Does energy intensity correlate with economic growth and government governance?

This study examines the relationship between energy intensity, economic growth, and government governance. The estimated number of countries is 182 countries, divided into three groups, namely high-income countries, middle-income countries, and low-income countries. The variables studied are energy intensity, renewable energy consumption, economic growth and government governance. Government governance is measured by government effectiveness and regulatory quality. Data is processed through correlation and comparison analysis. Research findings show that energy intensity during the pandemic was higher than in 2019, even though economic growth experienced a contraction on average. Based on country groups, there are significant differences in energy utilization where high-income countries are more efficient in energy use than other groups as indicated by a significance value <0.05. In general, energy intensity is positively correlated with economic growth, and negatively with government governance as indicated by a significance value of <0.01. The correlation between energy intensity and economic growth is in the low category with a correlation value of 0.19, while the correlation between energy intensity and government governance is in the moderate category with a correlation value of -.41 for government effectiveness, and -.42 for regulatory quality. The better the governance, the more efficient the use of a country’s energy. These findings recommend the importance of governance in encouraging energy efficiency efforts.


Introduction
Energy efficiency is closely related to the Sustainable Development Goals (SDGs) targets, namely: sustainable consumption and production patterns (SDGs-12), and immediate action to combat climate change and its impacts (SDGs-13).The government is an institution that can control the impacts of climate change through effective regulations, so that it can encourage effective institutions for sustainable development goals, in line with the SDGs-16 targets.Furthermore, efficient use of energy as a limited resource will support sustainable economic growth as per SDGs-8.Previous studies show that the level of efficiency increases with an increase in economic growth of 6% [1].Economic growth reduces energy intensity for high-and upper-middle-income countries, but not for lower-middleincome countries [2].Renewable energy can be a solution promoted by energy intensity reduction targets only when the level of economic development is between about 2673 dollars and about 12677 dollars [3]. GDP and institutional factors have the greatest impact on renewable energy consumption in all countries [4].
On the other hand, countries are faced with environmental content in terms of energy intensity, which encourages optimal institutional involvement, because circular activities are strongly and positively influenced by institutional quality [5].Previous research results found that there is a positive relationship between energy consumption, government effectiveness, regulatory quality, and 1324 (2024) 012098 IOP Publishing doi:10.1088/1755-1315/1324/1/012098 2 environmental degradation [6].The interaction of renewable energy consumption with institutional quality will have an impact on CO2 emissions [7].On the other hand, institutional quality and financial development are driving factors in encouraging environmentally friendly economic growth in the long term [8].Renewable energy consumption, and institutional quality enhance green growth in E-7 countries [9].Governance such as institutional quality has a short-term and long-term influence on energy consumption [10], but other studies find that changes in institutional quality have a limited impact on energy and environmental policy [11] so there is little relationship with energy efficiency.On the other hand, government governance in the form of regulations is expected to encourage energy efficiency for the country, but several findings show contradictory results.The contribution of environmental regulations to energy efficiency has undergone a U-shaped process [12].
Previous research examined the quality of institutions or government governance in relation to environmental issues and energy use from the demand side.This research examines whether government governance is related to energy use from the supply side or energy intensity for crosscountry studies.Studies regarding the use of energy from the supply side during COVID-19 are less studied.This research will also reveal the differences in energy intensity in various income groups.The research results are expected to contribute to recommendations regarding energy efficiency that are linked to improving government governance in line with support for SDGs targets.

Method
This research examines energy intensity in the COVID-19 period and the period before 2019.The estimated number of countries experiencing economic contraction is 182 countries which are divided into three groups, namely 56 high-income countries, 99 middle-income countries, and 27 low-income countries.The middle-income country group is a combination of the upper and lower middle income country group.The variables studied are energy intensity, renewable energy consumption and economic growth and government governance.Energy intensity is the ratio between energy supply and GDP, so the higher the intensity ratio, the more energy is used to produce output or the less efficient it is.Government governance is measured by government effectiveness and regulatory quality.Source of research data from World Bank publications.Data is processed through correlation and comparison analysis.The correlation test is applied to all estimated variables.Meanwhile, the comparison test is applied to assess whether there are differences in energy intensity based on income groups, and differences in efficiency during the economic contraction period and before.Before testing correlation and comparison, a normality test was carried out by the Kolmogorov-Smirnov test.If the data is normally distributed, then correlation and comparison are tested through parametric analysis, but if the data is not normally distributed then nonparametric testing is carried out.The interpretation of the correlation results is 0.9 ≤ rho ≤ 1 is very strong; 0.7≤ rho ≤ 0.89 is strong; 0.4≤ rho ≤0.69 is moderate; 0.1≤ rho ≤0.39 is weak, and rho ≤ 0.09 is very weak.Data is processed by EViews and SPSS.

Results
Table 1 presents descriptive statistics for research variables based on income groups.The high-income country group has a lower primary energy intensity level than the low-and middle-income country group.This implies that the energy efficiency of countries with high income is better than countries with lower income.On the other hand, the convergence of energy utilization is better in the middleincome country group, compared to other groups, which is indicated by a lower standard deviation value.The low-income group of countries appears to have greater differences or disparities in energy intensity than other groups of countries.There are several factors that influence energy convergence.Convergence occurs in the world as a whole, depending on the spatial distribution of countries and several long-term economic characteristics in which, in this case, groups of neighboring countries have higher levels of convergence, in addition, domestic capital accumulation, growth in total factor productivity, and renewable energy consumption significantly determine the characteristics of the convergence group [13].
The renewable energy consumption for the high-income country group is on average lower than for other country groups.The average consumption of renewable energy for the low-income country group is 71.41 percent of the total final energy.Furthermore, the economic growth variable shows that in general all countries experienced economic contraction in 2020 due to the COVID-19 pandemic.The highest economic contraction value was experienced by the high-income group of countries.Furthermore, government governance as measured by government effectiveness and law quality shows better for high-income countries, and very low in low-income countries.The results of the normality test show that for all estimated data, the Kolmogorov-Smirnov probability values for the energy intensity, renewable energy consumption, growth and regulatory quality variables are <0.05 or not normally distributed, while the government effectiveness variables are normally distributed.This is in line with the grouping of countries for high and middle income countries for energy intensity and energy consumption variables.In contrast to the group of countries with low income, have probability >0.05 for all variables, except energy intensity.Thus, further data estimation for correlation tests regarding the relationship between energy intensity and other variables is carried out using nonparametric statistics Spearman's rho for the case of all data, because all energy intensity data shows a probability <0.05, which is reinforced by the histogram graph as in Figures 1 to 4 which indicates that the energy intensity variable is not normally distributed.
Table 2 presents the results of the correlation test of the energy intensity variable with renewable energy consumption, economic growth and government governance.Data estimates for all country groups show a positive and significant correlation between energy intensity and renewable energy consumption and economic growth with weak correlation values of 0.14 and 0.193 respectively.This finding is different from previous ones, where economic growth and modern renewable energy contribute positively to increasing energy efficiency, and modern renewable energy negatively moderates the impact of growth and industrialization on energy intensity [14].On the other hand, there is a negative and significant relationship between energy intensity and government governance with a moderate correlation value of -.41 for government effectiveness, and -.42 for the regulatory quality variable.Institutional quality has a significant negative impact on energy intensity or contributes positively to increasing energy efficiency while industrialization and FDI stock tend to drive higher energy intensity [14].Good governance will encourage a reduction in the intensity of energy use.This means that government governance, which is measured by government effectiveness and the quality of regulations, will encourage more efficient use of energy in the economy.Environmental regulations significantly influence total factor energy efficiency [15].So that efforts to increase government effectiveness, good policies and regulations are needed to achieve the desired level of green economic growth [16].However, based on country groups, it appears that energy intensity in the high-income country group actually has a negative relationship with renewable energy consumption.On the other hand, energy intensity does not correlated with economic growth and government governance.This is not in line with previous findings, where government governance, especially environmental regulations, has a greater driving force in increasing energy efficiency in areas with high levels of regional development [12].There is a negative relationship between economic growth and increasing energy 1324 (2024) 012098 IOP Publishing doi:10.1088/1755-1315/1324/1/0120985 intensity as countries move from low to high income levels [2].On the other hand, the middle-income country group shows a significant correlation between energy efficiency and government governance.The 'rule of law' is important for implementing environmentally friendly technologies and tax reform [17] so as to increase energy efficiency and productivity and reduce energy intensity Testing the residual value of energy intensity between income groups is not normally distributed as the Kolmogorov-Smirnov significance value presented in Table 3 is <0.05, therefore the comparison test between income groups was carried out using the Wilcoxon test.The comparison test between income groups as presented in Table 3 shows that there are significant differences in energy intensity between country groups as indicated by a test significance of <0.05, where the high-income country group has lower energy intensity than others, and the middle-income country group has lower energy intensity than other low-income country group.Thus, the higher a country's income level, the more efficient its use of energy will be in producing economic output.Table 4 shows significant differences in energy intensity before and during the COVID-19 pandemic period which is indicated by a significance value of 0.008 < 0.05.The average energy intensity in 2020 was 4,776, while in 2019 was 4.71 or indicates that energy intensity in 2020 was higher than in 2019.In other words, there was energy inefficiency in 2020 compared to 2019, even though the economy in 2020 experienced contraction..008

Conclusion
Energy intensity during the pandemic was higher than in 2019, even though economic growth experienced a contraction on average.Based on country groups, there are significant differences in energy utilization where high-income country groups are more efficient in energy use than other country groups.In general, energy use is positively correlated with economic growth, and negatively with government governance.The better the governance, the more efficient the use of a country's energy.These findings recommend the importance of governance in encouraging energy efficiency efforts.These results strengthen recommendations oriented towards Sustainable Development Goals (SDGs), namely government institutions (SDG-16) and economic growth (SDG-8).The government needs to take a role in improving the effectiveness and quality of regulations for sustainable development, especially those related to energy efficiency.On the other hand, efficient use of energy is expected to encourage sustainable economic growth, in addition to efforts to use environmentally friendly energy which will encourage the achievement of SDGs-13 targets or actions to combat climate change and its impact on the environment.

Figure 1
Figure 1 Energy Intensity Histogram Graph for AllCountry Groups for the 2020 Period

Table 1
Descriptive statistics of research variables

Table 2
Correlation of research variables

Table 3
Comparison test of energy intensity based on income group

Table 4 Comparison
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