Executive Summary

Overview

This report examines Africa's transition to sustainable energy from 1990 to 2021, focusing on:

 Trends in renewable energy consumption as a percentage of total final energy consumption

(REC (% of total energy consumption)).

 Key investment opportunities.

 Progress toward Sustainable Development Goal 7 (SDG 7): Affordable and clean energy.

 Economic impacts of renewable energy adoption.

 Regional cooperation frameworks for energy transitions.

The study uses data from the UN SDG Indicators Database and Gapminder, employing statistical and

machine learning techniques to derive insights. The findings provide actionable recommendations for

policymakers, investors, and stakeholders in Africa's energy sector.

Highlights

Varied Adoption Rates: Significant disparities exist in REC (% of total energy consumption) across

African countries, ranging from near 100% in some nations to below 10% in others.

Overall Declining Trend: Despite individual success stories, African countries' average REC (% of

total energy consumption) has declined from 1990 to 2020.

Economic Impact: A weak positive correlation between REC (% of total energy consumption) and

GDP growth (0.03) suggests that other factors, such as foreign direct investment (FDI), are critical

drivers of economic growth.

Regional Clusters: Countries are grouped into distinct clusters based on their REC (% of total energy

consumption) patterns and growth rates, indicating opportunities for targeted regional cooperation.

Botswana, Gabon, Comoros, and the Democratic Republic of Congo (DRC) have been identified as

potential leaders in renewable energy transitions.

Top Performers: Zimbabwe, Gabon, and Congo, Rep. showed the highest Compound Annual Growth

Rates (CAGR) in REC (% of total energy consumption) from 1990 to 2021.

Kenya's Performance: Kenya’s REC (% of total energy consumption) has stabilized between 65%

and 75%, indicating a potential for further investment.

Target Audience

This report provides strategic insights and recommendations to accelerate renewable energy adoption

across Africa. It is designed for policymakers, energy sector stakeholders, investors, development

partners, and companies looking to contribute to Africa's sustainable energy future.

3 
 
Table of Contents 
Executive Summary ................................................................................................................................ 2 
Overview ............................................................................................................................................. 2 
Highlights ............................................................................................................................................ 2 
Target Audience .................................................................................................................................. 2 
1 Introduction ..................................................................................................................................... 5 
Background ......................................................................................................................................... 5 
Objectives ........................................................................................................................................... 6 
Scope ................................................................................................................................................... 6 
2 Literature Review ............................................................................................................................ 7 
Relevant Research ............................................................................................................................... 7 
2.1.1 International Energy Agency (IEA), 2022 ...................................................................... 7 
2.1.2 World Bank ..................................................................................................................... 7 
2.1.3 Renewable Energy Policy Network for the 21st Century (REN21), 2021 ...................... 8 
Theoretical Framework ....................................................................................................................... 9 
2.1.4 Energy Transition Theory ............................................................................................... 9 
2.1.5 Resource-Based View of Economic Development ....................................................... 10 
Gaps in Knowledge ........................................................................................................................... 11 
3 Methodology ................................................................................................................................. 13 
Research Design................................................................................................................................ 13 
3.1.1 Data Sources and Metrics ............................................................................................. 13 
3.1.2 Data Processing ............................................................................................................. 14 
3.1.3 Analysis Techniques ..................................................................................................... 14 
3.1.4 Tools Used .................................................................................................................... 14 
4 Findings......................................................................................................................................... 15 
Investment Opportunity Identification .............................................................................................. 15 
Strategic Energy Transition Planning ............................................................................................... 17 
Sustainable Development Goal 7 Alignment .................................................................................... 19 
Economic Impact Assessment .......................................................................................................... 22 
Regional Cooperation Framework .................................................................................................... 24 
5 Case Study: Kenya ........................................................................................................................ 26 
6 Discussion ..................................................................................................................................... 28 
Analysis of Findings ......................................................................................................................... 28 
Comparison to Literature .................................................................................................................. 28 
Limitations ........................................................................................................................................ 28 
Summary of Key Findings ................................................................................................................ 28 

4 
 
Contribution to Knowledge ............................................................................................................... 29 
7 Recommendations ......................................................................................................................... 30 
Short-term Actions ............................................................................................................................ 30 
Long-term Strategies ......................................................................................................................... 30 
Investment Priorities ......................................................................................................................... 30 
Policy Suggestions ............................................................................................................................ 31 
Glossary of Technical Terms ................................................................................................................ 32 
References ............................................................................................................................................. 34 
Appendices ............................................................................................................................................ 36 
Appendix A: Summary of data tables used in the analysis. .............................................................. 36 
Appendix B: Charts of REC trends for each African country. ......................................................... 38 
Appendix C: REC CAGR across Countries 1990-2021 ................................................................... 48 
Appendix D: Box Plots Comparing SDG 7 Indicators between the Top-performing ...................... 49 
Countries and others in Africa. ......................................................................................................... 49 
Appendix E: Regression Results from OLS regression analysis ...................................................... 50

1 Introduction

Background

Africa’s energy landscape is evolving, with the continent facing the dual challenge of meeting growing

energy demands while transitioning to more sustainable sources.

The adoption of renewable energy across African countries has evolved significantly in the last two

decades, reflecting both the continent's vast potential and the challenges it faces.

As global awareness of climate change and the need for sustainable energy solutions has increased,

Africa has emerged as a focal point for renewable energy initiatives. Despite having abundant

resources—such as solar, wind, hydropower, and geothermal energy—many African nations still

grapple with energy poverty and underdeveloped infrastructure.

This report examines the progress made in renewable energy adoption across African countries from

1990 to 2021.

africa_progress_map

Figure 1: Map showing the progression of Renewable Energy Adoption in Africa

Objectives

The primary objective of this report is to analyze Africa’s renewable energy transition from 1990 to

2021. The analysis focuses on several key areas:

1. Investment Opportunity Identification

2. Strategic Energy Transition Planning

3. Sustainable Development Goal 7 Alignment

4. Economic Impact Assessment

5. Regional Cooperation Framework

Scope

This report covers renewable energy consumption (% of total energy consumption) trends in African

countries from 1990 to 2021, focusing on key economic and environmental indicators.

The scope includes a regional analysis, comparative country performance, and an assessment of energy

transition strategies.

‘

2 Literature Review

Relevant Research

Renewable energy adoption has been the subject of extensive research globally, with Africa emerging

as a key focus area due to its vast renewable energy potential. A few important studies and reports

provide insights into renewable energy trends, investment opportunities, and the socioeconomic impacts

of renewable energy transitions in Africa.

2.1.1 International Energy Agency (IEA), 2022

The International Energy Agency's (IEA) Africa Energy Outlook 2022 offers a critical examination

of the challenges and opportunities facing Africa's energy sector as it seeks to transition to sustainable

energy sources. This report emphasizes the continent's vast potential in renewable energy, particularly

solar energy in sub-Saharan Africa, due to its abundant sunlight (International Energy Agency [IEA],

2022).

Energy Demand and Access: According to the IEA, Africa currently has the world's lowest per capita

modern energy use. However, population and income growth are projected to drive a 33% increase in

energy demand by 2030 in a Sustainable Africa Scenario (IEA, 2022a).

The report highlights that over 600 million people in Africa still lack access to electricity, with nearly

1 billion lacking clean cooking facilities, making the goal of universal access by 2030 a critical focus

(IEA, 2022a).

Renewable Energy Potential: Africa possesses 60% of the world’s best solar resources yet accounts

for only 1% of installed solar PV capacity. The report projects solar photovoltaic (PV) to be the

continent's cheapest power source by 2030, potentially contributing over 80% of new generation

capacity. Solar, alongside other renewable sources such as wind, hydropower, and geothermal, could

significantly enhance energy access and sustainability (IEA, 2022b).

Investment and Infrastructure Needs: The IEA underscores the necessity for substantial investment—

over USD 190 billion annually from 2026 to 2030—in clean energy infrastructure. This financial

commitment is essential to build resilient systems capable of meeting rising demands, particularly in

sub-Saharan regions (IEA, 2022b). Furthermore, regional cooperation is identified as a key strategy to

enhance energy integration and resource distribution (IEA, 2022c).

Challenges and Opportunities: While financial limitations, political challenges, and fossil fuel

dependencies pose barriers, the IEA also highlights economic growth potential through renewable

energy investment. To navigate these challenges, African nations are encouraged to adopt clear

strategies supported by international funding (IEA, 2022d).

In summary, the Africa Energy Outlook 2022 provides an essential roadmap for Africa's energy

transition, underscoring the pivotal role of renewable energy in achieving sustainable development and

expanding energy access across the continent.

2.1.2 World Bank

The World Bank's report, Rethinking Power Sector Reform in the Developing World, authored by

Vivien Foster and Anshul Rana, provides an in-depth analysis of power sector reforms, particularly

within African countries.

This report utilizes case studies to explore how regulatory frameworks, financing mechanisms, and

governance influence the integration of renewable energy into national grids (Foster & Rana, 2020).

Key Findings:

Regulatory Frameworks: The report emphasizes that regulatory measures, while widely adopted, often

fall short of expectations due to challenges in implementation. Effective regulation is essential for

renewable energy integration and helps power sectors adapt to emerging technologies and market

dynamics (Foster & Rana, 2020).

Financing Challenges: Access to finance is identified as a persistent barrier to modernizing power

sectors. While private sector investment has increased generation capacity, distribution efficiency

remains low, underscoring the need for innovative financing tailored to each country's context (Foster

& Rana, 2020).

Governance Structures: Good governance emerges as a key determinant of reform success. Countries

with strong governance frameworks are more likely to achieve positive outcomes, including the

integration of renewable energy sources. The report highlights that governance reforms should be

prioritized, especially in environments where financial viability is still being developed (Foster & Rana,

2020).

Policy Implications

The report suggests that reform efforts should be tailored to each country's unique political and

economic conditions. Instead of a one-size-fits-all model, the study advocates for a pluralistic approach

that allows flexibility in reform pathways. This perspective aligns with the growing emphasis on

context-sensitive reforms in developing economies and recognizes the evolving energy landscape of the

21st century (Foster & Rana, 2020).

In conclusion, Rethinking Power Sector Reform in the Developing World provides valuable insights

into power sector reform's complexities, especially in African countries, and underscores the importance

of regulatory frameworks, financing solutions, and governance structures for integrating renewable

energy.

2.1.3 Renewable Energy Policy Network for the 21st Century (REN21), 2021

The Renewables 2021 Global Status Report by REN21 provides a comprehensive analysis of the global

renewable energy landscape, with a focus on Africa’s growth potential in this sector.

The report highlights several key findings that underscore the need for aggressive policy reform to

expedite the global transition to renewable energy across all sectors (REN21, 2021a).

Overview of Global Renewable Energy Progress

The report emphasizes that despite incremental progress, fossil fuels continue to dominate global energy

consumption, maintaining a share of approximately 80% over the last decade (REN21, 2021b).

In 2020, the world witnessed a notable increase in renewable energy capacity, despite the challenges

posed by the COVID-19 pandemic, which has significant implications for achieving net-zero emissions

and sustainable development goals (REN21, 2021c).

Focus on Africa

Africa is identified as having substantial renewable potential, particularly in solar, wind, and

hydropower. Kenya, South Africa, and Morocco are recognized as leaders in this energy transition,

driven largely by policy reforms and foreign investment (REN21, 2021d).

The report advocates for establishing supportive policies and frameworks to harness this potential

effectively, recommending that renewable energy be integrated as a key performance indicator in

national strategies to assess climate progress (REN21, 2021e).

Recommendations

REN21 urges governments to prioritize renewable energy in post-COVID-19 economic recovery

strategies, which includes setting renewable energy shares as essential indicators for climate progress

(REN21, 2021f).

The report also calls for enhanced international cooperation and investment in renewable technologies

to accelerate the transition from fossil fuels, especially in developing regions such as Africa (REN21,

2021g).

In summary, the Renewables 2021 Global Status Report is a vital resource for understanding the current

state of renewable energy worldwide. It emphasizes the need for immediate policy action and

investment to unlock Africa’s vast renewable energy potential.

Theoretical Framework

The renewable energy transition in Africa can be analyzed through the lens of the Energy Transition

Theory, which posits that economies must shift from high-carbon energy sources to renewable energy

to ensure sustainable growth. This shift involves various stages, starting with policy incentives,

moving toward market-driven growth, and ultimately resulting in widespread adoption.

The Resource-Based View (RBV) of economic development also highlights how Africa's natural

resources, such as solar and wind, can be leveraged for growth.

2.1.4 Energy Transition Theory

Energy Transition Theory underscores the necessity for supportive policies, market incentives, and

technological innovation to facilitate the large-scale adoption of renewable energy. This theory is

fundamental in understanding the shift from fossil fuels to sustainable energy sources, addressing both

environmental and economic challenges.

Key Components of Energy Transition Theory

Supportive Policies: Governmental policies are essential for a successful energy transition, including

regulations that promote renewable energy, financial incentives such as subsidies, and carbon pricing

mechanisms. For instance, Cherp et al. (2018) highlight the importance of government intervention in

stimulating renewable energy markets, asserting that significant transitions are unlikely without such

support (Cherp et al., 2018; Korea Energy Economics Institute, 2023).

Market Incentives: Market mechanisms aligned with sustainability goals encourage investments in

renewable technologies while gradually eliminating fossil fuel subsidies. The International Renewable

Energy Agency (IRENA) notes that substantial investments—estimated at USD 150 trillion by 2050—

are necessary to meet climate targets, requiring a redirection of funds from fossil fuels to renewable

energy sources (IRENA, 2023).

Technological Innovation: Technological advancement is essential for enhancing efficiency and

lowering the costs of renewable energy deployment. Research shows that innovations in technology can

reduce adoption barriers, making renewable energy sources more competitive against traditional energy

(United Nations Development Programme [UNDP], 2023; Berkhout, 2023).

Pathways for Energy Transition

Cherp et al. (2018) propose a meta-theoretical framework that integrates techno-economic, socio-

technical, and political perspectives to analyze national energy transitions. This approach emphasizes

the complex interactions among various stakeholders and highlights the need for multi-faceted policy

design (Cherp et al., 2018; Ministry of Energy Kenya, 2023).

Challenges and Barriers

Despite the potential benefits of an energy transition, significant challenges remain:

 Resistance from Established Interests: Incumbent industries may resist changes that threaten

their market position.

 Investment Gaps: Current investment levels are insufficient to meet climate goals.

 Policy Inconsistencies: While some regions advance renewable policies, others continue

supporting fossil fuels, undermining global efforts (IRENA, 2023; Berkhout, 2023).

Conclusion

The success of Energy Transition Theory depends on a coordinated approach involving policies and

market participation. Addressing structural barriers and ensuring socio-economic benefits are essential

for technologies, and achieving a sustainable energy future. As highlighted by IRENA, the urgency of

this transition cannot be overstated, and proactive measures are crucial for aligning current practices

with long-term sustainability goals (IRENA, 2023).

2.1.5 Resource-Based View of Economic Development

The Resource-Based View (RBV) is a strategic framework emphasizing the significance of a firm's

internal resources and capabilities as primary drivers of competitive advantage and economic

performance. This perspective is especially relevant in resource-rich regions like Africa, where

effectively managing and utilizing resources can foster sustainable economic growth (Oxford

Reference, 2021).

Key Concepts of the Resource-Based View

Heterogeneity of Resources: RBV asserts that firms possess diverse resources that are not uniformly

distributed among competitors. This heterogeneity allows firms to adopt strategies uniquely suited to

their resource mix, resulting in varying success levels in exploiting market opportunities (Oxford

Reference, 2021; Study.com, 2021).

VRIN Criteria: Resources that provide a sustainable competitive advantage must meet four criteria:

they should be Valuable, Rare, Imperfectly Imitable, and Non-substitutable (ScienceDirect, 2021).

For instance, a resource must allow a firm to exploit opportunities or mitigate threats, be difficult for

competitors to replicate, and have no substitutes capable of fulfilling the same function (Wikipedia,

2021).

Core Competencies: Firms should cultivate core competencies, unique strengths that differentiate

them from competitors. These competencies arise from combining tangible and intangible resources,

including technology, skilled labour, and organizational culture (University of Illinois, 2021).

Application of RBV in Africa's Economic Development

In Africa, RBV suggests that leveraging renewable resources like solar, wind, and geothermal energy

can be pivotal for economic growth. With an abundance of renewable resources, effective

management could significantly improve energy access and sustainability.

Importance of Renewable Resources

Sustainable Growth: Investment in renewable energy aligns with global sustainability trends,

reducing dependence on fossil fuels and enhancing energy security for African nations (Science

Direct, 2021).

Job Creation: Developing the renewable energy sector can generate jobs, support local economies

and improve livelihoods (Oxford Reference, 2021; University of Illinois, 2021).

Technological Innovation: Renewable energy technology promotes innovation, attracting foreign

investment and further driving economic development (University of Illinois, 2021).

Challenges and Considerations

Despite the potential for renewable resources, challenges such as infrastructure development,

investment needs, and policy frameworks must be addressed to enable effective deployment and

equitable resource distribution (Study.com, 2021; University of Illinois, 2021).

In conclusion, the Resource-Based View offers a valuable framework for understanding how Africa

can leverage its natural resources for economic development. By focusing on renewable energy and

sustainable practices, African nations can harness their unique resource endowments for growth, job

creation, and innovation.

Gaps in Knowledge

Despite a growing body of research on renewable energy, there are still notable gaps when it comes to

Africa's specific challenges. For instance, studies on the relationship between renewable energy

adoption and foreign direct investment (FDI) remain sparse. Additionally, the impact of renewable

energy on GDP growth in the African context is less understood compared to other regions, with few

empirical studies addressing long-term economic impacts of renewable energy transitions.

Moyo and Billon (2021) emphasize significant data gaps concerning the effectiveness of renewable

energy projects in Africa, especially regarding their economic impact. They argue for more

comprehensive studies to explore how renewable energy adoption intersects with economic policy

and regional development, which is crucial for understanding the broader implications of renewable

energy beyond environmental benefits, focusing instead on economic sustainability and growth.

Key Findings from Moyo and Billon (2021)

Data Gaps: Many African nations lack detailed data on the economic impacts of renewable energy

initiatives, hindering effective policy-making and project implementation (Moyo & Billon, 2021).

Call for Research: Moyo and Billon advocate for more in-depth studies on the connections between

renewable energy projects, economic policies, and regional development outcomes. Such research is

essential for understanding renewable energy's potential contributions to economic sustainability and

growth (Moyo & Billon, 2021).

Policy Implications: Without a thorough understanding of these dynamics, the authors suggest that

policymakers may struggle to design effective interventions that leverage renewable energy for

economic development.

Broader Context

Moyo and Billon’s discussion aligns with ongoing research on the socio-economic impacts of

renewable energy. For example, studies show that renewable energy can lead to job creation and

market stabilization, but project success often depends on supportive government policies and

technological innovation (Energies, 2023; FEPBL, 2022). Additionally, regional variations in

institutional capacity may influence renewable energy initiatives' success, suggesting that localized

strategies could be essential for optimizing outcomes (BioMed Central, 2021; MDPI, 2023).

In summary, Moyo and Billon’s work highlights the need for comprehensive data collection and

analysis to inform policies that effectively harness renewable energy for economic growth in Africa.

3 Methodology

Research Design

This report follows a quantitative research design, using historical data to analyze trends in REC (%

of total energy consumption) and economic indicators. The study employs exploratory data analysis

(EDA) to identify patterns and relationships in the data.

3.1.1 Data Sources and Metrics

The analysis drew from two primary data sources:

UN SDG Indicators Database

URL: https://unstats.un.org/sdgs/dataportal/database

Access Method: API

License: CC-BY

Key Metrics:

 Proportion of population with access to electricity (%) Proportion of population with primary

reliance on clean fuels and technology (%)

 Renewable energy share in the total final energy consumption (%)

 Energy intensity level of primary energy (Mega Joules per constant 2017 purchasing power

parity GDP)

 Installed renewable electricity-generating capacity (watts per capita)

 International financial flows to developing countries in support of clean energy research and

development and renewable energy production, including in hybrid systems (millions of

constant 2021 United States dollars)

Gapminder Database

URL: https://www.gapminder.org/data/

Access Method: CSV download

License: CC-BY

Key Metrics:

 Foreign Investment inflows (direct, net % of GDP)

 GDP per capita (Price and inflation-adjusted in PPP$2017)

 GDP

3.1.2 Data Processing

The data processing involved several steps to prepare the datasets for analysis:

Data Cleaning and Transformation:

 Transposing data to switch rows and columns

 Filtering for specific years (1990-2021)

 Removing unnecessary columns

 Filtering for African countries

 Handling missing data by deleting incomplete rows

 Renaming columns for clarity

 Converting figures from shorthand formats (M, B, K) to whole numbers

Data Enrichment:

 Calculating Compound Annual Growth Rate (CAGR) and Growth Rate for GDP and REC (%

of total energy consumption)

 Merging multiple datasets for a comprehensive view

3.1.3 Analysis Techniques

The analysis employed various statistical and machine learning techniques:

 Descriptive Statistics: To summarize and describe the basic features of the data.

 Time Series Analysis: To examine trends and patterns in REC (% of total energy

consumption) over time.

 Correlation Analysis: To measure the strength and direction of relationships between

variables.

 Regression Analysis: To model the relationship between REC (% of total energy

consumption) and economic indicators.

 Cluster Analysis: To group countries with similar renewable energy adoption patterns.

 T-tests: To compare differences between groups of countries.

3.1.4 Tools Used

The primary tool used for data analysis was Python in Jupyter Notebook.

Key libraries utilized include:

 Pandas: For data manipulation and analysis

 NumPy: For numerical computing

 Matplotlib and Seaborn: For data visualization

 Scikit-learn: For machine learning algorithms (clustering)

 Statsmodels: For statistical modelling and econometrics

4 Findings

Investment Opportunity Identification

Relationship between Investment and Renewable Energy

The analysis examined the relationship between foreign direct investment (FDI/GDP), renewable

energy consumption (REC), and renewable energy growth rates.

A weak positive correlation (0.01494) was found between the FDI to GDP ratio and the share of total

energy consumption from renewable sources (REC). This implies there is almost no linear

relationship between levels of foreign investment and the prevalence of renewable energy in the

energy mix.

The analysis did find a moderate positive correlation (0.6088) between REC and the compound

annual growth rate (CAGR) of renewable energy. This suggests that countries with higher growth

rates in renewable energy tend to have slightly higher shares of renewable energy consumption,

though the relationship is not extremely strong.

Conversely, a weak negative correlation (-0.0148) was observed between FDI to GDP ratios and the

CAGR of renewable energy. This indicates that higher levels of foreign investment are slightly

associated with lower growth rates in renewable energy, though again the relationship is not

particularly strong.

Overall, the data points to an inconsistent relationship between foreign investment, the current

renewable energy mix, and the pace of renewable energy growth across countries.

Other factors beyond just investment levels likely play a bigger role in shaping renewable energy

development.

Figure 2: Heat map showing correlation between REC, CAGR and FDI/GDP

Growth vs. Investment:

Figure 3: Average REC across African Countries from 1990-2021

The analysis revealed that most countries showed a decline in the share of total energy consumption

from renewable sources (REC) over the period from 1990 to 2021, despite varying levels of

investment attractiveness across those nations (see Appendix B for details).

risk-reward matrix

Figure 4: Risk-Reward Matrix showing the Investment Attractiveness based on REC Growth between 2016 and 2021

However, the data did identify some potential investment opportunities in regions that exhibited

positive growth rates in renewable energy coupled with above-average FDI to GDP ratios (see

Appendix C). The countries that emerged as having relatively low risk but higher reward investment

opportunities in this area were Cape Verde, Somalia, Gabon, and Liberia.

This suggests that while broader trends point to declining renewable energy shares, there are still

pockets of high growth and investment potential that warrant further exploration. The key is

identifying those markets that have both the momentum in renewable development as well as the

investment climate to effectively capitalize on it.

Strategic Energy Transition Planning

Overall Trend

Figure 5: CAGR of REC by Country (1990-2021)

The analysis revealed an overall downward trend in renewable energy consumption across the

countries studied. The average compound annual growth rate (CAGR) from 1990 to 2021 was -

0.91%, indicating a general decline in the share of total energy consumption coming from renewable

sources (REC) over this period.

Country Performance (Appendix C)

While the broader trend was negative, a few countries did manage to post positive growth rates in

renewable energy consumption:

 Zimbabwe had the highest CAGR at 0.82%

 Gabon saw a 0.50% CAGR

 Somalia achieved a 0.32% CAGR

These countries are well-positioned for future investments, particularly in solar and wind energy

sectors.

In contrast, several countries experienced significant declines in their renewable energy shares:

 Equatorial Guinea had the lowest CAGR at -8.61%

 Mauritius saw a -5.34% CAGR

 Seychelles declined at a rate of -2.88% CAGR

This wide variation in country-level performance highlights the need for tailored, strategic energy

transition planning to address the unique circumstances and resource profiles of each market.

Identifying both the high-growth and struggling renewable energy markets will be critical for

informing effective policy and investment decisions.

Cluster Analysis:

Figure 6: Cluster Analysis of Countries based on REC (1990-2021)

Countries were grouped into four clusters based on their renewable energy consumption (REC) as a

percentage of total energy consumption:

Cluster 3 (Yellow): This cluster includes countries like Algeria, Seychelles, and Libya, which have

extremely low renewable energy consumption, falling under the 0-20% range.

Cluster 2 (Orange): This cluster encompasses countries with significant reliance on renewable energy

sources, such as Angola, Ghana, and Kenya. Their renewable energy consumption rates fall between

60-75%.

Cluster 1 (Purple): Countries like Lesotho, South Sudan, and Botswana fall into this cluster, with

moderate renewable energy consumption levels ranging from 25-50%.

Cluster 0 (Dark Blue): This cluster is dominated by countries like the Democratic Republic of Congo,

Uganda, and Ethiopia, which have the highest levels of renewable energy consumption, ranging from

76-100%.

Key Observations

 The countries with the highest renewable energy consumption, close to 100%, are

predominantly located in East and Central Africa, such as the Democratic Republic of Congo,

Uganda, Burundi, Somalia, and Ethiopia.

 In contrast, the countries with the lowest renewable energy consumption, close to 0%, are

primarily located in North Africa, including Algeria, Libya, and Egypt. South Africa, as a

large economy, also falls into this low-performing category.

 The small island nation of Seychelles stands out as an outlier, with very low renewable

energy use compared to other small countries.

Overall, the data reveals a stark divide in renewable energy reliance across the African continent, with

certain regions and countries significantly outperforming others. Understanding these regional

patterns and identifying the drivers behind the high and low performers will be crucial for informing

strategic energy transition planning.

Sustainable Development Goal 7 Alignment

SDG 7 Indicator Correlations:

Figure 7: Box plot showing relationship between REC and SDG7 Indicators

Clean Energy vs. Renewable Energy Consumption (Turquoise):

The data suggests there is a positive correlation between the percentage of clean energy in a country's

energy mix and its overall renewable energy consumption (REC). Most data points cluster between 0-

80% for clean energy, and the spread indicates that countries with higher clean energy shares tend to

have higher renewable energy consumption levels.

Electricity Access vs. Renewable Energy Consumption (Orange)

The analysis revealed a wide spread of electricity access rates, ranging from 0-100%, across the

countries studied. However, there does not appear to be a clear, strong correlation between a country's

electricity access rate and its level of renewable energy consumption. Many countries show varying

REC levels despite having high rates of electricity access.

Energy Intensity vs. Renewable Energy Consumption (Red)

An interesting pattern emerged where higher energy intensity generally corresponds to lower

renewable energy consumption. This inverse relationship implies that more energy-intensive

economies might be less reliant on renewable sources. The data points are also more densely clustered

at lower energy intensity values.

Renewable Capacity vs. Renewable Energy Consumption (Blue)

The relationship between a country's renewable energy capacity and its actual renewable energy

consumption appears scattered and not clearly defined. The wide spread suggests that having

significant renewable energy capacity does not necessarily translate directly to high levels of

renewable energy consumption.

Renewable Energy Support vs. Renewable Energy Consumption (Green)

This particular analysis had a more limited dataset, and the relationship between renewable energy

support policies and renewable energy consumption is not clearly articulated in the visualization.

Key Observations

The relationships between these various indicators and renewable energy consumption are complex

and not always linear. The strongest positive correlation seems to be between clean energy adoption

and renewable energy consumption. Energy intensity, on the other hand, appears to have a more

inverse relationship with renewable energy use. Capacity alone does not guarantee high renewable

energy consumption, and electricity access does not solely determine renewable energy levels either.

Overall, these insights highlight the nuanced factors at play in driving renewable energy transition

across different countries.

Top Performing Countries:

Figure 8: Chart showing the Composite Score of the SDG7 Indicators in Renewable energy Adoption

Gabon and South Africa Lead with High Composite Scores

The analysis revealed that Gabon and South Africa emerged as the leading countries, with composite

scores above 0.6. This indicates they have made significant progress on the key indicators evaluated.

Top Performing Countries

Beyond Gabon and South Africa, the top performing countries were identified as:

1. Gabon Composite Score: 0.65 Progress Level: High

2. Zimbabwe Composite Score: 0.49 Progress Level: Moderate

3. Eswatini Composite Score: 0.47 Progress Level: Low

These countries demonstrated the highest overall composite scores, suggesting they have achieved

more advanced levels of development and performance across the various renewable energy metrics

analyzed.

The composite scores and assessed progress levels provide a holistic view of each country's standing

in the renewable energy transition. This insight can help inform strategic planning and investment

decisions aimed at accelerating the clean energy transformation across the region.

Table 1: Table of the Top 3 Performing Countries

showing their Composite Score and Progress

Performance Comparison:

The Top Performers Stand Out in Renewable Capacity and Clean Energy

Upon further examination, the data revealed that the top performing countries, as identified by their

high composite scores, showed significantly higher levels of renewable energy capacity and clean

energy percentages compared to the other countries analyzed (see Appendix D for details).

This suggests that the ability to develop and deploy substantial renewable energy generation

infrastructure has been a key driver of the top performers' progress in the renewable energy transition.

Differences in Electricity Access and Energy Intensity Less Pronounced

However, the analysis also found that the differences in electricity access rates and energy intensity

metrics were not statistically significant between the top performing countries and the rest of the

group.

This indicates that factors beyond just electrification levels and overall energy efficiency are playing a

key role in determining a country's success in transitioning to renewable energy sources. Other

variables, such as policy frameworks, investment climate, and resource endowments, may be more

influential in shaping renewable energy outcomes.

These insights underscore the multifaceted nature of the renewable energy transition. While building

out substantial renewable energy capacity appears to be a hallmark of the top performers, achieving

broader progress requires a holistic approach that addresses a range of interconnected economic,

infrastructural, and policy-related considerations.

Country

Composite

Score

Progress

Gabon

0.650817

18.5

Zimbabwe

0.494736

12.9

Eswatini

0.473948

5.3

Economic Impact Assessment

Renewable Energy and GDP Growth:

Figure 9: Regression Analysis of REC vs GDP Growth Rate

The analysis explored the relationship between a country's share of renewable energy consumption

(REC) as a percentage of total energy consumption and its GDP growth rate.

The data revealed a very weak positive correlation (0.03) between these two variables. This suggests

there is almost no linear relationship between a country's renewable energy consumption levels and its

economic growth rate.

To further examine this, a regression analysis was conducted. The results showed that REC (% of

total energy consumption) only explains a small portion, about 4.6%, of the variation observed in

GDP growth rates across the countries studied.

This indicates that factors beyond just renewable energy consumption are much more influential in

driving a country's economic growth. Other macroeconomic, policy, and resource-related variables

likely play a bigger role in shaping GDP growth rates.

The lack of a strong, direct correlation between renewable energy use and GDP growth underscores

the complexity of the relationship between a country's energy transition and its broader economic

performance. Policymakers and planners should consider a more holistic set of indicators when

assessing the potential economic impacts of renewable energy deployment.

FDI Impact:

In contrast, the data showed a more consistent positive relationship between a country's FDI to GDP

ratio and its GDP growth, especially at 1-year and 3-year lags (see Appendix E for details).

The correlation analysis revealed that FDI has a more significant and positive impact on GDP growth,

particularly in the shorter and medium-term timeframes, compared to the country's renewable energy

consumption levels.

These findings indicate that while renewable energy development is an important part of the energy

transition, it may not directly translate to measurable economic gains in the same way that foreign

direct investment does. Policymakers and planners should consider a more holistic set of economic

indicators beyond just renewable energy consumption when assessing a country's growth prospects

and development strategies.

Country-specific Analysis:

Figure 10: REC for the Top 5 Countries

The analysis identified the top 5 countries that have achieved significant growth in renewable energy

consumption:

1. Zimbabwe

2. Gabon

3. Republic of Congo

4. Eswatini

5. Liberia

These countries stand out for their impressive strides in expanding their renewable energy footprint

over the time period studied.

However, the patterns of renewable energy consumption (REC) as a percentage of total energy

consumption varied across these growth leaders:

 Gabon and Zimbabwe demonstrated general upward trends in their REC levels over time.

 The other three countries - Republic of Congo, Eswatini, and Liberia - exhibited more mixed

or fluctuating REC trends.

This suggests that the pathways to growing renewable energy can differ, with some countries seeing

more linear progress while others experience more volatility in their renewable energy shares.

Nonetheless, the identification of these top renewable energy growth performers provides valuable

insights. Understanding the unique drivers, policies, and market conditions that have enabled their

progress can inform strategies to replicate and scale similar renewable energy transitions in other parts

of the region.

Regional Cooperation Framework

Cluster Analysis for Regional Cooperation:

country_clusters

Figure 11: Hierarchical Country Clusters based on REC and the Growth Rate

The analysis grouped the countries into four distinct clusters based on their renewable energy

consumption (REC) levels and growth rates:

 Cluster 0 (Blue): Low Consumption, High Growth

This cluster includes countries like Botswana and South Africa, which have relatively low REC

percentages but are experiencing high growth rates in renewable energy.

 Cluster 1 (Purple): Low Consumption, Low Growth

Countries in this cluster, such as Angola and Ghana, have both low REC levels and low growth rates

in renewable energy.

 Cluster 2 (Orange): Moderate Consumption, Moderate Growth

The countries in this cluster, including Comoros and Lesotho, exhibit moderate levels of renewable

energy consumption and growth.

 Cluster 3 (Yellow): High Consumption, Low Growth

This cluster is dominated by countries like the Democratic Republic of the Congo and Ethiopia, which

have very high REC percentages but low growth rates in renewable energy.

This clustering reveals the diverse pathways countries are taking in their renewable energy transitions.

Some are starting from a low base but rapidly expanding their renewable energy footprint, while

others have already achieved high renewable energy shares but are struggling to sustain growth.

Understanding these distinct groupings can help inform tailored policy interventions and investment

strategies to accelerate the clean energy transformation across the region.

Potential Regional Leaders:

regional_leaders

Figure 12: Hierarchical Country Cluster Leaders based on REC and the Growth Rate

The cluster analysis revealed several potential regional leader country profiles within each grouping:

Botswana (Cluster 0): This country exhibits high growth rates in renewable energy despite having

only moderate GDP per capita levels. Its position in the "low consumption, high growth" cluster

suggests it is a rising renewable energy performer.

Gabon (Cluster 1): As a "high consumption, high growth" country, Gabon stands out with its

combination of substantial renewable energy use and rapid expansion of its renewable sector. Its high

GDP per capita also indicates strong economic resources to support the energy transition.

Comoros (Cluster 2): This "moderate consumption, negative growth" country has low GDP per capita,

pointing to potential challenges in sustaining renewable energy progress amid economic constraints.

Democratic Republic of the Congo (Cluster 3): Despite having very high renewable energy

consumption levels, the DRC is experiencing a slight negative growth rate. Its low GDP per capita

also implies limited resources to invest in further renewable energy development.

Overall, the cluster analysis has identified countries like Botswana, Gabon, Comoros, and the DRC as

potential leaders in renewable energy transitions across the region. Their varied characteristics in

terms of renewable energy metrics and economic performance make them interesting candidates for

regional cooperation frameworks aimed at accelerating the clean energy transformation.

5 Case Study: Kenya

Kenya ranks among the moderately high countries in REC (% of total energy consumption) (67.70%).

Figure 13: Kenya's REC 1990-2021

Kenya's renewable energy consumption (REC) as a percentage of total energy consumption has

followed an interesting trajectory. REC peaked at around 81% in the early 2000s, but has since

stabilized at a level of 65-75%.

This suggests that while Kenya has historically been a leader in renewable energy use, it has not been

able to sustain the same high levels in more recent years. The country's reliance on hydropower and

geothermal energy sources presents opportunities for further diversification into other renewable

technologies like solar and wind.

Figure 14: REC Rates for Kenya and Countries with the Highest and Lowest Rates in 2021

The analysis reveals stark contrasts in renewable energy consumption across African nations.

Kenya occupies a distinctive middle ground, with a 67.7% renewable energy consumption

(REC) that surpasses low-performing oil-dependent countries like Algeria and Libya, yet falls

short of the over 90% REC achieved by the Democratic Republic of the Congo, Somalia, and

Liberia.

These regional variations reflect complex interactions between natural resources, economic

structures, and policy environments. Countries with abundant hydropower or biomass

resources can more readily develop renewable energy infrastructure. Conversely, oil-

producing nations face economic and infrastructural barriers to transitioning away from fossil

fuel-based energy systems.

Kenya exemplifies the potential for strategic renewable energy development in a middle-

income African context. Its notable 67.7% REC results from targeted policies and strategic

investment in geothermal resources, positioning it as a promising model for sustainable

energy transformation.

However, caution is necessary when interpreting renewable energy statistics. High

percentages can be misleading, often inflated by traditional biomass use in rural areas rather

than representing advanced green technologies. This nuance is crucial for accurately

assessing a country's true renewable energy landscape and progress.

The data underscores the multifaceted challenges and opportunities in Africa's energy

transition, highlighting the need for tailored approaches that consider each nation's unique

environmental, economic, and technological contexts.

6 Discussion

Analysis of Findings

Varied Renewable Energy Adoption: There is a significant disparity in REC (% of total energy

consumption) across African countries. While some nations like Congo Dem. Rep., Uganda, and

Ethiopia consistently show high percentages (close to 100%), others such as Algeria, Libya, and

Egypt have very low adoption rates (below 20%).

Overall Declining Trend: Despite individual success stories, the average REC (% of total energy

consumption) across African countries shows a declining trend from 1990 to 2020, with a simple

average growth rate of -0.62%.

Investment and Renewable Energy Relationship: There is a weak positive correlation between

Foreign Direct Investment (FDI) as a percentage of GDP and REC (% of total energy consumption),

suggesting that increased investment doesn't necessarily translate directly to higher renewable energy

adoption.

SDG 7 Progress: Progress towards SDG 7 (Affordable and Clean Energy) varies widely across the

continent. Countries like Gabon and South Africa lead in composite scores for SDG 7 indicators,

while others like South Sudan lag significantly behind.

Economic Impact: The relationship between REC (% of total energy consumption) and GDP growth

is weak, indicating that other factors likely have more significant impacts on economic growth in

African countries.

Regional Clusters: African countries can be grouped into distinct clusters based on their REC (% of

total energy consumption) patterns and growth rates, suggesting opportunities for targeted regional

cooperation and knowledge sharing.

Comparison to Literature

The findings align with global research suggesting that renewable energy adoption alone does not

directly translate to economic growth. However, the potential for job creation, energy security, and

environmental benefits make renewable energy a critical component of sustainable development.

Limitations

This study is limited by the availability of data for certain African countries, particularly in the early

years of the study period. Additionally, the analysis focuses on aggregate measures of REC (% of

total energy consumption) and does not account for differences in energy mix or infrastructure

quality.

Summary of Key Findings

Africa’s renewable energy transition has progressed unevenly, with countries like Zimbabwe, Gabon,

and Eswatini demonstrating significant growth in REC (% of total energy consumption). Economic

growth remains weakly correlated with REC (% of total energy consumption), but FDI plays a critical

role in driving GDP growth.

Contribution to Knowledge

This report contributes to the understanding of Africa’s energy transition by identifying key

investment opportunities and highlighting the importance of regional cooperation. The findings also

provide insights into the role of renewable energy in achieving SDG 7.

7 Recommendations

Short-term Actions

a) Targeted Investment Promotion: Develop country-specific investment promotion strategies

focusing on countries with high growth potential in renewable energy, such as Zimbabwe,

Gabon, and Congo, Rep.

b) Tailored Investment Strategies: Develop country-specific investment strategies that account

for the unique renewable energy landscape and growth potential of each nation.

c) Policy Benchmarking: Conduct a comprehensive policy review, benchmarking successful

regulatory frameworks from top-performing countries like Gabon and Zimbabwe. Implement

best practices in countries lagging in renewable energy adoption.

d) Policy Framework Enhancement: Strengthen policy frameworks to support renewable

energy adoption, focusing on successful models from high-performing countries like Gabon

and Zimbabwe.

e) Capacity Building: Initiate capacity-building programs focusing on renewable energy

technology, project management, and policy implementation. Prioritize countries with high

potential but low current capacity.

f) Data Improvement: Enhance data collection and reporting mechanisms across African

countries to ensure more accurate and timely renewable energy statistics. This will support

better decision-making and progress tracking.

Long-term Strategies

a) Regional Integration: Develop long-term plans for regional power pools and cross-border

renewable energy projects, leveraging the strengths of different countries within identified

clusters.

b) Regional Cooperation: Establish and strengthen regional cooperation frameworks based on

identified clusters, facilitating knowledge sharing and cross-border renewable energy

initiatives.

c) Economic Integration: Develop strategies to better integrate renewable energy adoption with

broader economic development goals, recognizing the complex relationship between energy

transitions and economic growth.

d) Technology Transfer: Establish continent-wide programs for technology transfer and

knowledge sharing, focusing on adapting successful renewable energy technologies to local

contexts.

e) Education and Workforce Development: Invest in long-term education and training

programs to build a skilled workforce capable of supporting a growing renewable energy

sector across Africa.

f) Research and Innovation: Create a pan-African renewable energy research network to foster

innovation and develop technologies suited to Africa's unique energy challenges.

Investment Priorities

a) Grid Infrastructure: Prioritize investments in grid infrastructure to support increased

renewable energy integration, focusing on countries with high renewable potential but poor

distribution networks.

b) Off-grid and Mini-grid Solutions: Invest in off-grid and mini-grid renewable energy

solutions for remote and rural areas, particularly in countries with low electricity access rates.

c) Energy Storage: Support the development and deployment of energy storage technologies to

address the intermittency challenges of renewable energy sources.

d) Renewable Resource Mapping: Invest in comprehensive renewable resource mapping across

Africa to identify high-potential areas for solar, wind, geothermal, and hydroelectric projects.

Policy Suggestions

a) Harmonized Renewable Energy Targets: Encourage all African countries to set and regularly

update ambitious, yet achievable renewable energy targets aligned with the Paris Agreement

and SDG 7.

b) SDG 7 Alignment: Intensify efforts to align national energy strategies with SDG 7 targets,

particularly in countries lagging behind in clean energy access and renewable capacity.

c) Standardized Power Purchase Agreements (PPAs): Develop standardized PPAs for

renewable energy projects to reduce transaction costs and attract more private investment.

d) Green Finance Mechanisms: Establish national and regional green finance mechanisms to

channel funding towards renewable energy projects, including green bonds and climate

finance instruments.

e) Fossil Fuel Subsidy Reform: Gradually phase out fossil fuel subsidies while implementing

social protection measures to cushion the impact on vulnerable populations. Redirect savings

towards renewable energy development.

f) Local Content Policies: Implement balanced local content policies that promote the

development of domestic renewable energy industries while still attracting foreign investment

and expertise.

g) Cross-border Energy Trade: Develop policies and regulatory frameworks to facilitate cross-

border renewable energy trade, leveraging the strengths of different regions and promoting

energy security.

By implementing these recommendations, African countries can accelerate their transition to

sustainable energy, capitalize on investment opportunities, and make significant progress towards

achieving SDG 7 while fostering economic growth and regional cooperation.

Glossary of Technical Terms

API (Application Programming Interface): A set of protocols and tools for building software

applications, used here for accessing the UN SDG Indicators Database.

CAGR (Compound Annual Growth Rate): A measure of growth over multiple periods, calculated

as if the growth had happened steadily each year over a specified time.

Cluster Analysis: A statistical method used to group similar objects into clusters, applied here to

group countries with similar renewable energy adoption patterns.

Correlation Analysis: A statistical method used to measure the strength and direction of relationships

between variables.

Descriptive Statistics: Statistical methods used to summarize and describe the basic features of a

dataset.

EDA (Exploratory Data Analysis): An approach to analyzing data sets to summarize their main

characteristics, often with visual methods.

Energy Intensity: The amount of energy used to produce a unit of economic output, measured here in

mega joules per constant 2017 purchasing power parity GDP.

Energy Transition Model: A theoretical framework describing the shift from fossil fuels to

renewable energy sources as a pathway to sustainable development.

FDI (Foreign Direct Investment): An investment made by a firm or individual in one country into

business interests located in another country.

GDP (Gross Domestic Product): The total monetary or market value of all the finished goods and

services produced within a country's borders in a specific time.

Machine Learning: A field of artificial intelligence that uses statistical techniques to give computer

systems the ability to "learn" from data.

OLS (Ordinary Least Squares) Regression: A type of linear least squares method for estimating the

unknown parameters in a linear regression model.

PPP (Purchasing Power Parity): A measurement of prices in different countries that uses the prices

of specific goods to compare the absolute purchasing power of the countries' currencies.

Regression Analysis: A set of statistical processes for estimating the relationships between variables.

Renewable Energy: Energy from sources that are naturally replenishing but flow-limited, such as

biomass, hydro, geothermal, solar, and wind.

SDG (Sustainable Development Goal): A collection of 17 interlinked global goals designed to be a

"blueprint to achieve a better and more sustainable future for all", set up by the United Nations

General Assembly.

SDG 7: The seventh Sustainable Development Goal, which aims to "Ensure access to affordable,

reliable, sustainable and modern energy for all".

Time Series Analysis: A method of analyzing time series data to extract meaningful statistics and

other characteristics of the data.

T-test: A statistical test used to determine if there is a significant difference between the means of two

groups.

34 
 
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Appendices

Appendix A: Summary of data tables used in the analysis.

Appendix A

Table 1a.

Table 1b.

Table 2a.

Table 2b.

Table 3a.

Table 3b.

Appendix B: Charts of REC trends for each African country.

Appendix B

REC Trend 1: Algeria

REC Trend 2: Angola

REC Trend 3: Benin

REC Trend 4: Botswana

REC Trend 5: Burkina Faso

REC Trend 6: Burundi

REC Trend 7: Cameroon

REC Trend 8; Cape Verde

REC Trend 9: Central African Republic

REC Trend 10: Chad

REC Trend 11: Comoros

REC Trend 12: Congo, Dem. Rep.

REC Trend 13: Congo Rep.

REC Trend 14: Cote d'Ivoire

REC Trend 15: Djibouti

REC Trend 16: Egypt

REC Trend 17: Equatorial Guinea

REC Trend 18: Eritrea

REC Trend 19: Eswatini

REC Trend 20: Ethiopia

REC Trend 21: Gabon

REC Trend 22: Gambia

REC Trend 23: Ghana

REC Trend 24: Guinea

REC Trend 25: Guinea Bissau

REC Trend 26: Kenya

REC Trend 27: Lesotho

REC Trend 28: Liberia

REC Trend 29: Libya

REC Trend 30: Madagascar

REC Trend 31: Malawi

REC Trend 32: Mali

REC Trend 33: Mauritania

REC Trend 34: Mauritius

REC Trend 35: Morocco

REC Trend 36: Mozambique

REC Trend 37: Namibia

REC Trend 38: Niger

REC Trend 39: Nigeria

REC Trend 40: Rwanda

REC Trend 41: Sao Tome and Principe

REC Trend 42: Senegal

REC Trend 43: Seychelles

REC Trend 44: Sierra Leone

REC Trend 45: Somalia

REC Trend 46: South Africa

REC Trend 47: Sudan

REC Trend 48: Tanzania

REC Trend 49: Togo

REC Trend 50: Tunisia

REC Trend 51: Uganda

REC Trend 52: Zambia

REC Trend 53: Zimbabwe

Appendix C: REC CAGR across Countries 1990-2021

Appendix C

COUNTRY

CAGR(1990-2021)

Zimbabwe

0.008185

Gabon

0.004967

Somalia

0.003239

Congo, Rep.

0.002835

Cape Verde

0.002218

South Sudan

0.001846

Eswatini

0.001620

Congo, Dem. Rep.

0.001475

Liberia

0.001452

Libya

0.000000

Zambia

0.000000

Rwanda

-0.000283

Guinea-Bissau

-0.000440

Cameroon

-0.000963

Central African

Republic

-0.001047

Madagascar

-0.001359

Togo

-0.001509

Uganda

-0.001925

Ethiopia

-0.001933

Nigeria

-0.002876

Djibouti

-0.003441

Eritrea

-0.003477

Kenya

-0.003934

Burundi

-0.004172

Niger

-0.004449

Malawi

-0.005364

Tanzania

-0.005638

COUNTRY

CAGR(1990-2021)

Sudan

-0.005908

Mozambique

-0.006113

Burkina Faso

-0.006185

Mali

-0.006518

Sao Tome and

Principe

-0.007109

Tunisia

-0.007172

Cote d'Ivoire

-0.007544

Gambia

-0.007824

Chad

-0.007942

Sierra Leone

-0.008383

Guinea

-0.009392

Angola

-0.010027

Namibia

-0.011173

Egypt

-0.012468

Lesotho

-0.013989

Senegal

-0.014401

South Africa

-0.017182

Benin

-0.017329

Botswana

-0.018576

Comoros

-0.018714

Algeria

-0.022111

Morocco

-0.022968

Ghana

-0.023145

Mauritania

-0.024047

Seychelles

-0.028754

Mauritius

-0.053378

Equatorial Guinea

-0.086082

Appendix D: Box Plots Comparing SDG 7 Indicators between the Top-performing

Countries and others in Africa.

Appendix D

Box plot 1: REC of Top Performing Countries vs. others.

Box plot 2: Renewable Capacity of Top Performing

Countries vs. others.

Box plot 3: Clean Energy (%) of Top Performing

Countries vs. others.

Box plot 4: Electricity Access (%) of Top Performing

Countries vs. others.

Box plot 5: Energy Intensity of Top Performing

Countries vs. others.

Box plot 6: Renewable Support of Top Performing

Countries vs. others.

Appendix E: Regression Results from OLS regression analysis

Appendix E

Table 2: OLS Regression Analysis