Gholam Reza Ghaffari; Ahmad Sarlak; Maryam Sharifnezhad
Abstract
Renewable energies have been proposed as a key solution to combat climate change and reduce dependence on alternative fossil fuels. The development and expansion of this type of energy depends on various factors, including good governance, green financing, technological innovation, and urbanization. ...
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Renewable energies have been proposed as a key solution to combat climate change and reduce dependence on alternative fossil fuels. The development and expansion of this type of energy depends on various factors, including good governance, green financing, technological innovation, and urbanization. Investment in the aforementioned factors can help accelerate the transition to renewable and sustainable energies. The present study examined the impact of factors affecting renewable energies in ECO member countries over the period 2000 to 2024 and based on the Cross Sectional Augmented Autoregressive Distributed Lag (CS-ARDL), the relationship between the research variables has been analyzed. The results of this study indicate that good governance, green financing, and technological innovation have a positive and significant effect on renewable energy consumption, while urbanization has a negative effect on renewable energy consumption in the ECO region. Since the use of renewable energies plays an important role in sustainable development, it is recommended to prepare space for the transition towards the use of green energies by considering and promoting effective factors. IntroductionIn the contemporary era, the main focus of many economies is to achieve the Sustainable Development Goals (United Nations, Sustainable Development Goals, 2016). Achieving the Sustainable Development Goals is essential for protecting and improving the environment and the economic well-being of the world's people (Awosusi et al., 2022). For this reason, the energy consumption of societies has increased from non-renewable energy sources to renewable energy consumption (Dogan et al., 2022). Since renewable energy and energy efficiency are dependent on the macroeconomics of a country and this type of energy is effective as a powerful marketing tool for commercial investment and domestic and foreign trade, the country's dependence on non-renewable energy should be minimized and by increasing the consumption of renewable energy, the life of existing domestic energy resources should be extended, and in this way, by reducing costs, it will make a useful contribution to the relevant companies, the government, and ultimately the national economy. In addition, renewable energy consumption has been identified as a mechanism to reduce environmental degradation, so it is essential to study the determinants and main drivers of this type of energy consumption. Analyzing these drivers can help provide appropriate policies for governments and energy policymakers. Governance is one of the fundamental drivers in the application of renewable energy technology. It is also responsible for many economic, social, political, institutional, health and environmental standards (Huang et al., 2022). Since renewable energy sources have specific cycles and mainly require storage or other mechanisms to save energy, many countries cannot afford this infrastructure. For this reason, conventional methods of energy production are mostly non-renewable. This leads to a discussion about the relationship between governance and the process of production and consumption of renewable energy. On the other hand, green financing also plays an important role in achieving sustainable development. Because it includes any structured financial activity for a product or service, including facilities, debt, and investment mechanisms to encourage and develop green projects or minimize the negative impacts of projects that affect the climate (Sampen et al., 2024). Green financing in the form of green bonds is a suitable initiative for the development of clean energy and can reduce capital risk, increase investment returns, and attract international and domestic investment in the field of renewable energy (Rasoulinezhad, Taghizadeh Hessari, 2022; Liu et al., 2021). Another essential mechanism for the development and transition to renewable energy consumption is to focus on investment opportunities in technological innovations. Improving technology reduces the cost of renewable energy and ultimately increases the amount of investment in this industry. Energy storage technology, therefore, offers a practical solution to the intermittent nature of renewable energy consumption (Yao et al., 2016). As a result, investment in technological innovations is essential for the effective implementation of renewable energy deployment (Qadir, et al., 2021). In total energy production, potential losses occur at the initial stage of conversion, extraction, transmission, transportation and final consumption. Due to technological advances in renewable energy generation and distribution, there are certain synergies between renewable energy consumption and technological innovations (United Nations, 2015). Another issue that can affect renewable energy consumption is urbanization, which has received less attention in the energy-urbanization literature. To create sustainable electricity integration and manage diverse patterns in urban and rural centers, it must be considered throughout the energy transition stages (Lantz et al., 2021). Theoretically, the energy-urbanization nexus is a transition to the theory of the compact city, the theory of the urban environment, and the theory of ecological renewal (Poumanyvong and Kaneko, 2010). The focal points of these theories are that the urbanization process has changed various renewal structures and has led to energy efficiency at a rapid pace with the use of environmentally friendly tools and technology (Lantz et al., 2021). Considering the above and the situation of the member countries of the Economic Cooperation Organization, it is necessary to move towards a fully sustainable energy system. Therefore, the present study has examined the factors affecting the consumption of renewable energies in the ECO member countries and analyzed the challenges and opportunities facing this area. The innovation of the present study is: examining the simultaneous effect of four independent variables: good governance, green financing, technological innovation, and urbanization on renewable energy consumption in the eco-region, as well as using the generalized distributed lag autoregression model as an econometric model. The present study was the first of its kind in the country.Methods and MaterialsThe present study used the Cross-sectional Augmented Autoregressive Distributed Lag method to examine cross-sectional problems. This approach has been found to be more satisfactory for solving cross-sectional problems than traditional models, such as least squares mean and pooled mean group (Sun et al., 2022; Addae, Sun, & Aban, 2022). In addition, studies have shown that this approach provides a more accurate and reliable estimate for panel data (Baydoun & Aga, 2021; Huang, Chien and Sadiq, 2021). The advantage of this estimation method is its ability to detect errors that may arise from collinearity between the indicators studied in this study (Sadiq et al., 2022). In addition, Cross-sectional Augmented Autoregressive Distributed Lag (CS-ARDL) represents a significant improvement over previous methods, such as pooled averages and linear regression, especially in the field of renewable energy studies. It estimates long-run and short-run elasticity more robustly and accurately, and addresses endogeneity and serial correlation issues more effectively than previous methods. Therefore, the use of this advanced model provides insight into dynamic relationships and sets a new standard for empirical analysis in this field (Sampen, Li, & Nashia, 2024). In cross-sectional econometrics, it is generally assumed that the data used are cross-sectionally independent. This assumption, like other assumptions, may not hold, so the first step in this method, before performing any test, is to detect cross-sectional dependence or independence by examining the "cross-sectional dependence test" and the "slope homogeneity or heterogeneity test". The reason for using the "cross-sectional dependence test" is to identify and solve the challenges of panel data, including residual interdependencies and unobserved parameters (Ngong et al., 2022), so the "cross-sectional dependence test" includes the corrected standard test of Pesaran (2007) and the Baltaji test (Baltagi, Feng, Kao, 2012) with a corrected scale and the standard test of Brosch and Pagan, and the "slope homogeneity or heterogeneity test" uses the Pesaran and Yamagata test (2008). In general, if the statistical value of the computational “test of cross-sectional dependence” at a certain significance level is greater than the critical value of the standard normal distribution, then the null hypothesis is rejected and cross-sectional dependence is confirmed (Pesran, 2004). If cross-sectional dependence is confirmed in the panel data, the second step is to examine the stationarity or calculate the unit root and then examine the cointegration. Using conventional panel unit root methods such as the Levine, Lin and Cho and Im, Pesran and Shin tests will increase the probability of false unit root results. To overcome this problem, multiple panel unit root tests with cross-sectional dependence have been proposed, including Pesran (Pesran, 2007). In this test, if the unit root test statistic is greater than the critical values, the null hypothesis (non-significance of the variable) will be rejected and the stationary variable will be accepted. The third step is to examine panel cointegration. Using conventional panel cointegration methods such as Pedroni (1996) and Kao (2006) will increase the probability of false cointegration results (Asadzadeh and Jalili, 2015). To solve this problem, the present study has used the method proposed by Westerland (2007). The null hypothesis of this test is the absence of a cointegration relationship, and if the null hypothesis is rejected, the variables will have a cointegration relationship. Finally, to determine the accuracy and precision of the estimation of the generalized distributed autoregressive model with cross-sectional lags, the generalized mean test (Eberhart and Bond, 2009) and the commonly correlated mean effect test (Chodik and Pesaran, 2013) were used. Similar to the original generalized distributed autoregressive model with cross-sectional lags, these tests examine the errors created by the “slope homogeneity or heterogeneity test” and the “cross-sectional dependence test”, including the correlation between indicators. Also, in addition to providing consistent and accurate predictions, these tests address multicollinearity, autocorrelation, and endogeneity issues with panel data (Aday et al., 2022; Rahman et al., 2022). The D-H causality test (Dumitrescu and Hurlin, 2012) was used to assess the interaction of the causal relationships of the parameters. In many studies, this test has been used to examine causal relationships between series (Chen et al., 2022-Islam, 2022).Results and DiscussionIn a world facing serious challenges such as climate change and limited fossil resources, the use of renewable energies has been proposed as a promising solution to achieve sustainable development, but the development and expansion of this type of energy depends on several factors, among which good governance, green financing, technological innovation and urbanization are of particular importance. For this purpose, the present study discussed and examined the impact of good governance, green financing, technological innovation and urbanization on the consumption of renewable energies in the ECO area. The adjusted model was estimated using annual data using the autoregressive method with generalized distributed lags (CS-ARDL) for the period 2000 to 2024. The results of the estimation indicate that the rule of law can be useful for reducing overall energy consumption in ECO member countries. Because a stronger regulatory regime imposes more restrictions on the energy sector and limits the use of various energy sources. This result is consistent with the studies of Mahmoud et al. (2021) and Wang and Dong (2022). Therefore, ECO member countries should focus on improving good governance and pursuing policies to control and limit non-renewable energy in the region. These measures will help reduce the use of non-renewable energy and improve the environment. On the other hand, green financing has a positive impact on renewable energy consumption in ECO member countries. In other words, increasing domestic credit through financial assistance from commercial banks and insurance companies provides investment through loans with long-term repayment and low interest to finance renewable energy projects. The use of crowdfunding and cooperatives can effectively fill the financing gap in the deployment of renewable energy sources. This result suggests that the financial system in ECO member countries can promote the financing of renewable energy consumption. This finding is consistent with the findings of Saadawi and Chetorou (2022), but contradicts the findings of Mukhtarov et al. (2020). Also, policymakers should emphasize the importance of investing in cleaner technologies and increasing R&D spending in renewable energy production due to the increasing digitalization, the Fourth Industrial Revolution, and artificial intelligence in the contemporary era. Furthermore, since technological innovation in cleaner energy sources is capital-intensive and requires huge financial support, this study suggests that ECO member countries should create the necessary governance channels and a conducive environment to attract other relevant stakeholders to invest in renewable energy consumption. This enabling environment includes inviting academic institutions to participate in the development of smart energy grids for current and future needs and risk consultants to assess the threat of such investment opportunities in renewable energy technologies. The research findings also showed that urbanization has an adverse effect on renewable energy consumption. Hence, city authorities should focus on expanding the use of electric vehicles, energy-efficient public transport systems and alternative fossil fuels for cars in cities. Urban planners and the government should implement appropriate awareness-raising measures to educate city residents about the necessity of using cleaner energy sources and maintaining a healthy environment.ConclusionThe use of renewable energy is crucial to achieving sustainable development goals and eliminating environmental pollution. Extensive studies such as this one can help create a more constructive debate on this issue and transform the energy industry of ECO member countries. To achieve a sustainable future and reduce dependence on fossil fuels, improved governance, green financing, technological innovation and urbanization in the field of renewable energy are essential. By strengthening the aforementioned factors, a clean, efficient and sustainable energy system can be achieved.AcknowledgmentsFinally, I would like to thank my beloved wife and my hardworking children who have chosen the path of education and refinement in their lives with me. I would also like to express my gratitude to the esteemed editorial staff of this prestigious magazine, who work to increase the knowledge of the educated people of this country.
Pparisa Moghadasi; Sajjad Faraji Dizaji; Abbas Assari Arani
Abstract
Income inequality is a critical economic issue that can destabilize socio-economic systems by impacting public health and economic resilience. This study investigates the role of good governance in mitigating the effects of COVID-19 on income inequality in oil-exporting countries, employing a panel ...
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Income inequality is a critical economic issue that can destabilize socio-economic systems by impacting public health and economic resilience. This study investigates the role of good governance in mitigating the effects of COVID-19 on income inequality in oil-exporting countries, employing a panel data model from 2000 to 2021. The analysis includes countries exporting over 50,000 barrels of oil daily, categorized into three groups by oil rent share in GDP. The independent variables encompass oil and gas rent, stringency index, population density, unemployment rate, good governance, an interaction term of good governance and COVID-19, and COVID-19 death rate. Findings indicate that the good governance-COVID-19 interaction significantly reduces income inequality in the first and third groups, with a negative effect on the Gini coefficient. However, in the second group—characterized by the highest oil rent—good governance does not mitigate the inequality impact of COVID-19-related deaths.
Introduction
The onset of 2020 marked the beginning of a global health crisis, with the COVID-19 pandemic significantly impacting economic sectors such as tourism, trade, capital markets, and currency stability. To contain the virus, governments increased health expenditures and offered financial support to households and businesses, funded through budget reallocations or tax adjustments. The pandemic’s effects varied among countries, influenced by differences in economic, political, cultural, and social structures, as well as governance responses (Nasseri et al., 2016).
In oil-dependent economies, natural resource rents—derived from foreign exchange earnings and foreign aid—exert a profound influence on institutional quality and governance. High oil rents contribute to a government’s financial independence from internal economic performance, potentially undermining good governance. Given the crucial role of governance, assessing public trust and the effectiveness of governance during the COVID-19 pandemic is essential, particularly regarding income inequality in oil-exporting countries (Dizaji, 2014; Dizaji & Ghadamgahi, 2018).
This research investigates the interactive effect of good governance and COVID-19 on income inequality in oil-exporting nations. In these countries, where budgets heavily depend on oil revenues, tax collection efforts may be deprioritized, reducing the efficiency of tax systems (Dizaji et al., 2023).
Methods and Material
This study uses an analytical-descriptive approach, employing a generalized linear model (GLM) for panel data to analyze the interactive effect of COVID-19 and governance on income inequality. Data were sourced from the World Bank, WHO, SWIID, Our World in Data, and OPEC. The study categorizes oil-dependent countries into three groups based on oil rent as a share of GDP:
First group: Countries with oil rent below 0.1% of GDP, including Australia, Sweden, the Netherlands, and others.
Second group: Countries with oil rent exceeding 10% of GDP, including Angola, Russia, Iran, and others.
Third group: Countries with oil rent between 0.1% and 10% of GDP, including Mexico, Brazil, China, and others.
Results and Discussion
The model presented in this paper is based on Mousavi Jahromi et al. (2013) and Su et al. (2022). We use oil rent, good governance, death rate resulting from COVID-19, stringency_index, unemployment rate, and population density as control variables in our model. In order to investigate whether good governance has been effective in reducing the adverse effects of COVID-19 on income inequality or not, the interactive variable of the product of the death rate from COVID-19 and good governance has been used.
GINI=
As can be seen, the coefficient of good governance is negative for all three groups of countries. This means increased good governance, can decrease income inequality, which is consistent with the results of past researches.
Table 1 GLM model estimation results
First Group
The explanatory variables
Coefficient
z statistic
Possibility
POPULATION_DENSITY
0/001351
11/56046
0/0000
GG
-4/302316
-8/865396
0/0000
STRINGENCY_INDEX
0/228148
1/772713
0/0763
UNEMPLOYMENT
-0/242954
-2/100441
0/0357
GG*COVIDDEATH
-0/000304
-0/398861
0/6900
COVIDDEATH
-12/02037
-1/675971
0/0937
Second Group
The explanatory variables
Coefficient
z statistic
Possibility
POPULATION_DENSITY
0/050317
5/607696
0/0000
GG
-0/000109
-0/784517
0/4327
STRINGENCY_INDEX
-0/018377
-0/089050
0/9290
RENT
0/388662
7/323428
0/0000
UNEMPLOYMENT
-0/241551
-1/330671
0/1833
GG*COVIDDEATH
0/001313
0/457576
0/6473
COVIDDEATH
2/248878
0/190813
0/8487
Third Group
The explanatory variables
Coefficient
z statistic
Possibility
POPULATION_DENSITY
-0/004998
-2/011478
0/0443
GG
-5/515814
-11/25881
0/0000
STRINGENCY_INDEX
-0/041721
-0/289228
0/7724
RENT
-0/462772
-3/916503
0/0001
UNEMPLOYMENT
0/662014
8/476852
0/0000
GG*COVIDDEATH
-0/001835
-0/881103
0/3783
COVIDDEATH
1/006094
0/111800
0/9110
* Research findings using Eviews software
The coefficient of the stringency index for countries of the second and third groups is negative, which means that increased stringency can decrease income inequality. But in the countries of the first group, the coefficient of stringency is positive, which means increased stringency can increase income inequality.
The interactive variable Corona × good governance has a negative and insignificant effect on income inequality in the first and third group countries and a positive and insignificant effect on the second group countries.
Conclusion
The results indicate that good governance in oil-exporting countries has effectively mitigated the adverse effects of the COVID-19 pandemic on income inequality. High-quality governance fosters public trust, enabling governments to respond more effectively to crises. Thus, nations with stronger governance frameworks have shown greater success in addressing COVID-19’s challenges and minimizing its negative impact on income disparities. This emphasizes the critical role of governance quality in managing socio-economic crises and maintaining equality.
