Methodology

The research underpinning the third edition of European Financial Flows on SDG7 to Africa is based on the production of a dataset as comprehensive and robust as possible. The dataset is comprised of commitments and disbursements to SDG7-compliant projects in Africa for the period 2014-2022 from public donors (bilateral and multilateral), African national governments, and the private sector.

Public data was primarily taken from the OECD’s Development Assistance Committee Creditor Reporting System (OECD DAC CRS), which tracks aid commitments and disbursements from OECD members.

Given that contributions to SDGs are of a certain qualitative standard, only public finance, classified as ODA or Other Official Flows (OOF), is included. Non-ODA finance (such as export credit) is omitted, as are public financial flows where data is not made available in a transparent way. For this reason, data on the Chinese financing of energy in Africa has been excluded.

For this third edition, data on private investments was derived from the OECD’s Mobilised Private Finance for Development database, which provides the most comprehensive and readily available source of private finance.

For African national government budget data, open source research was used to uncover spending at the department level. However, in some instances, spending was only available at the ministerial level instead of departmental level (e.g. budget of the Ministry of Energy instead of disaggregated for the electricity department). While data availability has improved over the years, it is still not possible to identify SDG7-compliant spending within budget documents. Where possible, project and programme information was used to exclude non-SDG7 spending.

Unless stated otherwise, the headline figures presented in this report are commitments as reported to the OECD DAC. Disbursements are analysed in parallel to track how much money has been actually disbursed versus that committed, and to quantify the grant equivalent and concessionality of investments.

It is important to note that due to the dispersed and disparate nature of data on the African continent, it was not possible to obtain an entirely exhaustive dataset. All the EU Member States and OECD member financing has been captured, but limited data is available for other actors, including regional development banks, other multilateral organisations, and non-OECD states. The dataset is built on project-level data to the greatest extent possible. This approach ensures that double counting is avoided. In some cases, project-level information is unavailable, at which point aggregated data published by credible organisations is used, if not already captured.

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