Methodology, Data Notes and Definitions


The research underpinning this report is based on the production of as comprehensive and robust a dataset as possible comprising commitments and disbursements to SDG7-compliant projects in Africa for the period 2014-2019 from public donors, African governments and development institutions and the private sector. However, it is important to note that this dataset is by no means complete, reflecting the dispersed and disparate nature of data on the African continent. All EU Member State and OECD member financing has been captured, but limited data is available for other actors, including African development banks and other multilateral organisations.

The dataset is built on project-level data to the greatest extent possible. This approach ensures double counting is avoided. In some cases, project-level information in unavailable, at which point aggregated data published by credible organisations is used if not already captured.

Given that contributions towards SDGs are of a certain qualitative standard, only public finance classified as ODA is included. Non-ODA finance (such as export credit) is omitted, as are public financial flows where the levels of concessionality are opaque.

ODA data for 2014-2018 is sourced from the OECD DAC’s Creditor Reporting System (CRS). Due to this, the report uses OECD defined categories, despite not precisely matching those used by the SDGs. Donor funding for 2019 was sourced from donors directly via completion of questionnaires.

The OECD methodology for categorising ODA changed in 2019. Prior to this date, the face value of concessional finance which met certain criteria was classified as ODA, whereas from 2019 onwards only the ‘grant equivalent’ of this finance is classed as ODA. For comparability across the six-year study period, and due to the lack of grant equivalent data reported by donors, this report uses the previous definition of ODA for the entire study period.

Data on non-OECD member financial flows is not always published and often lacking in detail. There is no confirmation as to whether these investments qualify as ODA (a precondition in determining con- tributions to the SDGs) or as SDG7 compliant. There is also no comprehensive dataset on private sector investment in energy, and as such data has been sought from a number of sources, including the World Bank’s Private Participation in Infrastructure database, a number of industry associations including GOGLA and the African Minigrid Developers Association, Bloomberg New Energy Finance’s Climate- scope, and African Energy Live Data, among others.

Very limited information is available in the OECD DAC CRS on which SDG (if any) an investment targets. This data has only been provided since 2017 and few donors submit this information.

To remedy this, ODA and private data which is not specified as SDG7-compliant is assumed to be so if it is directed at the following sectors: Renewable energy; Transmission and distribution; Energy efficiency; Clean cooking; Clean transport.

While not directly contributing towards SDG7, ODA support for capacity building is reported due to it being an important enabler for additional investment into SDG7. This data is therefore included in the report, unless otherwise stated.

The report endeavours to obtain national government spending exclusive of recurrent expenditure, however in some countries only total departmental spending is available. Furthermore, while budget reporting has improved markedly in recent years, it is still not possible to identify SDG7-only spending. Therefore, the spending reported may include non-SDG7 investments.

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Data Notes

Official Development Assistance

With the exception of African national government spending and investments made by Africa-based development banks, only public funding that is classified as ‘Official Development Assistance’, as defined by the OECD, was included. To ensure consistency and comparability across the study period, the face-value of ODA commitments or disbursements was reported. This is despite a change to the OECD methodology whereby only the ‘grant element’ of an ODA grant, loan or equity investment are considered as ODA from 2019 onwards.

ODA data collection

A robust and verified dataset based on project-level information was compiled for this report. The use of project-level data allows disaggregation and minimises the risk of double counting.

ODA from bilateral and multilateral international financial institutions for the years 2014 to 2018 was sourced from the OECD DAC Creditor Reporting System (CRS). This data – which includes both commitments and disbursements – was provided by donors and verified by the OECD DAC. Private development finance from private sector charities, foundations and philanthropic organisations which was classified as ODA was also obtained from the OECD DAC CRS.

Data from non-OECD members (such as China, Brazil, Turkey etc) was obtained from various open sources, including development agency websites and monitoring of news flow and official reports. None of the data collected from these sources was proven to be ODA-compliant and was therefore not used in the analysis of SDG7 financing.

A complete dataset on 2019 ODA funding was unavailable via the OECD DAC CRS during the research and production of this report. Data from four donors was obtained via the OECD DAC CRS, while the remainder was sourced from donors directly; they were asked to complete a questionnaire.

Export credit

Export credit issued by China, India and South Korea was obtained, but was excluded as it is not ODA compliant and therefore not considered as SDG7-compliant. Export credit from the Export-Import Bank of the United States was unavailable, while export credit from EU Institutions and Member States has also not been captured.

Private sector data

Data on private sector operations is limited. Information was obtained from the World Bank’s Private Participation in Infrastructure database, which reports on private and public investments into energy projects which reached financial close during the period 2014-2019. This information was cross-referenced using the OECD DAC CRS, the African Energy Live Data platform and Bloomberg New Energy Finance’s Climatescope.

Further data on private finance was obtained from industry associations, where possible. However, this often did not include private equity investments; nor was it possible to allocate investments made directly into globally-focused companies which were active in Africa.

In all cases, the financing of private sector projects was disaggregated so that only private sector contributions were counted, thereby avoiding double counting where public support was already including within the OECD DAC CRS.

African national government spending

Data was obtained from official documents, including official gazettes, budget reports and speeches. Where possible, only capital expenditure for energy was counted.

In some cases, it is impossible to disaggregate spending between energy and water where a country has a joint ministry. It is also not possible to identify capital expenditure which is SDG7 compliant. As a result, all capital expenditure for energy is included within this report.


Donor categorisation

African National Governments: Sovereign governments of African Union Member States.

Africa-based development banks: African Development Bank (AfDB), Banque Ouest Africaine de Développement (BOAD), Development Bank of Southern Africa (DBSA), East African Development Bank (EADB), Ecowas Bank for International Development (EBID), Trade and Development Bank of Eastern and Southern Africa (TDB).

EU Institutions & Member States: European Union financial institutions (including European Commission and associated funds and the European Investment Bank), and ministries/development agencies/development banks of its Member States as of 31 December 2019 (Austria, Belgium, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, United Kingdom).

Other Europe (non-EU Member States): Countries geographically located within Europe, but which are not a member state of the European Union.

Middle East: Countries within the Middle East and the Levant.

Asia: Countries located geographically within Asia.

Oceania: Countries located geographically within the continent of Oceania.

North America: Canada, Mexico and The United States of America.

South America: Countries located geographically within the continent of South America.

Private sector: Any finance from private sector organisations (excluding state-backed commercial banks or state-owned organisation in China).

Multilaterals: Multilateral development finance institutions or development banks which are funded by multiple countries, regardless of geography. This category includes organisations such as the World Bank, Islamic Development Bank and the Arab Bank for Economic Development in Africa, but excludes multilateral institutions based in Africa.

Sector categorisation

The sectors, and subsectors, by which financing was aggregated was based on those used by the OECD DAC in order to ensure comparability and consistency.

SDG7 compliance

For 2019, donors who provided completed questionnaires were asked to indicate an individual project’s SDG7 compliance. However, the reporting of SDG7 compliance was extremely limited within the OECD DAC CRS. Therefore, only projects in the sectors of renewable generation, transmission and distribution, energy efficiency, clean cooking and clean transport were considered as SDG7-compliant. Non-renewable generation was excluded from the SDG7 category unless indicated as SDG7-compliant by the reporting donor. Commitments and disbursements to policy support and capacity building are directly related to the achievement of SDG7, albeit the portion attributed to SDG7 is unknown. Despite this, policy support and capacity building is included as SDG7-compliant unless stated.

Country classification

Countries are grouped into regions as per African Union categorisation, and by income group as per World Bank categorisation.

Currency and exchange rate

All amounts contained within this report are expressed in current prices.

All values are converted to euro based on the average annual exchange rate of the year a particular commitment or disbursement was made. Exchange rates for OECD DAC members was sourced from the OECD, while African currencies were obtained from the AfDB.

Annual exchange rates were calculated based on the average of the exchange rate for the first day of each month of that year.

Grant equivalent

Data on grant equivalents (the monetary value of a grant or loan which is ‘granted’ via the level of concessionality) was limited, and where available was obtained from the OECD DAC CRS for the years 2015 to 2018. For 2019 data was obtained for EU Institutions and EU Member States only. The grant element (the percentage of a grant or loan which is ‘granted’) was calculated on a project level basis, with an average then taken on all grant elements for a donor category.