gini index values, and gross national income (GNI) per capita data used to simulate income distributions. The repository also provides tools for estimating Multi-Tier Framework (MTF)-based electricity bills and evaluating grid electricity affordability for households against simulated incomes.

The related code and result datasets supporting this paper are available through the GitHub public repository: https://doi.org/10.5281/zenodo.20348086.

Notes (English)

Average_affordability_by_country.xlsx: This dataset contains the average country-level household affordability results for each energy tier. The affordability results are calculated based on the methodology described in the paper, where country-specific income distributions are constructed using population, GDP per capita, and the Gini index, and compared with monthly residential electricity bills at different MTF-based energy tiers. The values in this dataset represent the average affordability across all population percentiles for each country under each energy tier. Additional details are available in the Methods and Results sections of the paper and the associated GitHub repository.

Electricity_Tariff_Calculator.xlsx: This database includes the latest residential electricity tariffs for 48 Sub-Saharan African (SSA) countries and estimates monthly residential electricity bills based on the Multi-Tier Framework (MTF).

Exchange_rate.xls: This file contains country-level exchange rate data sourced from the World Bank. For countries where World Bank data were unavailable, alternative data sources were used, as detailed in the paper’s Data Availability section.

Gini index.xlsx: This file contains country-level Gini index data sourced from the World Bank. For countries where World Bank data were unavailable, alternative data sources were used, as detailed in the paper’s Data Availability section.

GNI per capita 2023.xlsx: This file contains country-level GNI per capita data sourced from the World Bank. For countries where World Bank data were unavailable, alternative sources were used, as detailed in the paper’s Data Availability section.

Population.xlsx: This file contains country population data for 2024 sourced from the World Bank.

Residential_Electricity_Demand.xlsx: This dataset compiles and estimates actual residential electricity consumption across SSA countries as a proxy for electricity demand. The International Energy Agency (IEA) provides total residential electricity consumption data for 32 countries. For the remaining 16 countries where IEA data were unavailable, per capita electricity consumption data were sourced from Index Mundi. Further details are provided in the Methods section of the paper. This dataset supports the analysis presented in the “Affordability vs. Residential Electricity Demand” section of the Results.

SSA_Tariff_Documents.zip: This archive contains the original tariff structure documents for each country used in the analysis.

Summary_Electricity_Bills.xlsx: This dataset contains the calculated monthly residential electricity bills for each tier across 48 SSA countries, standardised to 2024 US dollars.

UPNEAT(World Bank)-Net profit margin.xlsx: This dataset provides proxy indicators of power utility financial performance for each country. Detailed calculation methods are described in the paper’s Data Availability section.

Files

SSA Tariff Documents.zip

Files (92.6 MB)

Name Size Download all
md5:36115e9add4bf423a270935f8fcd7acb
9.5 kB Download
md5:783487989eb3ba1440674cb51cac793d
2.3 MB Download
md5:3a18c6d0e4be784bf641b6ba96826085
338.9 kB Download
md5:268a9569b0959a5071ee144eb66bc8b7
1.1 MB Download
md5:5363e01979ed151a504df50b4db4c200
41.1 kB Download
md5:0eeaa12964b7514d0a38cb910496ff99
46.5 kB Download
md5:c1fe81e1c7c0fee149b219226df9f9ae
22.2 kB Download
md5:00a90166c0b1a488d19b4590795b178e
88.5 MB Preview Download
md5:6f5555c7cbb54e15c50c6ba6dfd4924c
209.7 kB Download
md5:398361cc8696738aeced7fb56d2a6535
38.4 kB Download

Additional details

Related works

Is supplement to
Journal article: 10.21203/rs.3.rs-6427206/v1 (DOI)

Dates

Updated
2026-05-11
Dataset updated following revisions to the associated paper after peer review.