Sustainable financing for renewable energy: Examining the impact of sectoral economy on renewable energy consumption

Getachew, Edosa; Lakner, Zoltán; Desalegn, Goshu; Tangl, Anita; Boros, Anita Article Sustainable financing for renewable energy: Examining the impact of sectoral economy on renewable energy consumption Economies Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Getachew, Edosa; Lakner, Zoltán; Desalegn, Goshu; Tangl, Anita; Boros, Anita (2024) : Sustainable financing for renewable energy: Examining the impact of sectoral economy on renewable energy consumption, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 12, Iss. 6, pp. 1-16, https://doi.org/10.3390/economies12060127 This Version is available at: https://hdl.handle.net/10419/329053 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Citation: Getachew, Edosa, Zoltan Lakner, Goshu Desalegn, Anita Tangl, and Anita Boros. 2024. Sustainable Financing for Renewable Energy: Examining the Impact of Sectoral Economy on Renewable Energy Consumption. Economies 12: 127. https://doi.org/10.3390/ economies12060127 Academic Editor: Angeliki N. Menegaki Received: 10 April 2024 Revised: 29 April 2024 Accepted: 16 May 2024 Published: 21 May 2024 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). economies Article Sustainable Financing for Renewable Energy: Examining the Impact of Sectoral Economy on Renewable Energy Consumption Edosa Getachew 1,2 , Zoltan Lakner 1, Goshu Desalegn 1,3,* , Anita Tangl 4and Anita Boros 5 1School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences, 2100 Godollo, Hungary; [email protected] (E.G.); lakner[email protected] (Z.L.) 2Department of Banking & Finance, College of Business and Economics, Wallaga University, Nekemte P.O. Box 395, Ethiopia 3 Department of Accounting and Finance, Faculty of Business and Economics, Kotobe University of Education, Addis Ababa P.O. Box 5563, Ethiopia 4School of Management and Business Administration, John von Neumann University, 6000 Kecskemét, Hungary; [email protected] 5Circular Economy Analysis Center, Hungarian University of Agriculture and Life Sciences, 2100 Godollo, Hungary; [email protected] *Correspondence: [email protected] Abstract: This study examines the effect of international financial flows, including investments and development assistance, on the expansion of renewable energy technologies. It also seeks to investigate the impact of the sectoral economy on the proportion of renewable energy consumption in Ethiopia. This study used an explanatory research design and a quantitative research approach. An autoregressive distributed lag model was applied to explore the long and short-term relationship among variables. A time series of data aggregated and disaggregated ranging from 2000 to 2022 was used. According to this study, sustainable finance programs are essential for advancing and aiding renewable energy projects in the long and short term. Ethiopia’s use of renewable energy will increase as sustainable finance rises. The main economic sectors determining Ethiopia’s consumption of renewable energy in the long and short term include the manufacturing, mining and service industries. This study’s findings imply that policies focusing on providing continuous financial support and fostering international cooperation to promote the development of the manufacturing sector are needed. This could include incentives for adopting renewable energy technologies and investing in renewable energy infrastructure. On the other hand, since the service and mining industries negatively impact renewable energy use, there is a need to diversify renewable energy sources beyond these sectors. This could involve promoting renewable energy projects in other sectors, such as manufacturing, agriculture, construction and trade. Based on the findings of this study, it is suggested that policymakers carefully consider the consequences within each economic sector when formulating decisions related to renewable energy. This study is novel in presenting empirical evidence linking renewable energy use to longand short-term economic growth. Keywords: sustainable financing; renewable energy; sectoral economy; financial flow; renewable energy consumption; Ethiopia 1. Introduction Advancing sustainable development goals, mitigating greenhouse gas emissions and fulfilling future energy demands have become a top concern worldwide, necessitating substantial financial commitments (Liu et al. 2021;Boston et al. 2021). As part of sustainable development goals, providing sustainable energy is a principal objective for many countries (Michaelowa et al. 2021). There is, however, the need to improve current financing levels and economic contributions to promoting sustainable energy (Clark et al. 2017). It is argued by Chan et al. (2019) that the Sustainable Development Goals and the Paris Climate Change Economies 2024,12, 127. https://doi.org/10.3390/economies12060127 https://www.mdpi.com/journal/economies Economies 2024,12, 127 2 of 16 Agreement need help to access enough funds. The Sustainable Development Goals and the Paris Agreement provide a roadmap for effective climate action (Chong 2018). However, they do not clearly define responsibilities or drive states to fulfill extraterritorial obligations. This issue is of considerable importance because the consumption of renewable energy sources in the sectoral economy depends on adequate financing. In this regard, many countries use different initiatives to increase funding for sustainable development goals and renewable energy projects. One of the initiatives that many developed countries mostly use to promote the transition to clean energy is through private investment mobilization. However, this initiative faces more significant constraints in developing countries. Apart from the issue of private investment mobilization, there are also many constraint hindering the expansion of renewable energy expansion across developing countries. These constraints include the implementation of domestic policies about renewable energy, the accessibility of global public funding and the broader commercial landscape (Chen et al. 2021). Although the global expansion of renewable energy faces significant challenges, there are numerous economic sectors that heavily rely on the services provided by renewable energy sources. Many studies conducted across the globe show that a substantial amount of renewable energy consumption is attributed to different economic sectors, such as the banking sector, transportation, residential buildings and commercial services (AmuakwaMensah and Näsström 2022;Le et al. 2020;Doytch and Narayan 2021;Iskandarova et al. 2021;Maji and Adamu 2021). More specifically, some studies highlight the association between real GDP per capita and the utilization of renewable energy (Simionescu et al. 2020;Altunkaya and Özcan 2020;Iskandarova et al. 2021). Within the specific context of Ethiopia, renewable energy sources, including solar, hydro, wind and geothermal, possess considerable capacity to stimulate economic expansion (Njoh 2021). Despite this potential, statistics reveal that 95 percent of total energy consumption in Ethiopia is derived from renewable sources. However, insights from a study conducted by Hailu and Kumsa (2021) underscore a significant challenge: a large part of Ethiopia’s population resides in areas with limited energy sources. This is a result of the proportion of the population that lives in urban and rural areas. The energy distribution in Ethiopian rural areas is still very limited, as the expansion of renewable energy in rural areas is more costly compared to that in urban areas. To support this argument, the study by Fu et al. (2024) suggests that deploying renewable energy constructions in rural compared to urban areas has different economic costs and benefits. This is mainly related to passive distribution networks that may no longer meet modern agricultural electrification and cleanliness requirements in rural areas, and this would necessitate urgent distributed energy planning in rural areas that could lead to high economic costs compared to urban areas. This has resulted in a distinctive scenario for the people of Ethiopia (Girma 2016). Although Ethiopia has taken a leading role in climate policy among low-income nations, its progress in rural development remains challenged, as highlighted by Paul and Weinthal’s (2019) analysis. More specifically, renewable energy consumption has slowly decreased in recent years, and these potential energy sources have faced barriers to broader adoption. These challenges include a complex and restrictive financing scheme by the Renewable Energy Fund (REF) (Kotu 2012), the lack of a subsidy policy (Hailu and Kumsa 2021), insufficient institutional cooperation among stakeholders (Tiruye et al. 2021) and limited public awareness about renewable energy technologies (Hameer and Ejigu 2020). Hence, addressing these obstacles is important (Belay Kassa 2019) because renewable energy expansion can diminish carbon emissions and stimulate sustainable economic expansion in Ethiopia (Adinew 2020). Despite numerous studies conducted to explore the challenges and potential of expanding renewable energy in Ethiopia, there has still been a significant reduction in renewable energy consumption. This reduction could be attributed to either an increase in demand or a decrease in supply. Therefore, further studies are needed to understand the factors behind the decline in renewable energy consumption. In doing so, the study at hand primarily focuses on the quantitative aspects of the economy, specifically examining the Economies 2024,12, 127 3 of 16 level of financial support provided for the expansion of renewable energy technologies that deliberately increase supply. Therefore, this study is motivated by the need to understand the sectoral economic factors contributing to the decline in Ethiopia’s renewable energy consumption and to explore the impact of international financial resources on renewable energy development in the country. Hence, this study investigates the effect of sustainable finance and the sectoral economy on Ethiopia’s renewable energy consumption. This study uses a benchmark from the United Nations Industrial Development Organization’s economic sector categorization system. The industries used in this study as part of the sectoral economy are manufacturing, agriculture, construction, hunting, forestry, transportation, fishing, mining, utilities, wholesale and retail commerce, dining establishments, lodging, storage and communication. All economic sectors are measured by their value added to the economy as a proportion of the GDP. Additionally, the target variable of this study, sustainable finance, is measured by the annual international financial flows funded for supporting clean energy research and development. The dependent variable of this study, renewable energy consumption share, is calculated as the quantity of renewable energy utilized in the total energy supply for each year. Apart from the sectoral economic contribution, the research includes aggregate data on economic growth as a control variable. Based on this information, this study examines the relationship between each variable. This study is novel in several ways. Initially, it fills a significant gap in the literature by exploring the relationship between sustainable finance, the sectoral economy and Ethiopia’s renewable energy consumption. Previous studies have not examined this relationship or provided empirical evidence. Additionally, this study uses a benchmark from the United Nations Industrial Development Organization’s sector categorization system to analyze various sectors’ contributions to Ethiopia’s economic decline in renewable energy consumption. Second, this study contributes to the existing knowledge on renewable energy utilization in Ethiopia by providing novel findings in these areas. 2. Literature Review 2.1. Sustainable Finance and Renewable Energy Finance for renewable energy has recently become very popular to meet the growing global need for clean energy resources while minimizing environmental effects. More substantial investments in clean energy resources are needed (Qadir et al. 2021). However, there must be more clarity between the literature’s point of view on funding mechanisms and their importance. Most research in developed nations focuses on market-based policy tools, with few exploring the public and private sectors’ direct financial flows ( Elie et al. 2021 ). Successful renewable energy financing innovation demands deeper comprehension of the correlation between various types of finance and investors’ willingness to make renewable energy investments (Apergis 2019). Many countries like Poland, the Netherlands and the United Kingdom (Sovacool 2021; Le et al. 2020) have developed different platforms to finance renewable energy (Iskandarova et al. 2021). As per Kim (2020), Iskandarova et al. (2021) investigated the influence of these platforms on renewable energy. Studies by Tsao et al. (2021) and Bohland and Schwenen (2022) emphasized the temporal nature of subsidization and exposed disputes and tensions in funding, including coverage gaps and disputes among stakeholder groups. In addition to providing valuable insight into renewable energy distribution, innovation and policymaking (Donastorg et al. 2022;Dinçer et al. 2021), mobilizing financing for renewable energy in developing countries is necessary (Isah 2019). Recent attention has been directed toward renewable energy financing, owing to the imperative for heightened investment in clean energy to address global demand while mitigating environmental consequences (Qadir et al. 2021). In actuality, there is a difference in funding strategies. Few studies have examined the public and private sectors’ role in directly financing market-based policies in developed and emerging nations (Vogeler 2019;Elie et al. 2021). As a result, these financing methods have received less attention in the global market Economies 2024,12, 127 4 of 16 because only some studies have examined this topic (Mullins and Walker 2009;James 2019;Apergis 2019). Another method to promote renewable energy finance is carefully considering pricing, capacity and financing policies when boosting renewable energy investments via institutions financing them (Tsao et al. 2021). Renewable energy funds have traditionally underperformed and lack market timing, implying low financial attractiveness (Elie et al. 2021) . Several financing options have become available for renewable energy investments (Altunkaya and Özcan 2020;Packham 2021), including crowdfunding, green bonds and green loans. Studies have examined financing and subsidies in different countries, revealing shifts in funding patterns and an increase in the number of financial actors (Iskandarova et al. 2021). However, the consumption and expansion of renewable energy patterns have not yet been investigated. Based on this fact, this study develops the following hypothesis: H1: Sustainable finance positively and significantly affects renewable energy consumption. 2.2. Sectoral Economy and Renewable Energy Several studies have examined how sectoral economies influence renewable energy consumption. Amuakwa-Mensah and Näsström (2022) emphasize that the service sector is one factor that impacts renewable energy usage. The study’s findings imply that a robust banking system with a large bank size, high asset quality and high managerial efficiency consumes more energy than other economic sectors. Maji and Adamu (2021) conducted another study to examine the connection between renewable energy and manufacturing performance and their effect on the environment. The study’s conclusions suggest that renewable energy degrades the environment negatively and reduces ecological footprints (Usman et al. 2021), and manufacturing performance is affected asymmetrically by sectoral energy consumption (Adekoya et al. 2021). In their study, Komarnicka and Murawska (2021) found that the transport sector exhibits the highest energy consumption, trailed by the industrial sector and households, thus resulting in elevated energy usage. According to Anton and Nucu (2020), financial development in the European Union, including the banking sector, the bond market and the capital market, contributes to a positive increase in renewable energy consumption. Commercial and public services are the sectors with the most minor consumption (Komarnicka and Murawska 2021;Adekoya et al. 2021;Zhong et al. 2021). Alternatively, foreign direct investment (FDI) generally decreases the consumption of non-renewable energy and augments the usage of renewable energy (Doytch and Narayan 2016). Using renewable energy in the US reduces carbon footprints but has a detrimental effect on environmental deterioration (Usman et al. 2021). International investment in renewable energy is constrained by the requirement for increased investment in renewable energy infrastructure and the substantial expenses associated with connecting to power grids (Ahmed et al. 2021; Rudkovskyy 2020). Romanian electricity systems have seen a significant rise in renewable energy-based generation capacity, resulting in lower usage of renewable energy (Jijie et al. 2021;Ciupageanu et al. 2021). Within developing nations, renewable energy consumption is influenced by the agricultural, industrial and energy sectors, whereas the service sector tends to diminish its usage (Mehedintu et al. 2021;Sarkodie 2021). The funding of renewable energy efforts in Ethiopia is influenced by several problems, including the country’s anti-private business climate, a lack of technical expertise and a shortage of both competent people resources and financial resources (Simionescu et al. 2020;Njoh 2021). Environmental and institutional factors, encompassing political, economic, social, technological, ecological, cultural and historical dimensions, impact the nation’s utilization of renewable energy sources (Raikar and Adamson 2020). Ethiopia possesses untapped renewable energy resources, supported by indigenous knowledge and government dedication, which enable renewable energy production and consumption (Asratie 2021;Scarpellini et al. 2021). The renewable energy resources in Ethiopia, including solar, wind, hydropower and biomass, were investigated in a study titled “A Review of Economies 2024,12, 127 5 of 16 Renewable Energy Scenario in Ethiopia” by Tahiru et al. (2023). The study highlights Ethiopia’s considerable potential for renewable energy production, particularly emphasizing wind and hydropower resources. Ethiopian grid-connected solar PV systems are feasible, according to research by Kebede (2015), which focuses on the systems’ financial sustainability. Based on a financial feasibility analysis of various solar PV system sizes, Ethiopian power generation can find a cost-effective solution in solar energy. Nevertheless, these studies cannot examine Ethiopia’s tendency to use renewable energy. The relationship between sustainability, the role of the private sector and the use of renewable energy sources cannot be examined concurrently by the research. Hence, this study is novel in providing fresh empirical evidence in favor of the variables’ link. In light of this fact, this study develops the following hypotheses. Additionally, the following Figure 1of the study shows the conceptual framework used to develop the relationship between variables. H2: The sectoral economy positively and significantly affects renewable energy consumption. H3: Economic growth positively and significantly affects renewable energy consumption. Economies 2024, 12, x FOR PEER REVIEW 5 of 16 The funding of renewable energy efforts in Ethiopia is influenced by several problems, including the country’s anti-private business climate, a lack of technical expertise and a shortage of both competent people resources and financial resources (Simionescu et al. 2020; Njoh 2021). Environmental and institutional factors, encompassing political, economic, social, technological, ecological, cultural and historical dimensions, impact the nation’s utilization of renewable energy sources (Raikar and Adamson 2020). Ethiopia possesses untapped renewable energy resources, supported by indigenous knowledge and government dedication, which enable renewable energy production and consumption (Asratie 2021; Scarpellini et al. 2021). The renewable energy resources in Ethiopia, including solar, wind, hydropower and biomass, were investigated in a study titled “A Review of Renewable Energy Scenario in Ethiopia” by Tahiru et al. (2023). The study highlights Ethiopia’s considerable potential for renewable energy production, particularly emphasizing wind and hydropower resources. Ethiopian grid-connected solar PV systems are feasible, according to research by Kebede (2015), which focuses on the systems’ financial sustainability. Based on a financial feasibility analysis of various solar PV system sizes, Ethiopian power generation can find a cost-effective solution in solar energy. Nevertheless, these studies cannot examine Ethiopia’s tendency to use renewable energy. The relationship between sustainability, the role of the private sector and the use of renewable energy sources cannot be examined concurrently by the research. Hence, this study is novel in providing fresh empirical evidence in favor of the variables’ link. In light of this fact, this study develops the following hypotheses. Additionally, the following Figure 1 of the study shows the conceptual framework used to develop the relationship between variables. H2: The sectoral economy positively and significantly affects renewable energy consumption. H3: Economic growth positively and significantly affects renewable energy consumption. Figure 1. Conceptual framework of the study. 3. Methodology and Materials Used This study examines the effect of Ethiopia’s sectoral economy on the percentage of renewable energy consumption using both aggregate and disaggregate time series data. Ethiopia is chosen as a case study due to its abundant renewable energy resources, with most of its energy derived from renewable sources. This selection aims to offer empirical evidence for countries relying on renewable energy sources. Figure 1. Conceptual framework of the study. 3. Methodology and Materials Used This study examines the effect of Ethiopia’s sectoral economy on the percentage of renewable energy consumption using both aggregate and disaggregate time series data. Ethiopia is chosen as a case study due to its abundant renewable energy resources, with most of its energy derived from renewable sources. This selection aims to offer empirical evidence for countries relying on renewable energy sources. This study uses an explanatory research design and a quantitative research approach to investigate the relationship between dependent and independent variables. Explanatory research design is used to understand the relationship between variables, making it a suitable choice for this investigation. To enable this research, the economic sectors are divided into six categories based on commonalities, using the categorization method supplied by the United Nations Industrial Development Organization. This categorization is based on similar characters to simplify the research process. This classification aims to facilitate the study by grouping sectors with similar characteristics. This division is undertaken to facilitate this study by grouping sectors based on their common attributes. This particular categorization allows for a comprehensive examination of how each sector contributes to and influences Ethiopia’s overall consumption of renewable energy. Table 1 shows the sectoral economy used in this study. Economies 2024,12, 127 6 of 16 Table 1. Sample of sectoral economy used. Group Sectors Group Name Measurement 1Agriculture, hunting, forestry, fishing Agriculture sector Aggregate value is added to the economy as the percent of the gross domestic product. 2 Mining and utilities Mining sector 3 Construction Construction sector 4 Manufacturing Manufacturing sector 5Wholesale, retail trade, restaurants, hotels Trade sector 6Transport, storage, communication Service sector Source: Created by authors, 2024. Based on the categorization above, this research examines how the sectoral economy affects the proportion of renewable energy use. At the same time, it also attempts to look into the relationship between foreign finance flow supporting clean energy research and development and renewable energy production and renewable energy consumption. This research is entirely based on secondary data gathered from the United Nations Statistics Division (UNSD) (Energy Statistics Database) and the United Nations Industrial Development Organization (UNIDO) for sectoral economic statistics spanning the period of 2000–2022. This period is selected based on data available for both renewable energy and sustainable finance. 3.1. Variables and Measurements Used This study aims to investigate how financing and the sectoral economy affect the consumption of renewable energy share in Ethiopia. As a result, the following functional estimation is used to develop the model. All independent variables are measured as the annual value added to the economy as a percentage of GDP. RE = f (GDP, FI, IS, MIS, CS, MAS, TS, SS). RE = Renewable energy consumption share (measured as the percentage of renewable energy consumption from each year’s total energy supply). GDP = Gross domestic product (the economy’s annual growth rate at the aggregate level). FI = Financial assistance to support renewable energy investment (measured by annual international financial flows supporting clean energy research at the aggregate level). AS (agricultural sector), MIS (mining sector), CS (construction sector), MAS (manufacturing sector), TS (trade sector), and SS (service sector). All are measured by their value added to the economy as a percentage of GDP. The above functional form can be written in the econometric form as follows. Here, β 0 is the intercept. β 1– β 8 are coefficients of the independent variables, and c represents the error term of the study (variables that are not included in this study). 3.2. Model Specification The first step in choosing the best research model is determining whether the variables are stationary over time. This can be performed through different methods, but this study employs a unit root test to identify the variable’s stationarity. This procedure entails assessing the variables’ characteristics over time to see if they have a stable mean and variance. The unit root test can assess whether the variables are stationary, which is essential for proper analysis and dependable results. As a consequence, the primary purpose of this first step is to investigate the variables’ stationarity using the unit root test. Table 2shows the stationarity test results. The hypotheses guiding these tests are as follows: H0 posits the presence of a unit root in the variables, and the decision criterion Economies 2024,12, 127 7 of 16 involves rejecting H0 if the p-value (PV) is less than 0.05. On the other hand, H1 suggests the absence of a unit root in the variables. Table 2. Result of stationarity test with the ADF test. At Level At 1st Difference Decision Variables Trend and Intercept Trend and Intercept RE 0.8034 0.0071 *** I(1) GDP 0.1618 0.0042 *** I(1) FI 0.0063 *** 0.0000 *** I(0) AS 0.0023 *** 0.0008 *** I(0) MIS 0.2924 0.0158 ** I(1) CS 0.7203 0.0037 *** I(1) MAS 0.5945 0.0008 *** I(1) TS 0.3940 0.0551 * I(1) SS 0.0003 *** 0.0033 *** I(0) Source: E-views output. Note: *** implies a 1 percent significance level, ** implies a 5 percent significance level, and * implies a 10 percent significance level. The numbers given in the table show the probability of a significance level derived from the t-statistics value. As depicted in the provided table, Table 2reveals the outcomes of the stationarity test conducted on the variables. These results indicate that the variables exhibit a consistent variance and mean over time. However, they display different levels of integration. Specifically, certain variables such as gross domestic product, financial assistance, the agricultural sector and the service sector are stationary at the level, indicating a stable pattern without significant fluctuations. On the other hand, variables like renewable energy, the mining sector, the construction sector, the manufacturing sector and the trade sectors exhibit stationarity at the first difference, implying that their values undergo consistent changes over time. Considering the overall stationarity result, it can be inferred that the variables possess different degrees of integration, characterized as I(0) and I(1). This signifies that some variables maintain a constant level, whereas others experience first-order integration, necessitating an autoregressive distributed lag (ARDL) model for analysis. 3.3. Discussion of Model Used The autoregressive distributed lag (ARDL) model is the econometric technique used by this study’s researchers. The rationale for utilizing the ARDL model stems from the nature of the series under investigation, which exhibits a combination of integration orders, namely I(0) and I(1). The ARDL model allows researchers to adequately capture the dynamics of the variables under study. Yt =oi +∑p i=1αjyt −1+∑q i=1βjXt −1+εit The ARDL model estimates to test for cointegration among the variables. ∆REt =β0+β1REt −1+β2GDPt −1+β3FIt −1+β4ASt −1+β5MISt −1+β6CSt −1+β7MASt −1 +β8TSt −1+β9SSt −1+∑h aλ2∆GDP t −a+∑h bλ3∆FIt −b+∑h cλ4∆ASt −c +∑h dλ5∆IMISt −d+∑h eλ6∆CSt −e+∑h fλ7∆MASt −f+∑h gλ8∆TSt −g +∑h hλ9∆SSt −h+εt (1) The formulation of the error correction model aims to illustrate the short-term associations among the variables. Economies 2024,12, 127 8 of 16 ∆REt =β0+β1∑h ai(REt −1)+β2∑h bi(GDPt −1)+β3∑h ci(FIt −1)+β4∑h di(ASt −1) +β5∑h ei(MISt −1)+β6∑h fi(CSt −1)+∑h gλ7∆MASt −g+∑h hλ8∆TSt −h +∑h iλ9∆SSt −i+ECM (−1)εt (2) The bounds-testing approach is applied (Pesaran and Taylor 1999), which is used to examine potential cointegration among variables. The results suggest cointegration, prompting an exploration of the shortand long-term relationship. The results of test statistics for the ARDL bounds test are presented below. As indicated in Table 3, the ARDL bounds testing results suggest that the variables exhibit a long-term relationship, prompting further examination of their short-term dynamics. The F-statistics result indicates a value exceeding the threshold for I(0) and I(1), indicating a long-term relationship between the variables. This finding underscores the importance of exploring the short-term dynamics to understand the relationship between these variables fully. Table 3. Result of ARDL bounds testing. F-Bounds Test Null Hypothesis: No Levels of Relationship Test Statistic Value Signif. I(0) I(1) Asymptotic: n = 1000 F-statistic 4.559073 10% 1.85 2.85 k 8 5% 2.11 3.15 2.5% 2.33 3.42 1% 2.62 3.77 3.4. Lag Selection Criteria This study’s results indicate that the model needs a maximum lag order of one. This conclusion is consistent across all lag length selection criteria, reinforcing the validity of the result. Consequently, this study uses a single lag order when running the model. The following Table 4of the study shows lag selection criteria used in the study. Table 4. Lag selection criteria of the model. Endogenous Variables: RE GDP FI AS CS MAS MIS SS TS Exogenous Variables: C Included Observations: 21 Lag LogL LR FPE AIC SC HQ 0−600.229 NA 1.28 ×1014 58.02178 58.46943 58.11893 1−469.54 136.9123 * 2.39 ×1012 * 53.28950 * 57.76602 * 54.26102 * * indicates lag order selected by the criterion; LR: sequential modified LR test statistic (each test at the 5% level). 4. Econometric Analysis and Discussion Before conducting an econometric analysis, it is imperative to understand the data within the group thoroughly. It is clear from Table 5’s descriptive statistics that the dependent variable, renewable energy, has a mean value of 92.71 percent. This suggests that renewable energy was consumed at about 92.7 percent during the period (2000 to 2021). In addition, the highest documented consumption rate occurred in 2000 at 95.5%, whereas the lowest was reported in 2021 at 89.5 percent. The significant difference between the highest and lowest scores highlights Ethiopia’s dramatic decline in its use of renewable energy. This shows that the country’s adoption and consumption of renewable energy sources have seen noticeable fluctuation. Economies 2024,12, 127 15 of 16 Hameer, Sameer, and Netsanet Ejigu. 2020. A prospective review of renewable energy developments in Ethiopia. AAS Open Research 3: 64. [CrossRef] Isah, Abdulrasheed. 2019. A Tale of Two Countries: Financing Renewable Energy in Nigeria and Brazil. USAEE Working Paper No. 19-400. Available online: https://ssrn.com/abstract=3377029 (accessed on 10 April 2023). Iskandarova, Marfuga, Agata Dembek, Maria Fraaije, William Matthews, Agata Stasik, Julia M. Wittmayer, and Benjamin K. Sovacool. 2021. Who finances renewable energy in Europe? Examining temporality, authority and contestation in solar and wind subsidies in Poland, the Netherlands and the United Kingdom. Energy Strategy Reviews 38: 100730. [CrossRef] James, Jack E. 2019. Can public financing of the private sector defeat antimicrobial resistance? Journal of Public Health 41: 422–26. [CrossRef] [PubMed] Jijie, Dumitru-Tudor, Alexandru Maxim, Teodora Roman, and Mihail Ro s , covan. 2021. Public acceptance and support of renewable energy in the north-east development region of Romania. Energies 14: 5834. [CrossRef] Kebede, Kassahun Y. 2015. Viability study of grid-connected solar PV system in Ethiopia. Sustainable Energy Technologies and Assessments 10: 63–70. [CrossRef] Kim, Jung Eun. 2020. Regulation trumps economics? Examining renewable energy policy, diffusion and investment in 80 developing countries. Energy Research & Social Science 70: 101613. Komarnicka, Anna, and Anna Murawska. 2021. Comparison of consumption and renewable sources of energy in European Union Countries—Sectoral indicators, economic conditions and environmental impacts. Energies 14: 3714. [CrossRef] Kotu, Teshome Bekele. 2012. Renewable for rural electrification in Ethiopia. Master’s thesis, KTH School of Industrial Engineering and Management Energy Technology EGI, Stockholm, Sweden, December. Le, Thai-Ha, Canh Phuc Nguyen, and Donghyun Park. 2020. Financing renewable energy development: Insights from 55 countries. Energy Research & Social Science 68: 101537. Liu, Zhen, Jinhang Xu, Yiming Wei, Assem Abu Hatab, and Jing Lan. 2021. Nexus between green financing, renewable energy generation, and energy efficiency: Empirical insights through DEA technique. Environmental Science and Pollution Research 30: 1–14. [CrossRef] [PubMed] Maji, Ibrahim Kabiru, and Sagir Adamu. 2021. The impact of renewable energy consumption on sectoral environmental quality in Nigeria. Cleaner Environmental Systems 2: 100009. [CrossRef] Mehedintu, Anca, Georgeta Soava, Mihaela Sterpu, and Eugenia Grecu. 2021. Evolution and forecasting of the renewable energy consumption in the frame of sustainable development: EU vs. Romania. Sustainability 13: 10327. [CrossRef] Michaelowa, Axel, Stephan Hoch, Anne-Kathrin Weber, Ruth Kassaye, and Tesfaye Hailu. 2021. Mobilising private climate finance for sustainable energy access and climate change mitigation in Sub-Saharan Africa. Climate Policy 21: 47–62. [CrossRef] Mullins, David, and Bruce Walker. 2009. The impact of direct public funding for private developers on non-profit housing networks in England: Exploring a research agenda. European Journal of Housing Policy 9: 201–22. [CrossRef] Njoh, Ambe J. 2021. A systematic review of environmental determinants of renewable energy performance in Ethiopia: A PESTECH analysis. Renewable and Sustainable Energy Reviews 147: 111243. [CrossRef] Packham, Natalie. 2021. Structured climate financing: Valuation of CDO on inhomogeneous asset pools. SN Business & Economics 1: 59. Paul, Christopher John, and Erika Weinthal. 2019. The development of Ethiopia’s Climate Resilient Green Economy 2011–14: Implications for rural adaptation. Climate and Development 11: 193–202. [CrossRef] Pesaran, Hashem Mohammad, and Larry W. Taylor. 1999. Diagnostics for IV regressions. Oxford Bulletin of Economics and Statistics 61: 255–81. [CrossRef] Qadir, Sikandar Abdul, Hessah Al-Motairi, Furqan Tahir, and Luluwah Al-Fagih. 2021. Incentives and strategies for financing the renewable energy transition: A review. Energy Reports 7: 3590–606. [CrossRef] Raikar, Santosh, and Seabron Adamson. 2020. Renewable energy finance in the international context. In Renewable Energy Finance. Theory and Practice. Edited by Santosh Raikar and Seabron Adamson. Cambridge, MA: Academic Press, pp. 185–220. Rudkovskyy, Serhii. 2020. The influence of the investment factor on the transformation of the global energy market. Technology Audit and Production Reserves 4: 54. [CrossRef] Sarkodie, Samuel Asumadu. 2021. Failure to control economic sectoral inefficiencies through policy stringency disrupts environmental performance. Science of The Total Environment 772: 145603. [CrossRef] Scarpellini, Sabina, José Ángel Gimeno, Pilar Portillo-Tarragona, and Eva Llera-Sastresa. 2021. Financial resources for the investments in renewable self-consumption in a circular economy framework. Sustainability 13: 6838. [CrossRef] Simionescu, Mihaela, Wadim Strielkowski, and Manuela Tvaronaviˇcien ˙ e. 2020. Renewable energy in final energy consumption and income in the EU-28 countries. Energies 13: 2280. [CrossRef] Sovacool, Benjamin K. 2021. Clean, low-carbon but corrupt? Examining corruption risks and solutions for the renewable energy sector in Mexico, Malaysia, Kenya and South Africa. Energy Strategy Reviews 38: 100723. [CrossRef] Tahiru, Abdul-Wahab, Silas Uwumborge Takal, Emmanuel Daanoba Sunkari, and Steve Ampofo. 2023. A Review on Renewable Energy Scenario in Ethiopia. Iranica Journal of Energy & Environment 14: 372–84. Tiruye, Girum Ayalneh, Abreham Tesfaye Besha, Yedilfana Setarge Mekonnen, Natei Ermias Benti, Gebrehiwet Abrham Gebreslase, and Ramato Ashu Tufa. 2021. Opportunities and challenges of renewable energy production in Ethiopia. Sustainability 13: 10381. [CrossRef] Economies 2024,12, 127 16 of 16 Tsao, Yu-Chung, Thuy-Linh Vu, and Jye-Chyi Lu. 2021. Pricing, capacity and financing policies for investment of renewable energy generations. Applied Energy 303: 117664. [CrossRef] Usman, Ojonugwa, Andrew Adewale Alola, and George N. Ike. 2021. Modelling the effect of energy consumption on different environmental indicators in the United States: The role of financial development and renewable energy innovations. Natural Resources Forum 45: 441–63. [CrossRef] Vogeler, Colette S. 2019. Market-based governance in farm animal welfare—A comparative analysis of public and private policies in Germany and France. Animals 9: 267. [CrossRef] Zhong, Weichen, Junnian Song, Wei Yang, Kai Fang, and Xiaoyu Liu. 2021. Evolving household consumption-driven industrial energy consumption under urbanization: A dynamic input-output analysis. Journal of Cleaner Production 289: 125732. [CrossRef] Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.