Assessing the Role of Renewable Energy in the Sustainable Economic Growth of the European Union

Abstract

The adoption of renewable energy sources offers significant economic and sustainability benefits. These sources—solar, wind, hydro, biomass, and geothermal—are crucial for transitioning to a sustainable, low-pollution energy model. Key benefits of renewable energy include job creation, reduced energy costs, decreased reliance on imported resources, minimized environmental impact, and long-term economic stability. Renewable energy also plays a vital role in achieving environmental and sustainability goals. By reducing dependence on imported energy resources, it enhances energy security. Countries investing in renewables lower their reliance on international supply chains and geopolitical risks, which is particularly relevant for European Union nations historically dependent on energy imports. Domestic renewable energy resources help stabilize prices and ensure a consistent long-term energy supply. This study aimed to assess the impact of renewable energy sources on the economy and sustainable development in the European Union. Data for all variables were collected from the Eurostat database. The unbalanced panel data sample consisted of 27 EU countries (N = 27), covering the period 2001–2022 (T = 22). The analysis and generalization of the scientific literature compared theoretical and practical statements, econometric models, and the least squares method. Here, the hypothesis that “the transition to renewable energy sources will have a smaller negative impact on economic growth when the country is more dependent on imported energy sources” was accepted, and this means that using renewable energy sources not only contributes to environmental goals and climate change mitigation but also provides various economic benefits, including job creation, lower energy prices, greater energy security, and long-term sustainability. It is essential in the transition to a cleaner and more sustainable economy.

1. Introduction

The use of renewable energy sources has significant economic and sustainability benefits. These resources—solar, wind, hydro, biomass and geothermal—are key to transitioning to a more sustainable and less polluting energy consumption model [1,2]. Renewable energy sources’ main economic and sustainability benefits include job creation, lower energy prices, reduced dependence on imported resources, lower environmental costs, and long-term financial stability.

The development of renewable energy sources directly contributes to economic growth by creating jobs in various areas, including technology development, production, design, installation, and maintenance. Each branch—from producing solar modules to installing wind turbines—requires skilled labor resources. For example, in 2022, the global solar energy sector provided more than 4 million jobs, while the wind energy sector created more than 1 million [3,4]. This contributes to the diversification of the economy and reduces dependence on traditional, less sustainable sectors.

In addition, using renewable resources helps reduce energy prices in the long term. Although the initial investment in implementing these technologies can be high, the long-term costs are significantly lower than traditional resources such as coal and gas [5]. Renewable energy is “free” (e.g., sunlight, wind), so while equipment and infrastructure require initial investment, operating and maintenance costs are significantly lower [6]. In addition, renewable resources reduce the variable energy prices that depend on fluctuations in international oil and gas markets, thereby increasing energy security and stability.

Renewable resources also contribute significantly to environmental goals and sustainability [7,8,9]. They are less polluting and do not have the same negative impact on the environment as fossil fuels [10]. Solar and wind energy production is almost emission-free, reducing carbon dioxide and other greenhouse gas emissions [6]. This is an essential step in the fight against climate change, as it reduces the release of these gases into the atmosphere. Renewable energy development helps the EU and countries worldwide achieve their climate change goals, including the Paris Agreement goals of climate change mitigation and carbon neutrality [11].

In addition, using renewable resources contributes to lower dependence on imported energy resources, increasing countries’ energy security [12,13,14,15,16,17]. Each country investing in its renewable energy resources reduces its dependence on international supply chains and geopolitical risks. This is particularly important for European Union countries that were previously heavily dependent on energy imports from different countries. Using domestic renewable resources reduces price fluctuations and ensures longer-term supply stability.

Ultimately, using renewable resources contributes to long-term economic stability and sustainability [18,19]. These technologies are long-term investments, as they can produce energy for decades without significant additional costs. Investments in renewable energy can also stimulate research and technological development, creating even more innovation and opportunities in the future [20,21].

The climate change mitigation policy is currently a priority environmental policy in the world. Increasing energy efficiency and using renewable energy resources are the main ways to reduce greenhouse gas emissions and are the main objectives of the European Union (hereinafter—EU) energy and climate change mitigation policy [22]. Renewable energy resources are integral to the sustainable development of the modern world and society. They have a profound impact on a country’s economy, growth rates, social and economic well-being, and play a key role in driving technological advancements, ensuring security, and fostering financial stability. Despite these benefits, non-renewable energy sources still dominate global energy production and consumption. However, as the cost of energy resources continues to rise, the energy sector’s role in combating climate change becomes increasingly critical, underscoring the need for a transition to renewable energy [23,24,25].

This is especially relevant for those countries where most of the energy resources are imported [26,27,28,29].

Therefore, it is crucial to justify how the state should correctly regulate the development of renewable resources to positively impact macroeconomic and social indicators reflecting the development of the state and the quality of life of its population. For this reason, developing renewable resources and assessing their potential are relevant from the point of view of governments, scientists, and business interests. Sustainability reporting is now essential [30,31,32].

The world’s energy needs are constantly growing due to rapid and intelligent development. Lithuania and other European countries have limited domestic energy sources and are therefore dependent on imported energy resources such as natural gas, oil, and coal. Over the past 10 years, Lithuania’s energy imports have increased by 89%, which has made our country even more vulnerable, as energy prices become volatile and difficult to predict. Another acute problem in the world is air pollution caused by fossil fuels. In order to reduce carbon dioxide emissions and mitigate global climate change, investments in green energy are needed. Also, the current and future lack of energy needs and environmental, political, economic, and social reasons force countries to look for other energy sources. A potential alternative is renewable energy resources, which can become the answer to the question of sustainable energy planning. Thus, replacing fossil fuels with renewable energy would reduce energy imports, increase the security and efficiency of energy supply, and solve environmental issues.

Our research problem consists of responding to the question of how the use of renewable energy resources can influence the growth of the economy in the context of the European Union. After studying the literature [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32], here the main problem is the lack of information about the use of renewable energy resources and their influence on the situation of the economy. Thus, the authors formulated the main research problem for their own research, as follows: how will the growing need to increase the share of renewable energy sources and reduce dependence on cheaper but imported fuels affect economic growth?

The object of this study is the impact of the development of renewable resources on economic growth.

The purpose of this work is to assess the impact of the use of renewable energy resources on the economy and sustainable development.

Research objectives: The objective of this article is to accomplish the following:

Review the theoretical aspects of renewable energy sources and sustainable development.

After that, it is necessary to develop a methodology for assessing the impact of renewable energy sources on the economy.

Based on this methodology, it is necessary to assess the impact of renewable energy sources on the economy and sustainable development.

Research methods include the analysis and generalization of the scientific literature, comparing theoretical and practical statements, econometric models, and the least squares method.

This article consists of three main parts. In the first part, the main information from scientific articles about the development of renewable energy resources as a factor of economic growth is provided. In the second part, the main method for the analysis is briefly mentioned and described. In the third part, the main hypothesis (H: the transition to renewable energy sources will have a more negligible negative impact on economic growth when the country is more dependent on imported energy sources) is checked. After that, the main conclusions are drawn, and some recommendations are proposed.

2. Development of Renewable Energy Resources as a Factor of Economic Growth: A Literature Review

Recently, the European Union has been facing three main issues in the energy sector: the security of the energy supply, the competitiveness of the energy sector, and the sustainability of the energy sector. Energy is the essence of any production process, and it must be ensured for the state’s economic growth. The progress of human civilization relies mainly on energy, and as human society continues to grow, energy needs are increasing. Due to limited fossil fuel reserves and increased energy consumption, it is no longer possible to rely solely on fossil energy resources in the current world [33]. European Union countries are among the most vulnerable due to their high dependence on energy imports and the scarcity of energy resources. Replacing fossil fuels with renewable energy would reduce energy imports, increase energy security, solve environmental issues, and increase energy efficiency [34,35].

It is necessary to note that economic development processes and economic growth also increase energy consumption worldwide. Therefore, traditional energy sources should be reduced to ensure sustainable development and economic growth. Transitioning to renewable energy is necessary to reduce global financial problems and carbon dioxide emissions and mitigate global climate change [18,36]. It is important to note that scientists are constantly analyzing the long-term benefits of renewable energy for the country’s economy. Therefore, it is necessary to highlight the classification of renewable energy sources.

2.1. The Results of an Analysis of Renewable Energy Sources in the Energy Sector and Their Development Trends in Individual Economic Sectors

It should be noted that the economic literature began to talk about renewable energy sources and their impact on the economy after the 1973 oil crisis. Renewable energy sources are a vital factor in achieving sustainable economic growth. It is important to note that financial well-being is threatened by increased energy demand, which has led to a rapid increase in the consumption of traditional energy sources [37]. It can be argued that renewable energy sources, which meet the basic energy needs of a country, not only do not pose a threat to economic well-being but also reduce dependence on energy-importing countries, promote more significant employment, and increase security [38,39]. Renewable energy sources are defined as energy sources whose occurrence is determined by natural factors and are therefore “renewable”. Renewable energy is defined as energy from renewable non-fossil resources: wind, solar, aerothermal, geothermal, hydrothermal and ocean energy, hydropower, biomass, biogas (including landfill gas and sewage treatment plant gas), and energy from other renewable non-fossil resources whose use is technologically possible now or will be possible in the future. Renewable energy sources are unlimited, and their supply is continuous, covering technological, economic, political, and social processes [40].

Research by various scientists reveals that renewable energy sources must be sustainable, inexhaustible, and environmentally friendly, and renewable energy must be inexpensive in the long term and meet the needs of society [6]. Scientists [1,6,11,41] define renewable energy sources as natural sources such as solar, wind, biomass, geothermal, hydropower and ocean resources, biofuels, and hydrogen obtained from renewable energy sources (

Table 1. The concept of renewable energy sources.

Source	Concept
[42,43]	Renewable energy sources are unlimited, and their supply is continuous, covering technological, economic, political and social processes.
[44,45]	Natural resources that arise from natural processes. Wind, biomass, solar, geothermal, and water energy.
[46,47]	Wind, solar, aerothermal, geothermal, hydrothermal and ocean energy, hydropower, biomass, biogas (including landfill gas and sewage treatment plant gas), and energy from other renewable non-fossil resources, the use of which is technologically possible now or will be possible in the future.
[1,2,6,45]	Renewable energy sources include primary energy technologies such as biomass, hydropower, geothermal, wind, and solar energy.
[1,2,47]	Solar, wind, biomass, geothermal energy, hydropower and ocean resources, biofuels, and hydrogen.

Source: Compiled by the authors based on the literature review.

). Renewable energy sources consist of natural sources that arise from natural processes—wind, biomass, solar, geothermal and water energy. Renewable energy sources include primary energy technologies and are unlimited. They include biomass, hydropower, geothermal, wind and solar energy [42,43,44,45,46,47,48].

It can be noted that in many literature sources, renewable energy sources are defined similarly. Authors who analyze renewable energy sources describe those sources that arise from nature and its natural processes, i.e., wind, solar, biomass, hydropower, water, and geothermal energy. Scientists do not emphasize natural processes but instead emphasize their inexhaustible resources and importance in economic, technological, political, and social processes.

In 2007, Jager Waldau revealed structural obstacles to implementing renewable energy sources—national dependence on traditional energy sources and significant initial investments. Although renewable energy accounts for a small share of countries and their supply network is not multiplying, the EU is creating incentive measures so that countries can develop renewable energy sources and, at the same time, ensure energy security.

The following renewable energy sources are distinguished: wind, hydropower, solar, biomass, and geothermal. The fastest development in recent decades has been in the fields of hydropower, wind, and solar energy. When evaluating each type of renewable energy, the advantages and disadvantages of RES are discernible.

It should be noted that biomass is defined as biologically transparent raw materials, waste, and residues of biological origins from agriculture, forestry, and related industries, including fisheries and aquaculture, plant and animal materials, and biologically transparent industrial and municipal waste. Biomass includes plant materials like wood, crops, and animal waste. Biomass is humanity’s primary energy source, and it has been used since the discovery of fire [46,47]. Biomass is cheaper than fossil fuels, ensuring the constancy of energy production, and available biomass resources can fully replace the shortcomings of fossil fuels. The main disadvantage of biomass found in the literature is the preparation of biomass itself, which requires high energy costs [6].

In the Renewable Energy Law, wind energy is defined as air energy that produces energy. The potential of wind energy is limited in many regions, but it ensures independence from energy-importing countries and their political instability. Wind energy is a scalable technology that can be transferred from households to the electricity grid [45]. This renewable energy source has some advantages. Wind resources are inexhaustible; implementing a wind farm takes little time compared to other technologies; and wind is a long-lasting energy source. The main disadvantage of wind energy is that wind energy is unstable. As mentioned, it can be limited in many regions since energy production depends on wind speed. Hydropower is the most widely used renewable energy source in countries and regions, generating the largest share of electricity. According to the Renewable Energy Sources Act, hydropower is the energy of stagnant and/or flowing water to generate electricity. When conditions are favorable, hydropower is a low-cost renewable energy source since it is the most suitable place for hydropower production in mountainous regions. The advantages of hydropower include inexpensive electricity production, inexhaustible water resources, uninterrupted electricity production, and reliability and stability. The scientific literature also identifies the disadvantages of hydropower; energy production depends on climate and location and impacts nature and aquatic life [46].

Geothermal energy is defined as heat energy accumulated below the surface of the earth. Scientists and technologists seek to improve and develop geothermal energy technologies because their application is wide. The advantages of geothermal energy are that resources are inexhaustible and constantly renewable, and the environment does not become polluted. The main disadvantage is that geothermal energy is limited and unavailable in all countries.

Solar energy is solar radiation energy, which is electricity directly obtained from sunlight. Solar energy is recognized as the most potential and powerful energy source. Solar energy has replaced fossil fuel energy costs in many countries. The advantages of solar energy include inexhaustible energy sources, durability and reliability, an ample supply of equipment, and rapidly decreasing prices. The main disadvantages of solar energy are insufficient energy production and dependence on weather conditions [1,2].

It is necessary to mention that the consumption and development of all previously discussed energy sources in many countries is constantly increasing. In the EU, their use and development are one of the most crucial energy policy goals. The use of renewable energy sources ensures the efficiency of important areas in the country. One is energy security, which reduces the state’s dependence on energy-importing countries. Economic growth and productivity depend on energy security because industries cannot develop without a reliable energy supply [41]. By extracting energy from renewable energy sources, the state’s independence and reliability of use increase.

It is noteworthy that the development of renewable energy sources in the state has a significant impact on technological progress. The EU market is open to technological development and aims to achieve the highest possible level, and the direction of renewable energy is inseparable from this.

In summary, the increasing use of renewable energy sources in the state ensures economic well-being. The use of regional energy resources for energy production promotes the country’s economic development. The number of jobs increases, and the import–export deficit is reduced [3,4]. Investments in renewable energy resources are beneficial in the long term. Attracting investments and local use of energy resources improves the state’s balance of payments.

It is important to note that the massive use of fossil fuels in the energy sector has caused difficulties for the world, has harmed the ecosystem, and has caused chaos. Climate change is an additional problem that has a negative impact on human life, including the environment. Energy demand continues to grow, so it is necessary to address the issue of petrochemicals (fossil fuels), consider the significant contribution of RESs to sustainable development and their impact on the environment on a global scale, and start to follow renewable energy resources [48].

It should be noted that the development of renewable energy resources—nationally, regionally, and globally—is closely related to sustainable development policies; one of the principles of sustainable development states that renewable resources must replace non-renewable ones. The development of renewable energy sources increases the diversity of domestically produced energy sources and thus reduces the need for imported energy and dependence on energy-exporting countries.

Research reveals that renewable energy sources—wind, solar, and geothermal—play an essential role in solving the problem of increasing energy needs in developing and developed countries [4,49,50,51,52,53,54,55].

Renewable energy creates a balance between environmental protection and economic and technological growth. The benefits of renewable energy sources include reduced dependence on fossil fuels and pollution, energy security, high energy efficiency, the use of natural resources, and the creation of new jobs [56].

Using renewable energy sources to produce electricity is very important to reduce carbon dioxide emissions. RESs are a part of the energy supply that reduces greenhouse gas emissions and meets the European Union’s (EU) commitments under the Paris Agreement on Climate Change and the EU Energy and Climate Programme for 2030. Furthermore, renewable energy production has a vital role in increasing the security of energy supply, technological development, and sustainable energy at affordable prices while ensuring health, environmental, and social benefits, as well as increasing job creation opportunities.

2.2. Description and Analysis of the Impact of the Development of Renewable Energy Resources on the Economy

It should be noted that, over the past decades, renewable energy deployment technologies have developed, and the main reasons for their development have also changed—energy security, environmental issues, and energy accessibility. Renewable energy includes various benefits—new jobs are created, the health and education system is improved, poverty is reduced, and negative environmental impact is reduced. The added value for the economy means that the value of the goods and services produced is created based on the development of renewable energy. The added value from renewable energy is assessed at the following levels [32,36,37,38,39,40]:

• At the micro level. The purchase of resources used for production has decreased during the production process.
• At the meso level. From the perspective of the entire industry, the added value is the difference between the total output and the costs of the intermediate product. The contribution of the industrial sector to the increase in the gross domestic product.
• At the macro level. The added value of all manufactured products and economic activity is reflected in the GDP indicator.

Welfare in economics is usually presented as a consumption benefit for a group of people. Renewable energy can affect many welfare indicators, as well as environmental and health protection. Employment in the country increases due to the development of RESs; each new project and investment in RESs creates new jobs and increases the income of citizens [56].

The category of value creation in assessing socio-economic impact focuses on the distribution of energy generation sources and ownership among energy consumers and taxpayers. Renewable energy plants generate income for their owners, whereas traditional power plants are typically owned by utilities. This shift affects centralized utility business models, leading to the emergence of new market participants alongside non-utility power producers (NPPs). The energy system’s socio-economic impact reflects the additional costs and benefits of transitioning to a renewable-based model. Costs include those related to electricity production from renewable energy sources (RESs), such as technology installation, system balancing to ensure stability, and long-term energy resource availability. Furthermore, expanding and modernizing energy networks to accommodate RESs also incur additional expenses. External factors associated with RESs can be both positive and negative. Positively, energy technologies drive innovation, foster the creation of new enterprises, and support the development of policy programs. Additionally, renewable energy production reduces both external and internal risks. External risks, such as unreliable energy supply, are mitigated, while internal risks, like the use of harmful substances, are minimized. Additional impacts include all remaining costs and benefits associated with the implementation of RES. One of the most important is the reduction in risks in the areas of accidents—geopolitical and financial. Geopolitical risk is closely related to imports; countries can achieve greater independence and avoid price fluctuations by reducing energy imports. Economic risk is closely associated with trade balance problems. As mentioned earlier, the economy is dependent on fossil fuels. Therefore, future energy prices for both importers and exporters are related to financial volatility risks. Renewable energy sources are more predictable, and predictable costs can mitigate this risk [42].

It is worth noting that in an increasingly energy-dependent world, the relationship between energy consumption and economic growth is becoming an increasingly popular topic of research for scholars. As a result, the literature on the relationship between energy consumption and economic growth has grown significantly over the past two decades. Scholars have conducted many studies on the causal relationship between economic growth and energy but have found mixed results. The first empirical study that analyzed the relationship between energy and economic development was conducted by Kraft in 1978. The study examined Granger causality between energy and GDP growth, and the results showed that such a relationship exists. This proved that an increase or decrease in GDP affects energy consumption, but energy consumption does not necessarily affect GDP. This result has prompted many new studies to investigate the correlation, as different methods yield different results.

Notably, there are many contradictory results regarding the relationship between energy consumption and economic growth, with some studies revealing a causal relationship while others do not. It is important to emphasize that such different results were obtained during the same study period due to the failure to assess other variables.

Renewable energy sources (RESs), such as wind, solar, biomass, hydropower, and geothermal, arise from natural processes and are vital for sustainable development. These resources are inexhaustible and play a significant role in economic, technological, political, and social processes. Despite challenges like reliance on traditional energy and high initial investments, the EU promotes RESs to enhance energy security and sustainability.

Wind energy is scalable and ensures independence from energy-importing countries but depends on wind speed and regional potential. Hydropower, the most widely used RES, provides reliable electricity at a low cost but depends on the climate and impacts aquatic ecosystems. Solar energy, abundant and rapidly advancing, reduces fossil fuel dependency but is weather-dependent. Biomass, derived from biological materials, is cost-effective but requires energy-intensive preparation. Geothermal energy, although clean and inexhaustible, is limited by geographic availability.

RES development boosts economic growth, technological innovation, and energy security while reducing carbon emissions and dependence on fossil fuels. The EU integrates RESs into energy policies to fulfill climate goals, enhance energy efficiency, and create jobs. Investments in RESs strengthen local economies, reduce trade deficits, and garner long-term benefits.

The socio-economic impact of RESs includes reduced environmental risks, improved health, and poverty alleviation. At various levels—micro, meso, and macro—RESs contribute to GDP growth and economic stability. Geopolitical risks are mitigated by reduced energy imports, and financial risks are minimized through predictable RES costs.

The relationship between energy consumption and economic growth is complex, with mixed study results. However, RESs clearly foster sustainable growth, balancing environmental preservation with technological and economic development and ensuring a resilient energy future. So here it is necessary to practically describe and evaluate the development of economic growth, because after deep literature analysis, the authors have found a gap in research in this area.

3. Materials and Methods

3.1. Econometric Specification of the Research Model

In trying to assess the impact of RESs on economic growth, the necessary data were used. Data for all variables were collected from the Eurostat database. The unbalanced panel data sample consists of 27 EU countries (N = 27), covering the period 2001–2022 (T = 22).

The impact of the transition to renewable energy sources on economic growth will be assessed using eclectic specification of the economic growth model [18,19,36,37,38,39,40,41,42,57]. The basis of this model is the neoclassical conditional beta convergence model, which, depending on the research objective, is supplemented with various economic growth factors. The following equation can describe the most general expression of this model for panel data:

$${\displaystyle \frac{1}{T}}ln\left({\displaystyle \frac{Y_{i,t+T}}{Y_{i,t}}}\right)={\alpha }_i+\beta ln{Y}_{i,t}+\gamma X+{\theta }_t+{\epsilon }_{i,t}$$

(1)

where ${\displaystyle \frac{1}{T}}ln\left({\displaystyle \frac{Y_{i,t+T}}{Y_{i,t}}}\right)$ is the average annual real GDP growth rates per capita (Y) from t to T in country i. In the following equations, these growth rates will be denoted by gri,t and used to approximate economic growth rates. This study will use the average overlapping five-year (T = 5) future economic growth rates (overlapping forward-looking 5-year growth rate). Several circumstances determine this choice. The first is that when calculating the average economic growth rates over several years, the effect of the business cycle on economic growth rates is eliminated, and only factors that affect economic growth in the long term can be taken into account. The second is that overlapping growth rates do not reduce the study sample as drastically as non-overlapping growth rates, although they cause the problem of error autocorrelation. The third is that future economic growth rates are used to reduce the possibility of the feedback effect. In the context of this study, we can more likely expect that it is not investments in and the transition to renewable energy sources in year t that affect economic growth in year t, but it is economic growth in year t or its forecast made in year t − 1 that encourages one or another state investment in the infrastructure of renewable energy resources or the development of their use in year t. For example, when predicting an economic recession, a state may pursue an expansionary fiscal policy and invest additional money in energy infrastructure projects. This potentially existing inverse relationship may lead to the incorrect conclusion that the development of renewable energy resources affects economic growth, even though the opposite is true. When analyzing the impact of factors on future economic growth rates, the Granger causality structure in the model specification avoids the possibility of feedback effects. Another reason for using future economic growth rates is based on the assumption that the impact of economic growth factors may not manifest itself in the current year. This effect is likely to be lagged.

${\alpha }_i$ includes unobserved and time-invariant (or very slowly varying) country-specific effects, i.e., unobserved country heterogeneity. In the context of this study, these could be the geographical and natural features of the countries (e.g., the average number of sunny and cloudy days and the average daylight hours, wind strength, and direction; river network suitable for hydroelectric power plants; the forest cover of the countries; the abundance of fossil fuel resources and their exploitation volumes, etc.), which determined and determine the different potential of renewable energy resources of the countries and the need to replace imported fossil fuels with them. Depending on the assumptions made about ${\alpha }_i$, the method of calculating the estimates is selected. $ln{Y}_{i,t}$ is the logarithm of the country’s initial GDP per capita, and the β estimate reveals whether convergence occurs between the studied countries’ economies. X is a vector of economic growth factors. γ is a vector of estimated coefficients of the impact of economic growth factors on economic growth. θ_t is a vector of time pseudovariables. Time pseudovariables allow us to model the general economic growth trend characteristic of this study’s analyzed group of countries. Neoclassical economic growth theory suggests that as the economies of the EU group of countries reach a higher level of development, their overall average economic growth rate will slow down. ${\epsilon }_{i,t}$ is the idiosyncratic error of the model.

3.2. Research Variables and Specification of Empirical Research Models

This subsection details the specifications of the models that will be used to test the research hypotheses empirically. To avoid overestimating the transition to renewable energy sources’ impact on economic growth due to omitted variable bias, it is necessary to ensure that all key economic growth factors are controlled in the model. Therefore, when detailing the first equation, we first discuss the factors of economic growth included in vector X. The detailed specification of the economic growth model used for empirical research with panel data can be written as the following equation:

$$\begin{array}{c}{gr}_{i,t}={\alpha }_i+\beta ln{Y}_{i,t}+{\gamma }_1{RnD}_{i,t}+{\gamma }_2{HC}_{i,t}+{\gamma }_3{∆lnHICP}_{i,t}+{\gamma }_4{G}_{i,t}+{\gamma }_5{GCF}_{i,t}{+\gamma }_6{GCF}_{i,t}^2\\ +{\gamma }_7{TR}_{i,t}{+{\gamma }_8{CC}_{i,t}+{\gamma }_9{∆lnEMPL}_{i,t}+\theta }_t+{\epsilon }_{i,t}\end{array}$$

(2)

where gr_i,t—average overlapping five-year future economic growth rates are calculated as ${\displaystyle \frac{1}{5}}ln\left({\displaystyle \frac{Y_{i,t+T}}{Y_{i,t}}}\right)$, where Y is real GDP per capita.

• Real (2010 prices) GDP per capita (EUR)—Y_i,t;
• Total investment in R&D (% of GDP)—RnD_i,t;
• Share of population aged 15–64 with tertiary (ISCED 5–8) education (%)—HC_i,t;
• Inflation (calculated as the average annual change in the Harmonized Consumer Price Index)—ΔlnHICP_i,t;
• Central government final consumption expenditure (% of GDP)—G_i,t;
• Gross capital formation expenditure (% of GDP)—GCF_i,t;
• Ratio of imports and exports of goods and services to GDP (% of GDP)—TR_i,t;
• Corruption control level (index)—CC_i,t;
• Employment change (index)—ΔlnEMPL_i,t.

The model includes the most commonly used economic growth factors in empirical studies, supplemented by specific variables of interest to researchers.

This study hypothesizes the impact of various external factors on how the transition to renewable energy sources affects economic growth. One of the goals of the transition to renewable energy sources is to increase the country’s security by reducing dependence on imported energy sources and supplying them with local ones. Therefore, this study proposes hypothesis H: the transition to renewable energy sources will have a more negligible negative impact on economic growth when the country is more dependent on imported energy sources. The dependence on the imported energy source (IMP_D_i,t) will be calculated as the ratio between the volume of imported energy resources and the sum of their imports and exports. In this case, 0 means that the country only exports but does not import, and 100 means that it only imports but does not export. Information on variables by individual energy sources is presented in

Table 2. Names of variables (mediators), their abbreviations, and descriptive statistics.

Variable Name	Abbreviation Title 2	Mean	Minimum	Maximum	Standard Deviation	Number of Observations
Dependence on imported solid fossil fuels (%)	IMP_D_SFFi,t	90.819	5.1666	100	19.121	571
Dependence on imported oil and oil products (%)	IMP_D_OPPi,t	77.279	31.352	100	13.683	594
Dependence on imported natural gas (%)	IMP_D_NGi,t	91.694	0	100	20.639	555
Dependence on imported electricity (%)	IMP_D_Ei,t	55.434	4.3875	100	23.191	557
Number of cooling degree days	CDDi,t	117.92	0	812.18	182.52	594
Number of heating degree days	HDDi,t	2825	322.36	6179.8	1152.1	594

Source: Compiled by the authors.

.

The hypothesis will be empirically tested using the following regression equation specification:

$${gr}_{i,t}={\alpha }_i+\beta ln{Y}_{i,t}+\gamma X+{\phi }_1{REN}_{i,t}+{\phi }_2{IMP\_D}_{i,t}+{\phi }_{12}{REN}_{i,t}\times {IMP\_D}_{i,t}+{\theta }_t+{\epsilon }_{i,t}$$

(3)

where the interaction between ${REN}_{i,t}$ and ${IMP\_D}_{i,t}$, i.e., ${REN}_{i,t}\times {IMP\_D}_{i,t}$, allows us to determine how the impact of the transition to renewable energy sources on economic growth depends on the extent to which a country is dependent on imported energy sources. Rearranging the equation yields an expression in which the effect of REN_i,t on gr_i,t depends on IMP_D_i,t as follows:

$${gr}_{i,t}={\alpha }_i+\beta ln{Y}_{i,t}+\gamma X+{\phi }_2{IMP\_D}_{i,t}+\left[{\phi }_1+{\phi }_{12}{IMP\_D}_{i,t}\right]\times {REN}_{i,t}+{\theta }_t+{\epsilon }_{i,t}$$

(4)

where ${\phi }_1+{\phi }_{12}{IMP\_D}_{i,t}$ is the composite coefficient of the impact of the transition to renewable energy sources on economic growth, depending on the degree to which the country depends on imported energy sources. In this specification, not only does the coefficient of the impact of the transition to renewable energy sources on economic growth depend on the degree of dependence of the country on imported energy sources but also the standard error of this coefficient (σ), indicated as follows:

$$\sqrt{var\left({\phi }_1\right)+{IMP\_D}_{i,t}^2·var\left({\phi }_{12}\right)+2·{IM{P}_D}_{i,t}·cov\left({\phi }_1,{\phi }_{12}\right)}$$

(5)

Since both the coefficient of the impact and its standard error are conditional, their ratio (t-ratio or Student’s coefficient) that determines the probability with which the calculated coefficient differs from zero depends on the degree of dependence of the country on imported energy sources. This means that to determine the effect of the transition to renewable energy sources on economic growth, depending on the degree of dependence of the country on imported energy sources, the coefficients and standard errors need to be calculated for each observed level of reliance on imported energy sources. Hypothesis H is accepted if the estimated conditional slope coefficient increases as the country’s dependence on imported energy sources increases.

The coefficient estimates for all regression models are first calculated using the ordinary least squares (OLS) method. The ${\alpha }_i$ estimates for these models are then tested to determine their behavior and select the appropriate method for calculating the estimates. In the first stage, the Fisher (F) test allows us to test H0: ${\alpha }_1={\alpha }_2\dots ={\alpha }_i$, i.e., that ${\alpha }_i$ is not specific, with the alternative that ${\alpha }_i$ is specific and invariant over time. The small p-value of this test (<0.05) allows us to conclude that the OLS method, which does not eliminate and model ${\alpha }_i$, is inappropriate and may result in biased parameter estimates. In this case, a more appropriate alternative would be calculating fixed effects (FE) estimates. The FE method transforms the data (time-demeaned transformation) and thus eliminates ${\alpha }_i$ from the model.

In the second stage, the Breusch–Pagan (BP1) test is performed, which tests H0: ${\alpha }_1={\alpha }_2\dots ={\alpha }_i$, i.e., that ${\alpha }_i$ is not specific, against the alternative that ${\alpha }_i$ is specific and varies randomly over time. The small p-value of this test (<0.05) allows us to conclude that the MKM, which does not eliminate and model ${\alpha }_i$, is inappropriate and may result in biased parameter estimates. In this case, a more suitable alternative for calculating random effects (RE) estimates would be the generalized least squares (GLS) method. The GLS method transforms the data (quasi time-demeaned transformation), thus partially eliminating ${\alpha }_i$ from the model.

In the third stage, the Hausman test is performed, which allows us to test H0: the estimates of the RE are consistent. A small p-value of this test (<0.05) will enable us to conclude that the RE is not appropriate and that the FE method is more suitable.

These three tests, based on the analysis of the behavior of ${\alpha }_i$, allow us to choose one of the three methods for calculating estimates—GLS, FE, or GLS. However, selecting the appropriate method for calculating estimates based on the behavior of ${\alpha }_i$ does not guarantee that the model will not be characterized by endogeneity.

3.3. Testing of the Model Assumptions

To ensure the reliability of the estimated coefficients of the regression model, the residual errors of the models are accounted for, i.e., ${\epsilon }_{i,t}$. To ensure the accuracy of the coefficient estimates of the regression model, it is necessary that the residual errors of the models (ε_(i,t)) meet certain assumptions. One of the main assumptions is the linear relationship between the dependent and independent variables since, in many cases, linear models are used due to their universality. If this relationship is not linear, the behavior of the error may become nonlinear, and its dispersion will depend on the value of the independent variables. While developing the model, it was estimated that some relationships were nonlinear. Therefore, several transformations were performed, including applying the natural logarithm (ln) and the parabolic expression of the second degree, and the conditional effect of some factors was also modeled. These transformations were performed only for those independent variables for which there were reasonable theoretical assumptions regarding the possible nonlinear effect. The nonlinear effect of independent variables on growth rates was tested using the Ramsey RESET test, and if necessary (if the linearity assumption was not satisfied), appropriate transformations were performed.

Another assumption tested is that the random error of the model is not autocorrelated. It is tested using the Wooldridge test. Although statistically significant negative autocorrelation should not significantly affect the size of the standard errors, the model errors will likely be positively autocorrelated when overlapping economic growth rates are used. In the presence of positive autocorrelation, the standard errors of the coefficients may be smaller than the true ones, distorting the factors’ significance levels. In this case, the model structure will not be changed, and stabilized standard error estimates will be used to correct the influence of autocorrelation.

The third assumption tested is that the dispersion of errors must be homoscedastic. If the model errors have a variable dispersion, this may reduce the accuracy of the estimates. The assumption of homoscedasticity is tested using the Breusch–Pagan (BP2) test or the Koenker test. If the errors are heteroscedastic, they are corrected using stabilized standard errors, which take into account both heteroscedasticity and autocorrelation.

The fourth assumption requires that the model errors should not have intergroup correlation. It is checked using the Pesaran CD test. If the errors’ intergroup correlation is significant, Beck–Katz-stabilized standard errors are used to correct this problem.

The fifth assumption is that the independent variables should not have strong correlations. The multicollinearity problem can be checked using the variance invariance factor (VIF). If the VIF > 5, this may indicate that the variables are strongly correlated, distorting the effect estimates. The problem is solved by revising the model specification.

The last assumption is that the independent variables must be exogenous, i.e., they must not be correlated with the error. If the independent variables are endogenous, this may distort the model estimates. The Durbin–Wu–Hausman test is used to test endogeneity, and methods with instrumental variables (IVs) or the generalized method of moments (GMM) can be applied to solve the problem.

This study also analyzes various methods of assessing the impact of RES development on economic growth, which is integrated into the model using econometric modeling based on the analysis of economic growth factors.

4. Results

First, the estimates of all regression models were calculated using the least squares method (LSM). Then, the ${\alpha }_i$ estimates of these models were tested in order to determine their behavior and select an appropriate method of calculating the estimates. The Fisher (F) test determined that ${\alpha }_i$ is specific. The small p-value of this test (<0.0001) allows us to conclude that the MSM, which does not eliminate and model country-specific effects of ${\alpha }_i$, is not appropriate. In this case, the alternative of calculating fixed effects (FE) estimates would be more suitable. The small p-value of the Breusch–Pagan test (<0.0001) allows us to conclude that ${\alpha }_i$ are specific and vary randomly over time. This once again confirms that MKM can lead to biased parameter estimates. A more suitable alternative for calculating random effects (AE) estimates would be the generalized least squares method (GLS). The small p-value of the Hausman test, which allows us to check whether the GLS estimates are consistent (<0.0001), allows us to conclude that the GLS is inappropriate and that the FE method should be preferred. Based on the results obtained, the estimates of all models were further calculated using FE.

These models were further tested for a possible endogeneity problem. The large p-value of the Durbin–Wu–Hausman test (>0.05) indicates that the model’s independent variables are exogenous and that the FE estimates are not biased. This also suggests that all the main factors of economic growth are included in the models and that no variables that would affect economic growth and correlate with other independent variables included in the model, thus causing endogeneity, are omitted.

In the last stage, FE model errors were tested for compliance with the typically required assumptions. The Ramsey RESET test revealed that the model specifications and the data transformations applied are sufficient to make the analyzed relationships linear. The Wooldridge autocorrelation test showed that the model errors are characterized by a small but positive and statistically significant autocorrelation. As mentioned earlier, the reason for this is the overlapping economic growth rates used in this study, which result in a positively autocorrelated model error structure due to the inertia of economic growth and the fact that the economic growth rate of the previous period is a good reflection of the expectations of economic entities and is positively correlated with the economic growth rate of the subsequent period. Since the dispersion of model errors was determined to be statistically not significantly different from the normal distribution, the possible heteroscedasticity of the model errors was tested using the Breusch–Pagan test. The test results show that the dispersion of model errors is heteroskedastic, which is why the calculated conventional standard errors of models may be ineffective and inappropriate for determining the statistical significance of the estimates. The Pesaran CD test revealed that the errors are characterized by intergroup correlation. Such a situation is very likely since the EU countries under analysis are interconnected by trade, investment, and labor migration flows, and changes in economic growth in one country are related to changes in economic growth in other countries; i.e., the economic growth factor of a given EU country is weighted by the vector of economic growth rates of the remaining EU countries, where the weight depends on the strength of economic ties. As in the case of positive autocorrelation and heteroskedasticity, intergroup correlation in the errors results in ineffectiveness and is likely lower than the true conventional standard errors of model estimates. Beck–Katz-stabilized standard errors were used to solve the problem, considering the intergroup correlation, heteroscedasticity, and autocorrelation inherent in conventional model errors. All models were also tested using the variance reduction factor to check whether the independent variables were excessively correlated. The results obtained (VIF < 4) allow us to state that the models are not characterized by multicollinearity.

Having assessed the development of different energy generation capacities and countries’ investments in the latest and most expensive technologies that require the most funds—geothermal, wind, and solar energy development in total capacities—we can state that this has a statistically significant positive effect on economic growth. The development of hydropower capacity has a positive but minor impact since this is already a long-developed technology. Therefore, we can reject the proposed sub-hypothesis since the study’s results do not confirm the negative effects of the transition to renewable energy sources on the economy. It should be emphasized here that the identified positive effects differ, and, therefore, the impact of investments allocated to development will be different and will depend on the nature of the resources being developed (

Table 3. Results of testing the hypothesis (H). Dependent variable—average overlapping five-year future economic growth rates.

Number of Observations	n	337	351	325	327
Adjusted coefficient of determination	$R_{adj.}^2$	0.6722	0.6851	0.6897	0.6717
$\mathrm{Fisher} \left(\mathrm{F}\right) \mathrm{test} \mathrm{H}0: {\alpha }_1={\alpha }_2\dots ={\alpha }_i$ p-value		<0.0001	<0.0001	<0.0001	<0.0001
$\mathrm{Breusch}-\mathrm{Pagan} \left(\mathrm{BP}1\right) \mathrm{test} \mathrm{H}0: {\alpha }_1={\alpha }_2\dots ={\alpha }_i$ p-value		<0.0001	<0.0001	<0.0001	<0.0001
Hausman test H0: AMKM estimates are aligned p-value		<0.0001	<0.0001	<0.0001	<0.0001
Durbin–Wu–Hausman test H0: The independent variables of the model are exogenous p-value		0.06757	0.13628	0.09324	0.07384
Ramsey RESET test H0: the relationships between the dependent variable and the independent variables are linear p-value		0.11235	0.08251	0.11315	0.10217
Wooldridge test H0: there is no first-order autocorrelation p-value		<0.0001	<0.0001	<0.0001	<0.0001
Breusch–Pagan (BP2) test H0: the variance of the errors is homoscedastic p-value		<0.0001	<0.0001	<0.0001	<0.0001
Pesaran CD test H0: the intergroup variance of the errors does not differ from zero p-value		<0.0001	<0.0001	<0.0001	<0.0001

Source: Compiled by the authors.

; Figure 1).

Next, we will discuss the results of the hypothesis (H), which states that the transition to renewable energy sources will have a smaller negative impact on economic growth when a country is more dependent on imported energy sources. After evaluating the calculation results, we can state that when countries are more dependent on imported energy sources, their transition to renewable energy sources does not statistically affect economic growth. However, it is worth noting that the trend clearly shows that for countries with a larger share of various imported energy sources, the impact on economic growth when they switch to renewable energy sources changes from negative to positive. Therefore, we can confirm hypothesis H and conclude that implementing a transition policy to renewable energy sources is primarily beneficial for countries with a larger share of imported fossil fuels (Figure 2).

Next, hypothesis (H) was additionally tested, which states that the transition to renewable energy sources will have a minor negative impact on economic growth when the country is more dependent on imported energy sources. In this case, the calculations were made not according to the share of renewable energy but according to the renewable energy generation capacity. After evaluating the calculation results, we can once again confirm that when countries’ dependence on imported energy sources is significantly higher, the transition to renewable energy sources has a more negligible negative impact on their economies. Thus, for countries with larger renewable energy generation capacities using them in this way, the transition to renewable energy sources will have a minor impact on economic growth rather than a negative one. It should be noted that the effect is not statistically significant, but the general trend is clear. Therefore, we can consider the H hypothesis confirmed and conclude that the transition to renewable energy sources is correct for those countries that import a larger share of energy.

The experience gained over the past 20 years in implementing environmental policies in the European Union can help formulate more targeted measures to promote the use of renewable energy to boost economic growth. This is particularly important in order to achieve carbon neutrality and implement the Green Deal by 2050. The recommendations set out detail how these goals can be achieved.

First, investment in renewable energy should be encouraged. Policymakers should further develop financial incentives, such as grants, low-interest loans, and tax breaks, to encourage domestic and foreign investors to invest in this sector.

Second, a differentiated approach is needed according to the type of energy and regional characteristics. EU policies should consider that different types of energy are better suited to different geographical and climatic conditions. For example, wind energy could be promoted more in wind-rich areas such as the North Sea region, while solar energy could be promoted in Southern Europe, with more sunny days. Hydropower could also be given priority in Alpine regions, where the geographical conditions are particularly favorable for such projects. This would allow for greater energy production efficiency, considering local conditions.

Thirdly, it is essential to focus on developing the economies of those EU countries most dependent on energy imports. For example, many Eastern European countries could use local renewable energy resources to reduce their dependence on external suppliers. This would reduce their reliance on energy imports and stabilize the local economy, as energy costs remain within the country. The EU could support these countries by providing funding and promoting joint projects that would help ensure energy security and stability across the Union.

Fourth, the EU should encourage Member States to develop renewable energy strategies adapted to local climate conditions.

Fifth, as the renewable energy market grows, there is a risk that significant investments in this sector will not generate the expected returns. In order to avoid market saturation and ensure economic benefits, indicators should be introduced to measure the impact of investments on the economy. These indicators help determine when subsidies and incentives should be adjusted to ensure the sustainability and efficiency of investments.

Sixth, strategic planning is essential to achieve the EU’s renewable energy targets. The European Union should establish long-term objectives for renewable energy development and integrate them into national planning processes. This would include milestones for renewable energy production and consumption, which would be incorporated into the broader EU environmental and economic policies. These long-term objectives would ensure investment stability and predictability, encouraging private investment in the renewable energy sector.

Seventh, focusing on specific sectors where renewable energy can be increased is also essential. For example, the transport sector could be used to promote the use of electric vehicles, and public buildings’ heating and cooling systems could be used to increase the use of renewable energy. Each sector requires solutions that consider different energy uses and the possibilities for integrating renewable sources.

Policymakers should focus on investment promotion, regional adaptation, reducing energy imports, exploiting local climate conditions, efficient investment management, long-term planning, and sector adaptation to ensure sustainable renewable energy development.

5. Discussion

Several studies reviewing the various renewable energy promotion measures in the European Union provide a solid basis for the proposed recommendations. The main research findings that support these measures are presented below.

Promoting investment in renewable energy: A study by [58,59,60,61] highlights the effectiveness of fiscal and financial instruments, such as tax breaks, grants, and low-interest loans, in promoting the development of renewable energy sources in the EU. This study showed that these instruments were more effective than other incentives, thus justifying the proposal to expand financial incentives for the renewable energy sector. This would create better conditions for more significant investment in renewable energy, as foreseen in the EU climate objectives.

Differentiated approach by energy type: A study by [62,63] found that incentive mechanisms based on incentives per kilowatt-hour produced are more effective than rebates for investments in generation capacity. This suggests that policies should be tailored to the specific technological characteristics of renewables. For example, wind energy projects should be promoted in wind-rich regions, and solar energy projects should be promoted in sunny areas. Such differentiated policies would ensure the efficient and sustainable use of renewable energy.

Focus on economies with high import dependence: References [64,65,66] also highlights the importance of fossil fuel consumption and GDP for developing renewable energy. Regions that are dependent on energy imports could increase the development of local renewable energy sources, thereby reducing their dependence on external suppliers and ensuring energy security. This study confirms that energy independence is essential in promoting the development of renewable energy sources in the EU.

Adaptation to local climate conditions [67,68]: Although no study directly analyses policies’ adaptation to local climate conditions, the literature broadly supports strategies that rely on regional specificities. Adapting renewable energy strategies to local climate conditions and geographical contexts is a key factor in increasing the efficiency of energy production. For example, solar energy may be a priority in warm regions, while wind and hydropower are a priority in cold and windy regions.

Addressing the issue of diminishing returns on significant investments [69]: While no research directly addresses this issue, a common theme across research suggests that managing the scale of investment is essential to optimize economic returns. As the renewable energy sector expands, monitoring investments and adjusting incentives based on economic impact indicators is necessary to avoid market over-saturation and ensure sustainable development.

Long-term-planning [70,71]: While no research directly analyses the impact of long-term goals on renewable energy policies, most research studies support the view that long-term planning increases policy effectiveness. By setting clear long-term targets and integrating them into national plans, the EU can ensure stability and predictability, which in turn will encourage both public and private investment in the renewable energy sector.

Impact on individual sectors [72,73,74,75,76,77]: Studies show that sectoral initiatives are crucial to achieving sustainable energy consumption. Differentiated policy measures tailored to each industry can increase efficiency and reduce costs, which would encourage greater integration of renewable energy into different sectors.

Although not all directly address specific aspects, these studies confirm the main recommendations for promoting renewable energy, highlighting the importance of applying balanced, strategic, and region-specific policy measures to achieve maximum impact.

6. Conclusions

• Using renewable energy sources to produce electricity is very important to reduce carbon dioxide emissions. RESs are a part of the energy supply that reduces greenhouse gas emissions and meets the European Union’s (EU) commitments under the Paris Agreement on Climate Change and the EU Energy and Climate Programme for 2030. Furthermore, renewable energy production has a vital role in increasing the security of energy supply, technological development, and sustainable energy at affordable prices while ensuring health, environmental, and social benefits and increasing job creation opportunities.
• The transition to renewable energy sources has a statistically significant positive impact on economic growth, especially when focusing on advanced renewable technologies like wind, solar, and geothermal energy. These effects are particularly pronounced in countries that invest heavily in modern renewable infrastructure, while the impact of hydropower is less significant due to its maturity as a technology.
• The transition to renewable energy sources has a more substantial positive effect on economic growth for countries highly dependent on imported fossil fuels. For such countries, reducing import dependency by increasing renewable energy capacity mitigates the economic risks associated with fluctuating fossil fuel prices and supply chain vulnerabilities.
• Effective renewable energy integration requires tailoring strategies to the geographical and climatic conditions of specific regions. For instance, wind energy should be prioritized in wind-abundant areas like the North Sea, solar energy should be prioritized in sun-rich Southern Europe, and hydropower should be prioritized in mountainous regions. This differentiated approach ensures the efficient utilization of renewable resources and maximizes economic benefits.
• This study also analyzed various methods of assessing the impact of RES development on economic growth, which were integrated into the model using econometric modeling based on the analysis of economic growth factors. Here, the hypothesis “H: the transition to renewable energy sources will have a smaller negative impact on economic growth when the country is more dependent on imported energy sources” was formulated.
• The hypothesis was accepted, and this means that using renewable energy sources not only contributes to environmental goals and climate change mitigation but also provides various economic benefits, including job creation, lower energy prices, greater energy security and long-term sustainability. It is essential in the transition to a cleaner and more sustainable economy.
• Further research should focus on optimizing the transition to renewable energy sources by exploring advanced technologies, innovative policies, and tailored regional strategies. Investigating how to enhance the efficiency and cost-effectiveness of wind, solar, and geothermal energy systems could unlock their full potential, particularly in regions with abundant natural resources. Additionally, studies should examine the socioeconomic benefits of renewable energy integration, including its role in job creation, technological innovation, and improved public health outcomes. Future research should also prioritize the development of comprehensive models to better assess the economic impact of renewable energy investments, especially in countries heavily reliant on imported fossil fuels. These models should incorporate the evolving dynamics of energy markets, geopolitical factors, and the varying maturity levels of renewable technologies. Furthermore, interdisciplinary approaches combining economics, environmental science, and policy analysis will be crucial to identify pathways for maximizing the benefits of renewable energy while minimizing potential trade-offs.