The Relationship Between the Energy Market, Economic Growth, and Stock Market Performance: A Case Study of COMESA

Abstract

This study examines the relationship between energy use, economic growth, and stock market performance in the COMESA region. It utilizes yearly data from 1990 to 2022, sourced from the World Bank. It applies the Method of Moments Quantile Regression (MMQR), a statistical technique that captures how relationships vary across different levels of stock market development. The analysis examines how fossil fuels, renewable energy, and energy imports impact stock market size (market capitalization) at varying levels of performance. The results indicate that both the use of fossil fuels and renewable energy have a significant impact on stock markets, although the effects vary. Renewable energy has the most important positive effect in countries with smaller or weaker markets, suggesting it can help strengthen financial systems in developing economies. However, its impact becomes weaker in stronger markets, possibly due to the costs and challenges of switching to clean energy. On the other hand, economic growth does not always lead to stock market growth, likely due to structural problems in the region that prevent economic progress from boosting financial markets. This study shows how energy policy, economic growth, and market performance are closely linked. It calls for targeted policies to support the shift to renewable energy, manage short-term challenges, and build strong infrastructure to support long-term growth and financial stability. This research helps explain how energy and economic factors shape stock market outcomes in COMESA, offering helpful guidance for investors, researchers, and policymakers aiming for sustainable development.

1. Introduction

In the COMESA region, economic growth has been unstable and closely linked to fluctuations in the energy market as reflected by stock market performance. This instability threatens the region’s goals for sustainable development and economic resilience, making the challenges more severe and highlighting the need for collective action [1,2]. A key factor contributing to this vulnerability is the heavy reliance on fossil fuels such as oil, coal, and natural gas to meet the region’s energy demands. Traditional energy sources have long been the backbone of many COMESA member states, making their economies vulnerable to global fossil fuel price shocks. For instance, a rise in oil prices can lead to higher production costs and increased inflationary pressures, which in turn can destabilize economic growth [3]. The heavy reliance on fossil fuels also traps the COMESA region in a cycle of vulnerability, where economic stability is frequently disrupted by external market conditions beyond its control [4].

Another major challenge in the COMESA region is the lack of commitment to developing green energy. Despite global targets aimed at transitioning to renewable energy, progress toward cleaner power systems remains disappointing for most member countries. Ref. [5] identifies several reasons for this gap, including limited financing, insufficient technical expertise, and weak planning frameworks. Consequently, these countries miss out on low-carbon energy sources that are both more affordable and sustainable. This situation is made even worse by inefficiencies in energy policy, where efforts to promote green energy are often held back by resistance to reforms that could reduce economic dependence on fossil fuels.

Inconsistent and poorly designed energy policies lead to energy shortages, higher costs, and reduced industrial productivity, which in turn constrain economic growth [1]. This disrupts the supply of energy and also creates an element of unpredictability that slows down investments in the energy market [6]. This has multiple downstream effects. A lack of diversification increases economic volatility, as fossil fuels traded like any other commodity are subject to sharp price fluctuations. Sudden fuel price hikes driven by market dynamics can trigger inflation, reduce consumer spending, and ultimately lower economic output. Indeed, this economic instability and low level of development limited the countries in the region to poor economic foundations, thus further eroding their potential to develop consistently and sustainably [3].

Secondly, the limited situation in the energy market continues to affect the performance of stock markets directly. Fluctuations in energy prices also impact stock markets; rising fossil fuel costs increase operating expenses for businesses, which can, in turn, lead to a decline in stock prices [7]. On the other hand, the lack of development of the green energy sector has resulted in lost potential for the stock market surge through investment in renewable energy companies [8]. The stock exchange and energy market in COMESA are integrated and closely linked to economic growth. A common narrative is that of the stock markets serving as leading indicators of economic health, revealing investor sentiment and economic expectations. Research has shown that the volatility greatly influences investment performance in the stock market in energy prices. For instance, an increase in fossil fuel prices would affect stock prices through higher operating costs for firms as well as lower consumer discretionary spending [7].

Conversely, when modern innovations in green energy occur, they can lead to investor funds being allocated to firms in renewable power production and other sectors, which in effect drives green markets. Therefore, the development of an emerging green energy industry might offer both new areas of investment to the market and the development of a stronger and more diversified stock market in COMESA [8,9]. The interactive conditional correlation analysis reveals the very close relationship between the energy market, economic growth, and stock market performance in COMESA, which is driven by both global and regional events. Transitioning to more sustainable energy sources offers large trade and sustainable development opportunities, but it also means managing fossil energy dependencies and economic vulnerabilities.

This study contributes to knowledge by explaining the linkages among the energy market, economic growth, and stock market performance, specifically in COMESA. Combining fossil fuels and green energy, the study gives a complete view of the interaction between energy price risk and economic and stock market dynamics at a regional level. It is crucial for policymakers, investors, and scholars aiming to develop strategies that enhance economic resilience and promote sustainability. This study, in contrast, concentrates attention on the economic consequences of varying prices of fossil fuels in COMESA. The study also evidences the economic opportunities that could arise from a switch to renewable energy, evidencing the positive effect that green energy investments have on economic growth, employment, and reductions in the cost of energy. Equally important is research on the effects of energy market dynamics on the performance of stock markets in COMESA. This study examines how changing energy price trends will impact investor sentiment and stock prices, with a specific focus on energy-intensive industries.

2. Literature and Hypothesis Development

2.1. Energy Market

The energy market covers all the ranges of operations connected to manufacturing, transportation, and the use of energy. Crucially important for the global economy, this market shapes home energy use as well as industrial production. It comprises conventional fossil fuels, including natural gas, coal, and oil, as well as renewable energy sources, including solar, wind, and hydroelectric power. A sophisticated interaction of elements shapes the dynamics of the energy market: supply and demand, geopolitical impacts, technical developments, and legislative laws [10]. Though the energy sector is paramount for economic growth in the COMESA region, it is worth noting that this has created many significant possibilities and problems. These regions have primarily depended on fossil fuels, which makes it challenging due to their complexity caused by changes in the external market and price instability. For instance, they would face dire inflation consequences due to oil price fluctuation, the cost of production, and that of the economy in general. For any nation that solely depends on the importation of fossil fuels and lacks the idea of involvement in diversifying its energy source, price instability would then be inevitable [2]. The energy market covers a variety of sectors, spanning from the production sector, the transportation sector, and the consumption of energy sector. The energy market as a whole is crucial for the world economy because it factors in both household use and industrial usage for production. It includes conventional fossil fuel usage, including coal, oil, and gas, and also renewable energy usage, which includes wind, solar, and hydroelectric power. The changes in energy over the years have shaped the multifaceted relationship of supply and demand, the geopolitical impact of technological progress, and governing policies.

The COMESA region has focused on the demand for affordable and sustainable energy sources; therefore, the COMESA region is slowly transitioning to renewable energy. A green energy setup is possibly the best investment considered as a means of mitigating the adverse effects of fossil fuel use and, hence, encouraging economic resilience. These sources of energy, solar and wind, among other renewable energy sources, offer the opportunity for a consistent and predictable cost of energy. This, in turn, increases industrial development and advances energy security, through which they will be used [5]. By embracing the idea of renewable energy, the COMESA region would drastically reduce its carbon emissions, which would help it to have a sustainable environment, therefore complementing international initiatives to combat climate change [11,12] The energy market is mostly guided by the policy setting of the countries involved (Policy efficiency). This means incentives for investment, guarantees of regulatory stability, and support of research and development in fresh technologies. Effective energy policies can play a vital role in ensuring the change to renewable energy sources. On the other hand, policy inefficiencies and inconsistencies might impede this transition, hence causing energy scarcity, higher prices, and lower industrial output [1]. Coordinated policy advantages are needed in COMESA to solve these issues and provide an environment that is fit for the increase of renewable energy usage [6]. Currently, fossil fuel stocks are underperforming, as reflected in their disappointing market performance. In 2024, fossil fuel stocks grew by only 5.72%, compared to a 25.02% increase in the S&P 500 index. This poor performance suggests that there is a significant market shift, which makes investors move their focus to renewable energy.

The energy market is a multifaceted and growing sector that is crucial to the modern economic operation. It covers the creation, supply, and consumption of several types of energy sources, such as fossil fuels (coal, oil, and gas), nuclear energy, solar energy, geothermal energy, biomass energy, and wind/water energy. The energy market presents a confounding maze of supply and demand dynamics, regulation, technology development, and geopolitics.

Fossil fuels have long-held market penetration, particularly due to their high energy density (i.e., energy per mass unit) and their established fueling and transportation infrastructure. However, their environmental cost and finite supply have increasingly shifted attention to other forms of energy. The enormous impact of the volatility of fossil fuel prices driven by geopolitical tension, market speculation, and supply disruptions on economic stability and growth has been well documented [13]. This makes countries that rely heavily on fossil fuels more susceptible to the economic impacts of sharp price fluctuations and supply disruptions [14]. Moreover, such dependence can lead to a political economy where the state becomes overly reliant on the energy sector as a primary source of revenue. It’s worth noting that overdependence on fossil fuel has cost the COMESA region and made it vulnerable to external shocks, which invariably leads to fluctuation and price instability. Such dependency would eventually lead to inflationary pressure and economic volatility. Now, noting these challenges of over-dependency, the COMESA region is progressively switching to renewable energy sources. Funding green energy structures like solar and wind is deemed tactical to alleviate the bad effects of fossil fuel usage and also to strengthen economic reliance [15].

Recent research continues to emphasize the link between the energy market and stock market performance, particularly within the economies of developing countries [16,17]. In addition, recent theories linking financial development to economic growth now recognize that the relationship is not always straightforward. Instead, it can change at different stages of development, depending on certain economic conditions [18]. These findings also support the use of quantile-based methods like the Method of Moments Quantile Regression (MMQR), which are particularly effective for examining how the relationship between variables such as energy use and financial performance varies across countries with differing market strengths, rather than assuming a uniform effect across all cases [19].

On the other hand, there has been a significant rise in renewable energies, which have the edge of being sustainable, and the costs of renewable energy have been decreasing. With advancements in technology and economies of scale, renewable energy options are now becoming increasingly cost-competitive with traditional fossil fuels [12]. This migration to a clean energy transition includes global climate policies and greenhouse gas emission reductions. Government policies, subsidies, and incentives are used to influence the renewable energy markets to promote cleaner energy adoption [20]. Nevertheless, as Ref. [21] notes, transitioning to a renewable energy economy demands substantial economic and infrastructural transformations, which can disrupt short-term economic performance and affect market capitalization [22]. Recent studies found a positive relationship between energy consumption and stock market capitalization; i.e., research investigating the G20 nations established the statistical connection between renewable energy consumption, market capitalization, and carbon emission. The outcome of the research advises that an increase in renewable energy consumption can hugely impact the financial development and sustainable economic growth of that nation [23].

The energy market is also influenced by tariffs and prices that are set by regulatory frameworks put in place to control the production, distribution, and consumption of energy. These regulations may involve environmental law, emissions targets, or national incentive programs for renewable energy. Regulatory policies are pivotal in shaping the energy market by driving investment, technology innovation, and market competition [24]. Ref. [25] stated that strong policies are typical for a well-regulated market that enhances the effectiveness of markets based on sustainability and resilience, and that weak policies, as experience has shown, can create distortions and market inefficiencies. Furthermore, the world’s shift to the adoption of renewable energy is greatly influencing the stock market. Examining 25 nations using the VAR Vector Auto-Regression model has revealed an important change between renewable energy, stock market performance, and the carbon market. This investigation shows that renewable energy corporations are no longer closely tied to fossil fuel usage, indicating a shift in stakeholders’ attention toward more sustainable energy sources.

According to [16,17], their studies reveal significant uncertainty in the relationship between the energy market and stock market performance, particularly in developing economies. On the other hand, the theoretical models connecting financial development and economic growth have advanced to explain why the nonlinear effect was a better fit, specifically for the developing country perspective [18], This means that MMQR is the best method for our quantile analysis, as it helps capture the macro-financial relationship with our distribution rather than assuming a uniform effect [19].

From an African perspective, Ref. [26] examines the links between energy consumption, CO₂ emissions, and economic growth. Their study offers valuable insights for shaping effective policies in the COMESA region. These findings highlight the importance of concentrating on COMESA and employing modern, rigorous econometric methods in such analyses.

Technological innovation could help increase the efficiency and sustainability of energy use and production. For instance, advancements in battery storage technology are required for renewable energy to be feasible, which tackles issues of intermittency and reliability [27]. On the other hand, by making the use of renewable energy sources possible, the markets are being altered through the use of smart grid technologies and digitalization, which have the potential to integrate more efficient energy management and positive energy generation [16].

The 2024 energy regulation harmonization workshop and the AfDB’s 2021 grant have provided continued efforts to improve regional power integration and the regulatory alliance [28]. At the same time, recent programs by the COMESA region Monetary Institute show a growing policy attention to energy-related financial risks. Altogether, these developments underscore the practical urgency of examining energy finance linkages within the COMESA region.

Geopolitical factors also play a significant role in the energy market. Natural resources like energy tend to be geographically concentrated, so their use has a huge impact on how power is distributed among nation–states, regions, and other factors. For example, oil and gas reserves have been the basis of modern-day global trade and have always been geopolitically crucial in the Middle East [29]. Energy security, the ability to reliably access and afford an energy source, is a growing concern for all countries that import energy. Energy security is also enhanced with diversification of energy sources and encouraging domestic energy production, which can help reduce geopolitical risks [30].

2.2. Economic Growth

In economics, economic growth is the steady rise in an economy’s output of goods and services over time. Commonly expressed as the Gross Domestic Product (GDP) or Gross National Product (GNP), it is a major gauge of the general state of affairs and growth of a nation or region [31]. Investing in physical and human capital, technical know–how developments, effective resource allocation, and decent institutional frameworks and other features drives economic growth [32]. In the COMESA region, economic development is vital for mitigating poverty and inequality, raising the standard of living as a means of pulling many individuals out of poverty. However, the COMESA region has in the past suffered different hurdles that have limited its capacity for wide-ranging and steady economic development. The focal struggle is the strong dependency on conventional sectors like agriculture and extractive industries, which are very sensitive to outside shocks and changes in commodity prices [33]. Also, limited economic development in many COMESA nations includes poor infrastructure, limited access to finance, poor governance, and political unrest [34].

Aside from these difficulties, COMESA has great opportunities to improve its economy. One more idea is the economic diversification away from the conventional sectors in the direction of more vibrant and knowledge-intensive ones. Financing manufacturing, services, and technology firms can help generate employment, encourage creativity, and boost output [35]. The idea of regional integration, such as COMESA Free, can also boost trade, investment, and economic collaboration among member states, thereby opening fresh development prospects [36]. Additionally, the shift to a green economy offers COMESA fascinating opportunities for sustainable development in terms of the economy. Financing and participating in renewable energy, raising energy efficiency, and supporting environmental sustainability can benefit the COMESA region, solve urgent environmental issues, and make fresh economic projections [37]. The green economy offers potential benefits, including employment opportunities, improved energy security, and less overdependence on fossil fuels, hence promoting long-term economic resilience and prosperity [38].

Economic growth by the economist school of thought has been one of the primary concepts in economic study, which is defined as the persistent rise in the production of goods and services in any given economy over time. Generally, it is calculated via the Gross Domestic Product (GDP) growth rate, which signifies the value of all goods and services produced within a country. Economic growth is an important indicator of economic health and prosperity, signifying advancements in the standard of living, employment rates, and overall economic stability. Research confirms that governance quality is a key driver of economic growth. Ref. [39] suggest that a strong governmental framework in sub-Saharan Africa can have a substantial impact on both the rate of economic growth and patterns of government consumption. This highlights the long-term significance of institutional value in modeling the economic outcome.

Ref. [23] in their study of G20 countries reveal that there is a significant relationship between trade openness and economic growth, and also noted that a high tariff among G20 countries can affect the effect of economic growth among countries. Additionally, a study examining ASEAN nations from 2000 to 2022 suggests that the impact of trade openness may vary. While some scholars find that increased trade volume can positively influence economic growth, higher trade barriers between countries may hinder this effect and lead to more complex outcomes [40].

Some important factors of economic growth are usually identified, with the most important key factors being capital accumulation, growth in the size of the labor force, and technological innovation. Capital accumulation involves investments in physical assets, such as plants, machinery, infrastructure, and buildings, which increase productive capacity [41]. A larger pool of labor increases the availability of inputs for production, thus offering a stimulus to economic growth [31]. Technological innovation, with its ability to raise efficiency and productivity, is also a key driver of long-run economic growth. Technological improvements allow economies to produce more without increasing the amount of input, possibly making an economy grow even faster [42].

Educational attainment, workforce skills, and health are part of the human capital that affects economic growth and development. Expenditures and capital investments in education and health have significant long-term growth effects through enhancing productivity and labor efficiency, resulting in higher levels of economic output [32]. Economies that emphasize human capital development tend to achieve higher growth rates, and this growth is often sustainable. For example, countries with greater levels of educational attainment or more extensive healthcare systems often perform better in economic terms because they have a more productive workforce.

In addition, institutional factors that affect economic growth include governance quality, legal systems, and economic policies. Good governance and institutions serve as an enabling space for economic activities and boost investor confidence in the efficient allocation of resources [34]. Sound economic policies, whether fiscal or monetary, help maintain economic stability, encouraging investment and demand. On the other hand, poor institutions and governance can act like sand in the gears, slowing down economic growth due to uncertainty and inefficiencies.

International trade and openness are essential for economic growth. Countries that engage in international trade benefit from comparative advantages and economies of scale, accessing a broader range of goods, services, and technologies [43]. Openness to trade also encourages competition, innovation, and productivity growth. There is abundant empirical evidence suggesting that countries with more open trade regimes achieve more rapid growth than those with less liberal policies [44].

The role of natural resources is also a vital dimension of economic development. Resource-rich countries can capitalize on their natural endowments to develop their economies. However, the relationship between natural resources and economic growth is nuanced and conditional. Excessive focus on natural resource exports can lead to economic volatility, corruption, and slower long-term growth, a phenomenon known as the “resource curse” [45]. A 2020 study analyzing data from 95 countries over the period 1980–2017 found that oil abundance can hinder a nation’s economic growth. However, the research also revealed that trade openness can mitigate up to 25% of this negative impact [46]. Likewise, research by [17] takes a fresh look at the challenges faced by resource-rich countries, showing that the failure to invest resource income into long-term financial development is mostly due to corruption and poor governance. These weaknesses in leadership and institutions make it harder for countries to benefit from their natural wealth, ultimately slowing down sustainable economic growth.

Economic growth is often associated with improvements in living standards and poverty reduction. As economies grow, they generate more income and employment opportunities, leading to higher per capita income and better living conditions [11]. The distribution of economic growth benefits is crucial. Broad-based and equitable growth, or inclusive growth, is needed to sustain development and social stability [47].

2.3. Stock Market Performance

The performance of the stock market is the movement and behavior of stock prices within a specified financial market. It is a main gauge of investor attitude, the state of the economy, and company confidence. Stock markets are vital in allocating resources, enabling investment, and hence fostering economic growth since they let businesses raise funds by selling shares to investors [48]. Within COMESA, stock market performance represents the combined performance of listed firms across the region’s stock exchanges, including the Nairobi Securities Exchange (NSE), the Johannesburg Stock Exchange (JSE), and the Zimbabwe Stock Exchange (ZSE). Macroeconomic conditions, company performance, investor behavior, and world market trends all affect the way these exchanges turn out [49].

Economic development is one of the main factors controlling stock market performance. Strong economic foundations, like low inflation, steady interest rates, and strong GDP growth, usually match optimistic stock markets since they indicate rising company earnings and investment possibilities [50]. On the other hand, a recession or economic crisis could cause bearish stock markets marked by falling stock prices and investor pessimism [51]. Globally and locally, stock market performance in COMESA is likewise impacted. Events like changes in global commodity prices, investor mood, or geopolitical concerns can have knock-on impacts on stock markets inside the region, given the linked character of financial markets [52]. Furthermore, the incorporation of COMESA economies into international financial systems implies that local stock markets are vulnerable to instability and contamination from markets abroad [53].

Research by [54] underlines the complex connection between stock market performance and macroeconomic variables, highlighting the role of financial and trade openness and economic growth, especially in a developing economy, showing that there is a significant relationship between economic growth and trade openness and financial openness which in turn affect the performance of stocks. In conclusion, the incorporation of the global fiscal market suggests that the local stock would be vulnerable to global shock, highlighting the need for complex regulatory policy to maintain stakeholder confidence.

The performance of stock markets is significantly influenced by their regulatory environment and structural framework. Also, transparent, well-run stock markets with strong regulatory systems and investor protections usually draw more confidence and liquidity from the investors [55]. On the other hand, markets with poor governance, insufficient transparency rules, and regulatory uncertainty could find it difficult to keep investor confidence and liquidity, resulting in less-than-ideal stock market performance [56]. Furthermore, advancements in financial markets and technology have a significant impact on stock market performance. The rise of electronic trading platforms, AI-driven trading, and high-frequency trading has transformed how securities are bought and sold, influencing market liquidity, efficiency, and volatility [57]. Additionally, changes in financial derivatives such as options and future scan expose fresh risk and uncertainty to stock markets, therefore influencing investor behavior and market dynamics.

2.4. Market and Stock Market Performance

Several empirical studies have examined how stock market performance and the energy market interrelate, hence explaining the mechanics of this intricate interplay. Across several major economies, including the United States, the United Kingdom, Japan, and Germany, a notable study by [8] investigated the relationship between oil prices and stock market performance from 2004 to 2017. The study revealed evidence of an outstanding positive link between oil prices and stock market returns via a vector auto-regression (VAR) model, suggesting that upsurges in oil prices regularly follow a better stock market performance in the above-mentioned countries. The study did, however, also express changes in the intensity and direction of this association depending on changed periods and nations, suggesting the heterogeneous influence of oil prices on stock markets. Another study by [7], focusing on a Central American country, examined the relationship between stock market performance, fossil fuel prices, and renewable energy consumption. Acknowledging the nonlinear and dynamic nature of these relationships, the researchers analyzed data from 1980 to 2011 using a nonlinear Panel Smooth Transition Vector Error Correction Model (PSTVECM). The results indicated that there is a positive relationship between the use of renewable energy and stock market performance, hence suggesting that investments in renewable energy can drive economic activity and make stock market returns surge. The analysis also revealed evidence of asymmetric effects: rises in fossil fuel costs have a stronger negative effect on stock market performance than declines in prices. Ref. [58] argued that oil price shocks significantly affect stock market performance, though the effect changes depending on whether a country is importing oil or exporting. They employed the panel vector error correction model (PVECM). Their finding was that oil-importing countries tend to experience positive stock market responses to oil price increases, while oil-exporting countries showed a mix of strong or weak responses. This is due to differences in market development, economic structure, and oil revenue dependency.

Recent research has looked more closely at how energy use affects financial markets, especially in developing countries. For example, Ref. [59] shows that open economies are more likely to adopt renewable energy, while Ref. [60] find that renewable energy stocks hold up better during market crises. This research implies that green energy can help stabilize financial markets during turbulent times. However, the majority of this research focuses on huge economies, such as the BRICS, rather than smaller regional groups like COMESA. Furthermore, while we know that renewable energy can be reliable, we know nothing about how it relates to stock market growth and economic progress in locations with varying financial conditions. This study addresses that gap by employing a method that demonstrates how these linkages fluctuate based on a country’s level of financial growth within COMESA. This means that in some regions, when the economy grows (as measured by GDP), the stock market does not increase with it; instead, it may contract or stagnate. This unique pattern shows that these regions’ financial systems are plagued by long-standing issues. These issues could include inadequate financial policies that hinder market development, a reliance on public or foreign aid rather than private investment, and a lack of a strong equity market in which enterprises can generate capital by selling shares. This result contradicts the traditional financial theory, which expects market capitalization to expand with the economy. However, it is consistent with what other academics have seen in countries that lack sufficient capital and rely primarily on natural resources.

Ref. [61] analysis shows that the emphasis was on Africa’s sustainable development consequences of its renewable energy shift. The data source for the research was from 2000 to 2018 and examined how stock market performance, economic growth, and renewable energy investments are interrelated in African countries. The study also established, using panel data analytic approaches with fixed-effects and dynamic panel models, that investments in renewable energy were positively connected with regional stock market performance and economic growth. The results also show how well renewable energy might drive sustainable development and support African countries’ resistance to outside shocks. This empirical study regularly provides an understanding of the study in the connection between the energy market and stock market performance, emphasizing the need for renewable energy investments, oil price dynamics, and regional heterogeneity in establishing this connection. This research will provide policymakers, investors, and researchers with valuable insights to inform decision-making and policy development. Employing a rigorous econometric approach and analyzing data from multiple regions and periods, it offers diverse perspectives on the complex interactions between energy markets and financial markets.

2.5. Economic Growth and Stock Market Performance

A wide-ranging understanding of how significant economic variables interrelate has come from the empirical study of the linkage between economic development and stock market success. To investigate the long-term relationship between stock market development and economic growth, Ref. [62] conducted a notable study using data from 47 countries between 1976 and 1993. Their analysis showed that indicators of stock market development, such as market size and liquidity, were strongly associated with future economic growth rates, capital accumulation, and productivity improvements. This conclusion was drawn using cross-country regressions and various growth accounting models. The results showed that by helping to allocate capital and increase investment efficiency, well-functioning stock markets are quite important in fostering economic development. Beyond academic proof, recent regional policy initiatives suggest a strong and useful basis for this study. COMESA’s partnership with the World Bank via the 2024 ASCENT initiative shows the region’s planned commitment to expanding access to clean energy [63].

Another significant study by [64] broadened the focus to a 40-country sample spanning the years 1976 through 1998. To handle any problems where cause and effect might be mixed up, this study used panel data methods, more specifically, dynamic panel data estimations using the Generalized Method of Moments (GMM). The findings revealed a quite substantial, favorable correlation between economic development and stock market performance. The writers underlined that by offering financial services that better allocate resources, strengthen corporate governance, and encourage innovation, stock markets help to drive economic development. The study also underlined how significantly the legal and regulatory environment shapes the efficiency of stock markets in advancing development.

There is a symmetrical connection between the growing economy and the stock market development, making it comfortable for companies to increase capital and make an investment plan. Ref. [54] employed panel data analysis in a developing economy, and the findings established that financial openness and trade openness are important catalysts for economic growth. This outcome supports the assumption that an efficient stock market aids economic development by enabling well-organized capital allocation and promoting innovation. More recently, Ref. [65] examined the BRICS nations Brazil, Russia, India, China, and South Africa over the years 1988 through 2012. This work investigated the long-run and short-run relationships between stock market development and economic growth using a panel co-integration technique. The results revealed a two-way relationship between stock market development and economic growth over the long term. This means that stock market growth not only helps boost the economy, but economic growth also supports further expansion of the stock market, creating a continuous cycle of mutual reinforcement. The study found evidence of a one-way relationship, where economic growth leads to stock market development in the near future.

According to [66], who studied the relationship between financial developments, including stock markets, and economic growth in developing countries, their research used data from 1965 to 1997. They applied vector auto-regression (VAR) models for individual countries, along with time-series analysis. The findings highlighted the need for both stock market expansion and banking sector expansion for economic growth, but they also emphasized that in nations with more developed financial systems, the effect of stock market development was more evident. This research gave many new views on how the periods of financial development might affect the power of stock markets.

Altogether, this empirical examination has pinpointed the important role the stock market has played in advancing global economic development over the years and in countries. These studies have strongly revealed the positive connection between stock market performance and economic growth by making use of numerous methodological approaches, which include cross-country regressions, panel data analysis, co-integration analysis, and time-series models. The main need for the institutional and regulatory framework is to improve these benefits, as well as the fact that well-built stock markets help to increase capital allocation, develop company governance, and encourage innovation in promoting economic development. Policymakers must try to maximize the potential of stock markets to boost economic development, and investors trying to comprehend the wider economic effects of their investments rely on these results.

2.6. Theoretical Framework

Within the context of COMESA, the Financial Development Theory (FDT) is the most relevant paradigm for analyzing the interplay between the energy market, economic growth, and stock market performance. This view holds that by effectively allocating resources, mobilizing savings, enabling capital creation, and encouraging technological innovation, financial markets, including stock markets, play a vital part in economic development [67]. The theory provides a comprehensive framework for understanding the interaction between well-built financial institutions and other economic elements, such as energy markets, and their perspective on improving economic performance. According to the Financial Development Theory, by raising the usefulness of capital allocation, stock markets support economic development. The efficient operation of stock markets reduces capital costs for corporations, provides financiers with liquidity and expansion options, and facilitates risk sharing. This increases companies’ capability to fund fresh innovation and technology, thereby increasing production and economic growth [62]. The good connection between stock market development and economic performance over numerous countries and historical phases clearly shows the connection between stock markets and economic growth [64].

Additionally, agreeing to the theory, economic development is greatly molded by the energy market, particularly concerning the pricing and availability of energy supplies. Industrial manufacturing, transportation, and other economic activities all depend on energy. Accordingly, fluctuations in energy prices can have extensive significance on general economic stability, inflation, and manufacturing costs [13]. For example, while stable and reasonably priced energy prices can boost economic activity and growth, high oil prices can raise production costs, lower disposable incomes, and limit economic development. Connecting this to the performance of the stock market, the Financial Development Theory shows that stock prices and investor attitudes can be affected by the dynamics of the energy market. It lessens production costs and improves profitability prospects, resulting in more stable and predictable energy prices, which assist businesses to be more profitable, thereby affecting the stock values and stock market performance [68]. On the other hand, irregular energy prices could increase risk and create economic uncertainty, thereby affecting the performance of the stock markets. Industries that are highly dependent on the energy market specifically benefit from this connection since changes in energy costs directly impact investor confidence and business profits.

The Financial Development Theory continues to offer a strong basis for examining the relationship that exists among the financial market, energy market, and economic growth. Current empirical studies support the theory statement that the financial market comprising the stock market plays a significant role in helping to assemble savings, allocate resources efficiently, and encourage technological ideas. It’s worth noting that there is a positive effect of financial development and trade openness on economic growth, as proved by [59], which also supports the theoretical idea. Also, the merging of renewable energy into the financial market has been linked with improved economic performance. According to a study by [59], trade openness and renewable energy adoption show that the policies can promote trade openness to help improve the adoption of renewable energy, which in turn stimulates economic growth and influences the performance of the stock market.

Furthermore, the theory plays a significant role as regards changes in renewable energy sources; by proposing a more consistent and environmentally friendly energy source, investing in renewable energy sources brings about sustainable economic growth. This paradigm movement can help lower overdependence on irregular fossil fuel markets and reduce the economic risks associated with changes in the price of fuels [12]. New economic prospects, technological developments, and improved energy security are key factors that assist the stock market as businesses and countries make a full commitment to green energy. Recent research shows that studies support these theoretical links. For example, Ref. [7] found that investments in renewable energy significantly support stock market performance and economic growth in Central American countries. Similarly, Ref. [61] suggested that renewable energy investments in Africa are linked to stronger economic growth and improved stock market performance, highlighting the potential of green energy to drive sustainable development and financial market expansion.

This study covers the Financial Development Theory by using the energy mix (fossil fuel, renewable energy, and energy import) as a key driver of the stock market penetration in a constrained region. A prior study in the COMESA region, Ref. [1] employed a mean-based estimator in their study, which doesn’t factor in variation.

We employed MMQR because

• COMESA countries have a mix of income and energy dependence.
• There is a strong cross-sectional dependence.
• The policy interest is centered on low and leading markets.

The current study shows that the relationship between energy usage and carbon emission is connected to economic growth, thereby creating a good perception for the COMESA region in determining a good policy [26]. This has shown how important it is to focus on the COMESA region and support the adoption of modern and more reliable econometric methods in the study.

The MMQR was used along with Driscoll–Kraay robust errors [69], which aligns with our question: how do various energy components shape the market capitalization at various points, and at what point do we experience a structural break?

As shown in the Figure 1. below, the theoretical framework shows how energy market parts influence economic growth and stock market performance, as it is further strengthened by the Financial Development Theory.

As shown in Figure 1, this study’s theoretical framework is based on the Financial Development Theory, which critically explains how energy markets impact economic growth and stock market performance within the COMESA region. The use of fossil fuel, renewable energy consumption, and energy imports are key drivers of economic growth. On the other hand, industrial output and consumer spending affect stock markets (economic activity), helping stock market capitalization, which results in a symmetrical effect where financial development supports investment and innovation in the energy sector. This structuring validates our selection of the model and also supports our approach of adopting the MMQR and DKSE method of analysis to capture the effect across market outcomes.

3. Research Model

Driscoll–Kraay Standard Errors (DKSE) are used for serial correlation and heteroscedasticity problems [69]. This robust estimator confirms reliable inference in dynamic panel models by correcting standard errors and cross-sectional dependence. The Westerlund Co-integration Test (WCT) and the Cross-Sectional Augmented Dickey–Fuller (CADF) test are used to check the long-run relationships between variables [70]. These methods work well for heterogeneous panels and are consistent in recognizing co-integration under cross-sectional dependence. While the CADF test uses cross-sectional averages to account for dependency, the Westerlund test offers group-mean and panel-mean statistics. The Pesaran Panel Unit Root Test is used to verify that the panel data is stationary. The test considers cross-sectional dependence while extending the Augmented Dickey–Fuller framework to panel situations. The existence of a unit root is assumed by the null hypothesis.

The model of our research is stated thus,

Where: $\mathrm{M}\mathrm{C}\mathrm{A}\mathrm{P}={\beta }_0+{\beta }_{1}FSIL+{\beta }_{2}RECO+{\beta }_{3}EIMP+{\beta }_{4}GDPG+{\mu }_t$

3.1. Data and Sources

The annual data are obtained from the World Bank Development Indicators from 1990 to 2022. The explanatory variable in this study includes the energy market as measured in terms of energy prices, fossil fuel consumption, energy consumption, and GDP growth. The dependent variable of the study is stock market performance measured in terms of stock market capitalization. The study employs annual data from 1990 to 2022 obtained from the World Bank Development Indicators, aiming at several key variables. The dependent variable is Market Capitalization (MCAP), which denotes the total market value of open-traded companies’ shares within the COMESA region’s stock exchanges. This measure is a crucial indicator of the general size and strength of the stock market, showing investor confidence and the economic events of the region. Between the dependent variables, Fossil Energy Consumption (FSIL) measures the aggregate usage of energy derived from fossil fuels such as coal, oil, and natural gas within the COMESA nations.

This study employs a purposeful sample technique, which allows us to select COMESA member countries with the most consistent and available data spanning from 1990 to 2022. With this method employed, it confirms the relevance to the question and the robustness of the region assessment. The World Bank development indicator was employed due to the credibility and reliability of the data source. Then, to boost validity, second-generation panel econometrics techniques were employed in our analysis, which account for cross-sectional dependence, non-stationarity, and heterogeneity, to confirm that the model will precisely capture the dynamics and connections among the countries. The relationship between the research question and the analytical model is rooted in the research on energy market variables and how economic growth affects the stock market performance. This was carried out through quantile estimation and robust correction.

This variable is vital for understanding the dependency on traditional energy sources and their impact on the COMESA region’s economic stability. Likewise, Renewable Energy Consumption (RECO) denotes the total usage of energy from renewable sources, including solar, wind, hydroelectric, and biomass. This variable illustrates the extent to which COMESA countries are shifting towards sustainable and environmentally friendly energy sources. Another significant explanatory variable is Energy Imports (EIMP), which measures the total amount of energy imported by the COMESA nations. This variable, expressed as a proportion of total energy consumption, reflects the region’s reliance on external sources for its energy needs. A high dependence on energy imports signifies weaknesses in external market settings and geopolitical factors. Finally, Gross Domestic Product Growth (GDPG) signifies the annual percentage growth rate of the Gross Domestic Product in the COMESA region. This variable works as an indicator of the total economic performance and growth, giving insights into the economic resilience and development of the member countries. The study covers the member countries of the Common Market for Eastern and Southern Africa (COMESA), which include Burundi, Comoros, the Democratic Republic of Congo, Djibouti, Egypt, Eritrea, Eswatini, Ethiopia, Kenya, Libya, Madagascar, Malawi, Mauritius, Rwanda, Seychelles, Somalia, Sudan, Tunisia, Uganda, Zambia, and Zimbabwe.

3.2. Method

In the examination of the panel of this research, we would make use of the Method of Moments Quantile Regression (MMQR) model, as proposed by [71], to examine the relationship among energy market variables, economic growth, and stock market performance in the COMESA region. This study inspects the connections between economic growth, natural resource rents, energy consumption, and environmental sustainability in the COMESA region. The analysis utilizes second-generation econometric models to account for the relationships among these variables, including cross-sectional dependence, heterogeneity, and non-stationarity in the panel data. Cross-sectional dependence occurs as a result of common economic, environmental, and structural attributes among nations. The Pesaran Panel Unit Root Test is used to verify that the panel data is stationary. This test considers cross-sectional dependence while extending the Augmented Dickey–Fuller framework to panel situations. The existence of a unit root is assumed by the null hypothesis. Global energy price variations and regional trade agreements might concurrently affect several countries within the region. The following tests are employed to confirm the presence of cross-dependency. Pesaran and Yamagata’s Heterogeneity Slope Test is used to evaluate heterogeneity among nations. Slope coefficient consistency across panel units is tested, and significant results show that diverse models are required. We chose the 5th, 25th, 50th, 75th, and 95th quantiles to represent a wide range of stock market situations, from low (underperforming markets) to high (outperforming markets). This spread enables us to see how energy consumption and economic growth affect financial performance not only on average, but also at different levels of market capitalization. This helps in the COMESA region because it helps capture data clearly, where we have a wide range of market structures among member countries. This is also consistent with [71], where they allow different quantiles to compare and interpret data across their study.

The MMQR model is estimated using panel data from 1990 to 2022 for COMESA member states. The data, obtained from the World Bank Development Indicators, include:

Dependent Variable:

Market Capitalization (MCAP) represents the total market value of publicly traded companies in COMESA.

Independent Variables:

GDP Growth (GDPG)

Fossil Energy Consumption (FSIL)

Renewable Energy Consumption (RECO), and

Energy Imports (EIMP)

Where: $\mathrm{M}\mathrm{C}\mathrm{A}\mathrm{P}={\beta }_0+{\beta }_{1}FSIL+{\beta }_{2}RECO+{\beta }_{3}EIMP+{\beta }_{4}GDPG+{\mu }_t$

Also, $\beta$ presents the parameter coefficient, and $\mu$ shows the stochastic error term.

The data collected was from the World Bank datasets (

Table 1. Summary of variables.

Variable	Measurement	Source
Market Capitalization (MCAP)	GCF % of GDP	WDI
GDP Growth (GDPG)	% diff of GDP in 2 years	WDI
Fossil Energy consumption (FSIL)	% diff in terawatt usage in a 2-year gap	WDI
Renewable Energy Consumption (RECO)	% of GDP	WDI
Energy Import (EIMP)	% of GDP	WDI

Source: Author’s own illustration.

); hence, we use the World Bank Development Indicators (WDI).

4. Data Analysis

The results of the cross-sectional dependency tests (

Table 2. Cross-sectional dependency tests.

Test	Statistic	p-Value
Pesaran	15.51 ***	0.00
Fisher	50.34 **	0.03
	Statistics
Frees	4.57 ***
Critical values from Frees’ Q distribution	α = 10%: 0.41
	α = 5%: 0.57
	α = 1%: 0.90

Note: (***), and (**) indicate that the estimated parameters are significant at the 1%, 5% significance level, respectively.

) provide strong evidence of cross-sectional dependence among the variables in the dataset. This finding implies that economic shocks or fluctuations affecting one country in the COMESA region are likely to influence other countries within the region, indicating interconnections across the panel data.

The Pesaran test for cross-sectional dependence yields a statistic of 15.51, with a p-value of 0.00. This result, significant at the 1% level (***), strongly supports the presence of cross-sectional dependence, indicating that the variables are not independently distributed across countries. Similarly, the Fisher test, with a statistic of 50.34 and a p-value of 0.03, is significant at the 5% level (**). This additional evidence confirms the findings from the Pesaran test and reinforces the conclusion of cross-sectional dependencies in the data. The Frees test statistic of 4.57 also exceeds the critical values at all levels of significance provided by Frees’ Q distribution (0.41 at 10%, 0.57 at 5%, and 0.90 at 1%), establishing significance at the 1% level (***). This result further supports the conclusion of significant cross-sectional dependence, with strong evidence that countries within the panel are economically interlinked.

The results of the Pesaran Panel Unit Root Test (

Table 3. Pesaran Panel Unit Root Test.

Variable	Statistic
MCAP	−3.82 ***
GDPG	−1.15
FSIL	−0.86
RECO	−1.38
EIMP	−3.83 ***
∆GDPG	−2.23 **
∆FSIL	−2.63 ***
∆RECO	−2.57 ***
Critical values	α = 10%: −2.05
	α = 5%: −2.16
	α = 1%: −2.36

Note: (***), and (**) indicates that the estimated parameters are significant at the 1%, 5% significance level, respectively.

) indicate that certain variables in the dataset are stationary, while others are non-stationary at levels but become stationary after the first difference. This is evident from the test statistics compared to the critical values at the 10%, 5%, and 1% significance levels. For the variable Market Capitalization (MCAP), the test statistic of −3.82 is highly significant at the 1% level (***), which suggests that the MCAP is stationary in levels. Similarly, Energy Import (EIMP) shows a test statistic of −3.83, also significant at the 1% level (***), indicating that EIMP is stationary at levels as well. However, other variables, including the GDP Growth (GDPG), Fossil Energy Consumption (FSIL), and Renewable Energy Consumption (RECO), show test statistics of −1.15, −0.86, and −1.38, respectively, which are all higher than the critical values for stationarity at the usual significance levels. This result indicates that these variables are non-stationary in their original form and may require differencing to become stationary. After the first difference, these variables show significant test statistics: the first difference of GDP Growth (∆GDPG) has a test statistic of −2.23, significant at the 5% level (**), while the first differences of the Fossil Energy Consumption (∆FSIL) and Renewable Energy Consumption (∆RECO) have test statistics of −2.63 and −2.57, respectively, both significant at the 1% level (*). These results confirm that differencing has successfully rendered these variables stationary.

The study proceeds to use the Heterogeneity Slope Test to assess whether there are significant differences in the slopes of the variables across cross-sectional units in the panel data. This test is vital as it helps us to find out the connection between the variables in our research, to check how consistent they are across entities, or how they differ, which is very important when making a decision or generalizing our results. In

Table 4. Heterogeneity Slope Test.

Δ	p-Value	Δ Adj	p-Value
8.03 ***	0.00	11.21 ***	0.00

Note: (***), indicates that the estimated parameters are significant at the 1% significance level.

, in the above table, our results display that the test statistics for both Δ (first difference) and Δ Adj (adjusted first difference) are highly significant, with a p-value of 0.00 for both. The Δ value has a test statistic of 8.03, and the Δ Adj value has a test statistic of 11.21. Both test statistics are statistically significant at the 1% significance level (***), which shows strong evidence against our null hypothesis of homogeneity. This simply means that the slope coefficients for the variables differ significantly across the cross-sectional units in the panel, which suggests that the connections between the independent variables and the dependent variable are not the same for the entities in the sample. The significant outcome from both Δ and Δ Adj further supports the presence of heterogeneity in the model, which supports the notion that the homogeneity of slopes does not hold in this study. Therefore, heterogeneity should be reflected in the model specification, as it shows that the individual characteristics or differences across the entities are necessary for accurate estimation and inference. It may also suggest the need to apply models that account for this heterogeneity, such as fixed effects or random effects models, depending on the nature of the data and the underlying assumptions.

Next, the study determines whether there is a long-run equilibrium relationship between the variables in the model. Co-integration tests are particularly important in time-series and panel data analysis because they help to identify whether the variables move together over time, indicating a stable long-term relationship. In this case, the use of various co-integration tests provides a comprehensive approach to confirm the presence of such relationships between the energy market, economic growth, and stock market performance in the context of COMESA. The results from all of the tests in

Table 5. Co-integration tests.

Test	Statistic	p-Value
Westerlund	18.55 ***	0.00
Modified Dickey–Fuller	−17.99 ***	0.00
Dickey–Fuller	−7.38 ***	0.00
Augmented Dickey–Fuller	−4.56 ***	0.00
Unadjusted modified Dickey–Fuller	−3.65 ***	0.00
Unadjusted Dickey–Fuller	−7.38 ***	0.00

Note: (***) indicates that the estimated parameters are significant at the 1% significance level.

indicate statistically significant evidence of co-integration, as the p-values for each of the tests are 0.00, which is well below the 1% significance level (***). This implies that the null hypothesis of no co-integration is rejected in favor of the alternative hypothesis that the variables are co-integrated, meaning they share a common long-term trend. The Westerlund test statistic is 18.55, and the modified Dickey–Fuller test statistic is −17.99, both of which are highly significant, indicating strong evidence of co-integration. Similarly, the traditional Dickey–Fuller test and the Augmented Dickey–Fuller test have statistics of −7.38 and −4.56, respectively, which are also significant at the 1% level, confirming the robustness of the results. Furthermore, it is worth noting that our unadjusted modified Dickey–Fuller and unadjusted Dickey–Fuller tests have indicators of −3.65 and −7.38, respectively, with matching p-values of 0.00, which additionally support the notion that co-integration exists among the variables. The importance of these various tests is to strengthen the idea that, notwithstanding the potential short-term fluctuations, there is an unwavering long-run relationship between the energy market, economic growth, and stock market performance in the COMESA region.

Table 6. MMQR model (dependent variable: MCAP).

Quantile	GDPG	FSIL	RECO	EIMP	Intercept
5	−0.44	2.89 **	3.86 ***	1.08 ***	376.82 ***
25	−0.71	4.31 ***	5.26 ***	0.91 ***	485.50 ***
50	−1.02	5.99 ***	6.91 ***	0.70 ***	613.61 ***
75	−2.36	13.17 **	13.99 **	−0.17	762.76 **
95	−4.15	22.80 **	23.48 *	−1.33	898.67 *

Note: (***), (**), and (*) indicate that the estimated parameters are significant at the 1%, 5%, and 10% significance levels, respectively.

shows the effects of the MMQR model, which examines the relationship between market capitalization (MCAP) and some other dependent variables: GDP growth (GDPG), fossil energy consumption (FSIL), renewable energy consumption (RECO), and energy imports (EIMP). We will make use of the MMQR model, which will evaluate the coefficients at different quantiles (5%, 25%, 50%, 75%, and 95%). This will help us understand how the connection between our dependent variable, MCAP, and other of our independent variables varies at different points of distribution. This method allows us to identify the impact of the variables at the lower, middle, and upper tails of the MCAP distribution, giving us the analog to understand the fundamental dynamics compared to conventional OLS regressions. At the 5th quantile, GDPG has a negative and statistically significant coefficient of −0.44, which suggests that higher economic growth is linked with lower market capitalization at the lower end of the distribution. The result is different from the general expectation that economic growth is positively associated with market performance [53,66]. FSIL, RECO, and EIMP show positive and statistically significant coefficients of 2.89, 3.86, and 1.08, respectively, which show that these energy-related factors have a positive effect on market capitalization at this quantile. The value of intercept at the 5th quantile is 376.82, which is highly significant, showing a positive baseline level of market capitalization when all variables are set to zero, which primarily associates with the notion that energy markets and related organizations play a vital role in the economy and market performance [7,20].

At the 25th quantile, GDPG suggests a slightly stronger negative effect on MCAP at −0.71, while FSIL, RECO, and EIMP uphold positive coefficients and go on to be statistically significant at 4.31, 5.26, and 0.91, respectively. This persistent positive effect of energy variables on market capitalization matches with the study underlining the role of energy consumption in driving economic growth and market performance, particularly in developing nations [7,57]. The intercept rises to 485.50, which signifies a higher baseline market capitalization at this quantile compared to the 5th quantile. At the 50th quantile, the negative connection between GDPG and MCAP becomes more evident at −1.02, while there is a positive effect of FSIL at 5.99, RECO at 6.91, and EIMP at 0.70, which shows as significant. The intercept increased to 613.61, indicating that higher market capitalization is associated with a larger baseline value at the median of the market capitalization (MCAP) distribution. These outcomes are in line with findings in the literature that propose that energy markets, particularly renewable energy, can positively influence financial markets [20,46].

At the 75th quantile, GDPG had a further negative effect at −2.36, and the coefficients for FSIL (13.17) and RECO (13.99) are particularly greater than that of previous quantiles, although the coefficient for EIMP is negative at −0.17. This change in the connection between EIMP and MCAP at the upper middle quantile proposes a diminishing positive effect of energy imports on market capitalization. The outcome will be explained by the fact that higher levels of energy imports might signify economic dependence on foreign energy sources, which could dampen market confidence [29]. The intercept value rises to 762.76, showing even higher baseline market capitalization at the 75th quantile. At the 95th quantile, GDPG continues to employ its negative effect of −4.15, and FSIL (22.80) and RECO (23.48) are equally highly significant with great positive coefficients. On the other hand, the coefficient for EIMP turns out to be negative at −1.33, showing a possibly negative impact of energy imports on MCAP at the top levels of market capitalization. This study reveals concerns over the sustainability of the dependence on energy imports, which can worsen economic weaknesses, as argued by [30]. The intercept further increases to 898.67, indicating the highest baseline level of market capitalization in the upper quantile.

These results align with the existing literature on the relationship between energy consumption and economic variables, particularly in the context of energy and economic growth. For example, Ref. [7] found that renewable energy consumption positively affects economic performance, which is similar to the significant positive coefficients observed for RECO in this study. Similarly, Ref. [64], emphasized the role of financial markets, which aligns with the positive relationships between energy factors (FSIL, RECO, and EIMP) and MCAP in this study. Additionally, the results are consistent with the findings of [61], who noted the growing role of energy investments, particularly in renewable energy, in driving economic outcomes and market performance in Africa. The consistently positive relationship between RECO and MCAP across quantiles further supports the view that a transition toward renewable energy may enhance economic growth and financial market development. However, the negative relationship between GDPG and MCAP at higher quantities of MCAP suggests that in more developed markets, the effect of economic growth on market capitalization may diminish, possibly due to diminishing returns at higher levels of development. This aligns with findings from studies such as [41], who suggested that the relationship between growth and market performance could weaken as economies reach higher stages of development.

The results from the Driscoll–Kraay Standard Errors (DKSE) method in

Table 7. DKSE (Driscoll Kraay Standard Errors) Method (Dependent Variable: MCAP).

	Coefficient	p-Value
GDPG	−1.43	0.51
FSIL	8.19 ***	0.00
RECO	9.08 ***	0.00
EIMP	0.44 *	0.09
Intercept	782.14 ***	0.00

Note: (***), and (*) indicate that the estimated parameters are significant at the 1% and 10% significance level, respectively.

provide estimates of the relationship between market capitalization (MCAP) and various explanatory variables: GDP growth (GDPG), fossil energy consumption (FSIL), renewable energy consumption (RECO), and energy imports (EIMP). The DKSE method is particularly valuable for accounting for potential heteroscedasticity and auto-correlation in the panel data, making it more robust for inference when the standard assumptions of panel regression models may not hold [69] Starting with the coefficient for GDPG, which is negative (−1.43) and statistically insignificant (p-value = 0.51), the lack of significance suggests that economic growth, at least in the context of COMESA, does not have a clear or immediate effect on market capitalization when using the DKSE method.

This result contrasts with the theoretical expectation that higher economic growth should be linked to greater market capitalization, as proposed by [32,66], who found that economic growth generally has a positive effect on financial markets. The insignificance of GDP growth in this case may offer important insights into the growth dynamics within the COMESA region suggesting that, despite experiencing substantial economic growth, these countries may still face structural barriers that prevent them from effectively translating that growth into financial market expansion.

The coefficients for FSIL and RECO are positive and highly significant (p-values of 0.00), which indicates that energy consumption, especially fossil fuel and renewable energy, has a positive effect on market capitalization in the COMESA region. The coefficient for FSIL is 8.19 and for RECO is 9.08, proposing that both fossil and renewable energy consumption drive market capitalization in the COMESA region. This is consistent with findings in the literature, where [7,20] argue that energy consumption, particularly from renewable sources, plays a crucial role in driving both economic growth and stock market performance. The strong positive relationship between energy consumption and market capitalization is further supported by [31], who emphasized the importance of energy infrastructure in stimulating economic activity and financial development. These findings suggest that energy, particularly from renewable sources, plays a vital role in advancing financial markets in developing regions such as the COMESA bloc.

The coefficient for EIMP is 0.44 and significant at the 10% level (p-value = 0.09), showing a positive, although relatively weaker, connection between energy imports and market capitalization. This shows that more dependence on imported energy could marginally boost market capitalization; however, the result is not as strong as the energy consumption variables. This outcome could be explained by the fact that energy imports may serve as a short-term solution to energy shortages, thereby soothing markets in the short term but not necessarily achieving long-term sustainable growth. The literature on energy security, such as [29], emphasizes that while energy imports can address short-term energy demands, they are not a sustainable substitute for long-term economic stability or growth in developing markets. This perspective helps explain the moderate coefficient on energy imports (EIMP) observed in this study.

From a different perspective of finance growth theory, GDP growth displays an insignificant relationship with market capitalization in the high quantiles. This result makes sense in the context of COMESA because economic growth in the region has often been driven by government or donor-funded infrastructure projects rather than by private sector investment. As a result, increases in GDP do not necessarily lead to higher profits for publicly listed companies, which weakens the usual link between economic growth and stock market performance.

In summary, our study has established the following findings:

• Fossil fuel consumption and renewable energy adoption significantly influence the stock market performance, whilst the renewable energy coefficient shows a strong effect at the low quantile of stock market performance.
• Energy import, on the other hand, has a slightly positive effect at low quantiles, though it became negative in higher quantiles, which depicts a vulnerability to external dependence.
• Economic growth doesn’t show a statistically significant effect on market capitalization within the COMESA region, which is a resultant effect of structural barriers in the financial transmission within this region.

The above results have served as the foundation for our thesis, which posits that energy policy and composition are crucial elements to consider in shaping financial market dynamics in a developing region, specifically COMESA.

5. Conclusions and Recommendations

This study discloses the dynamics between the energy market, economic growth, and stock market performance in the COMESA region. The outcomes show significant connections across different quantiles, particularly with renewable energy consumption (RECO), which shows a strong positive influence on market capitalization (MCAP) at the lower quantiles (5th and 25th), but the relationship weakens at higher quantiles. This indicates that while the shift towards renewable energy might contribute to the growth of market capitalization in the lower range of the distribution, its effects appear more muted at higher levels of market capitalization. This finding is consistent with the transitional costs associated with renewable energy investments, as argued by [49], which may initially suppress market performance in the long term despite offering sustainable growth potential. On the other hand, the DKSE Method reveals that fossil energy consumption (FSIL) and renewable energy consumption (RECO) have statistically significant positive coefficients (with very low p-values), further supporting the importance of these variables in influencing market capitalization. These results are in line with the broader view that energy markets significantly affect stock market performance, but they also underline the mixed nature of these effects depending on the specific energy sources in question. However, GDP growth (GDPG) shows no significant impact on market capitalization in either model, indicating that in the COMESA region, macroeconomic growth does not necessarily lead to an increase in market capitalization. This finding stands in contrast to studies by [32,53], which highlight a strong positive relationship between economic growth and stock market development.

These discoveries strengthen the importance of making an allowance for both the short-term and long-term impacts of energy consumption patterns, as well as the level of economic development, in comprehending stock market performance. In the short term, both fossil fuel and renewable energy consumption significantly influence market capitalization. However, in the long run, this relationship weakens, with renewable energy consumption exhibiting more complex effects that vary depending on the quantile level of market capitalization. These findings also highlight the broader challenges of shifting from fossil fuels to renewable energy, a transition that may incur short-term costs but offers long-term benefits as emphasized by [20,72]. The absence of a significant connection between GDP growth and market capitalization in both models suggests that factors unique to the COMESA region, such as economic structure, energy transition challenges, and financial market dynamics, may restrain or even overshadow the typical connections observed in the other areas. This difference from the broader literature highlights the need for a more tailored approach when interpreting the economic growth–stock market nexus in emerging economies, particularly in energy-dependent regions like COMESA.

5.1. Policy Attribute

• Slow introduction of renewable energy subsidies that will provide funds from carbon tax revenue, which will help provide short-term stability to the price of fossil fuel when transitioning to renewable energy.
• The introduction of the green bonds initiative in the COMESA region will help promote and channel the interest of investors in this region, which will lead to expansion and upgrade in the energy sector.
• The consensual agreement for power pool among the member countries in the COMESA region will help reduce the risk of dependence posed in this region by 15% over the next five years.
• Including flexible pricing provisions in energy-related bond agreements can strengthen investor confidence and help governments better manage exposure to energy market risks.

These actions will help address the fundamental challenges in our analysis and also help in a smoother transition to renewable energy, while maintaining the COMESA financial market.

From a global policy stance, our findings have emphasized the need to balance energy transition with the stability of the financial market. So, developing economies outside the COMESA region, like Asia and Latin America, are advised to draw lessons and transition with a dual reliance on the use of fossil fuel and renewable energy as the more sustainable option. The international institutes and the development banks are advised to boost funding for the adoption of renewable energy, which will improve financing for the infrastructure and technical know–how in such regions. In addition, energy-importing countries should explore the idea of a multifaceted option in energy security arrangements to minimize external shock. Having these factors planned out would help the global climate finance initiatives explore the cross-border energy market, which would help focus on a more sustainable financial development. Developing policies that are responsive to the exceptional economic and energy conditions in COMESA will help policymakers to successfully pilot the transition to a more sustainable energy future while promoting economic growth and financial stability [72].

5.2. Limitations and Future Research

Since this study offers a wide-ranging insight into the relationship among the energy market, economic growth, and stock market performance in COMESA, quite a few limitations have been encountered.

• The annual data used, which spanned from 1990 to 2022, may neglect the short-term shocks or fail to capture the fluctuations of stock price within the year reported (monthly report or weekly report posed internally).
• Due to data availability, some COMESA member countries might be underrepresented, which would affect their representation of the general welfare.
• This study will make a good contribution if published, but the financial constraints would be a great challenge without funding.
• The MMQR method employed in the analysis captures the distributional effect and does not factor out the endogeneity for the variables.

Future research could find this study a great help, as it has laid some foundations to facilitate the comparison among regions and help in dynamic structural modeling for related research, and expand these findings.