The non-linear relationship between carbon dioxide emissions, financial development and energy consumption in developing European and Central Asian economies.

A sizeable amount of scholarly work has been done on different aspects of financial, economic, and environmental factors. In the present study, the nonlinearity is determined between financial development and carbon dioxide emissions in the long-run and short-run periods. According to the finding, the continued financial development initially increases the carbon dioxide emissions in the short and long run. Simultaneously, the square term of financial development reduces carbon dioxide emissions and proves the inverted U-shaped hypothesis in the short and long periods. The consumption of fossil fuels produces carbon dioxide emissions, leading to environmental pollution. In contrast, renewable energy sources have fostered ecological sustainability by reducing CO2 emissions in the long and short term. At the same time, a positive response from labor productivity to carbon dioxide emissions causes environmental pollution, while capital formation is not acknowledged as a significant contributor to CO2 emissions. The Error Correction term has ascertained the reduction in error and convergence of the model from short to long term with a speed of 8% per annum. The study suggested that renewable energy and financial development should be indorsed for environmental preservation in developing European and Central Asian economies. Financial development in favor of low-cost renewables, advancing cleaner production methods, solar paneling, and electrification are a few possible remedies to achieve environmental sustainability in the short-run as well as long-run time frame.

Introduction

In this modern era, environmental sustainability along with financial development is the demand of both developed and developing economies. Developing economies need respectable economic growth and financial development along with a healthy environment to achieve the economic targets to get the rank of the developed nations. In evidence of APEC countries, financial development reduces carbon dioxide emissions, leads to improvement in environmental quality and economic prosperity (Zaidi et al. 2019). A clean and healthy environment provides a better life for the living. It is expected that when the environment becomes pure, it will give better health to individuals and better health status is the sign of better production in the economy. In other words, when the labor is healthier, vigorous, and skillful, the production activities in the economy flourish, and it will improve financial development and bring economic prosperity (Chaudhry et al. 2012; Hanif and Chaudhry 2015). In these modern times and according to the contemporary concepts of economic well-being, the energy sector also has great importance. Currently, the energy sector is considered the leading sector regarding economic well-being because of its strong linkages with economic prosperity, financial development and the natural environment. The rapid productivity of goods and economic growth relies on the energy sector in developed and developing nations. In this regard, energy is further divided into two segments, which are non-renewable and renewable energy. Non-renewable energy like fossil fuels such as gas, coal, and oil are readily available and less costly. Therefore, mainly developing nations depend on non-renewables to produce goods (Mudakkar et al. 2013; Hanif et al. 2019). Non-renewable energy is frequently used in developing countries because the primary concern is to enhance productivity with low production costs to compete in the national and international markets. The high dependency on non-renewable energy has a formative influence on developing economies, as their economic growth is increasing rapidly (Zhang et al. 2012; Waslekar 2014). At the same time, non-renewables are undoubtedly considered the helping hand to rapid productivity in economic growth, but it is also demoralizing ecological sustainability. The high feasting of non-renewables is causing the emissions of greenhouse gases like carbon dioxide emissions. The developing countries have the limitation of resources to sustain their non-renewable energy resources. That’s why they are using non-renewable energy resources above the limit and causing environmental pollution (Mudakkar et al. 2013; Adams et al. 2018).

Fossil fuel-based energy is used as a frequent intake in developing economies because it is easy to access, less costly in term prices, and contributes to the growth generation process. As a result, this non-renewable energy is increasing health risks and air pollution in the form of carbon emissions (Hanif et al. 2019). Here are the ten-year averages of some developing economies from Europe and Central Asia, highly dependent on fossil fuel energy. Such as Azerbaijan 96.10%, Belarus 91.99%, Bosnia and Herzegovina 86.10%, Moldova 90.01%, Russia 91.11 %, Serbia 85.29%, and Turkey 89.38%. These countries are mainly consuming fossil fuels to generate energy and the largest emitter of carbon dioxide in the air (World Bank   2020). Thus, it is expected that such countries are at high risk of environmental degradation and ecological disorder. To slow down the ecological disruption, there is essential to highlight the dangers of fossil fuel energy consumption. In the present time, under high environmental challenges all over the globe, it is essential to search for environment-friendly energy alternatives to produce goods and to meet energy requirements at the domestic level. As a result, many studies have highlighted the importance of renewable energy to improve economic growth and ensure environmental sustainability. However, renewable energy resources are usually costly than non-renewable energy sources while providing a better growth process and sustainable environment. That’s why renewable energy has significant importance in the growing generation process without destroying sustainable environmental conditions. After the developed economies, the developing economies are also moving to renewable energy resources to improve their financial development without any threat of ecological degradation. For instance, Albania 37.01%, Georgia 35.57, and Montenegro 46.09 are some developing economies from Europe and Central Asia, have highly dependent on renewable energy. At the same time, these values are the 10 years average of renewable energy (World Bank 2020).

This research mainly objects to expose the nonlinearity in the relationship between renewable and nonrenewable energy intakes, financial development, and carbon secretions by adopting the EKC hypothesis in eighteen European and Central Asian developing economies. The present study ' s primary concern is to highlight the nature of the relationship between financial development, environmental, and energy variables because parabolic relationships between variables demand different policy frameworks compared to the linear association between such variables. There is a prerequisite to understanding the linear or nonlinearity in the relationship between energy consumption, financial development, and carbon emissions. For this purpose, the Environmental Kuznets Curve hypothesis might help investigate such types of association and develop a practical policy framework to control or mitigate the carbon dioxide emissions in the selected countries. The EKC hypothesis assumes that in countries with low financial development, initially or in the first phase of EKC, there will be a positive relationship between financial development and carbon emissions. Because under poor economic conditions, the countries usually ignore the environmental issues and try to improve financial development to tackle economic challenges such as poverty, unemployment, and low production of goods and services. However, in the second phase of EKC, it is assumed that the countries treated the environment as a fundamental and other economic challenge after getting respectable financial development. Therefore, there should be a negative relationship between financial development and carbon emissions in the second phase. In short, this study hypothesizes that EKC will show an inverted U-shaped relationship between financial development and carbon emissions. There is similar evidence presented in the past research in which the square term of financial development is introduced, and evident the second phase (inverted U-shaped) of the EKC hypothesis. It was found that there is a negative relationship between financial development and carbon dioxide emissions (Shahbaz et al. 2013). The study objective is to investigate the U-shaped, and inverted U shaped EKC for financial development and environmental pollution. Further, the study objective is to examine environmental sustainability by examining the influence of renewable energy consumption, which is the clean form of energy, on carbon dioxide emissions. Therefore, it is expected that the findings of this study will be helpful to and depict a different angle of association between financial development, energy variables, and environmental quality. The above discussion has raised some questions to be answered. First, whether the non-linear relationship between carbon dioxide emissions, energy consumption and financial development exists?. Second, whether the EKC U or inverted U-shaped relationship exists in the dependent and independent variables? In the end, the research demands some beneficial policies to maintain environmental sustainability by mitigating environmental pollution.

This research is constructed into 5 sections to explore the non-linear relationship between carbon dioxide emissions, energy consumption and financial development. Section 1 of the introduction introduces these indicators, research questions, importance, contribution, and study objectives. The following “Review of literature” section has reviewed the previous research regarding the relationship between carbon dioxide emissions, energy consumption, economic growth and financial development and ends up with a research gap. “Data, methodology, and specification of model” section discusses the description of variables, data, specification of the theoretical and econometric model and methodology. However, “Results and discussions” section interprets the results and discuss with economic reasoning and evidence of past studies. In the end, “Conclusion” section concludes the research by conclusion, implications, limitation and future direction of the research.

Review of literature

In this modern times, the energy sector is considered one of the leading sectors in developed and developing countries. The developed nations have adopted sustainable energy resources and gaining the benefit in the form of economic growth. Simultaneously, the developing countries have a deficiency of planning and resources to adopt these sustainable energy resources for economic development. Most developing countries have adopted fossil fuels and paid the cost in the shape of ecological threats. The environment is significantly tainted in emerging nations because of much enslavement of the energy resources that cause greenhouse gas emanations. These greenhouse gases like carbon dioxide releases have spoiled the environment and reduce the environment ' s sustainability, cause them to get far away from developed nations ' status. While most emerging countries are seen to have substantial renewable energy intake, their dependence on nonrenewable energies has not enabled them to rehabilitate environmental sustainability. However, this literature review section has reviewed the past studies to achieve the following hypothesis: EKC U-shaped hypothesis and EKC inverted U-shaped hypothesis.

Country level studies of carbon emissions and economic growth nexus

Energy consumption has a positive association with economic growth, as the high energy intake has enhanced the economic growth of developing economies. This positive association has also been enhanced the carbon secretions and degraded the environmental quality. This ecological deprivation in developing countries has lessened the environment ' s sustainability or purity (Alam et al. 2007; Qi et al. 2011; Bo 2011; Ahmed and Long 2012). However, transitory to the early stages of growth generation, the later stage of stable economic growth helps to mitigate the carbon dioxide emissions, proved the inverted U-shaped EKC hypothesis (Qi et al. 2011; Bo 2011). Shahbaz et al. (2012a, 2012b) stated that environmental cleanliness is reduced by more energy intake, as economic growth in Pakistan is improved. In another piece of evidence of Zhang et al. (2012), the high feasting of energy has promoted China’s economic growth but failed to sustain the environmental purity. Renewable energy and non-renewable energy are the two types of energy used by developing economies. Simultaneously, non-renewable energy resources are not environmentally friendly, frequent in developing countries. Non-renewable energy is frequent to enhance economic growth, while this prolific enhancement has increased the carbon dioxide emissions that caused environmental pollution in China (Zhang et al. 2012). Mudakkar et al. (2013) evidenced that the large abundance of energy sources has degraded Pakistan ' s environment. The consumption of fossil fuels as nonrenewable energy resources caused CO2 discharges and threatened ecological contamination in Pakistan. The study of the Malaysian economy evident the positive reliance of carbon dioxide secretions on all energy forms. However, the plentiful fossil fuel energy consumption has mitigated environmental sustainability (Saboori and Sulaiman 2013a). Shahbaz et al. (2014) in Pakistan, Hu et al. (2014), and Wang et al. (2015) in China have ascertained that the high consumption of energy for better economic conditions undoubtedly enhanced the economic growth but enforced environmental pollution. However, Shahbaz et al. (2014) proved that carbon dioxide emission is reduced in Pakistan after achieving the desired level of economic growth. In UAE, the consumption of energy to promote the economy of UAE, the greenhouse gases like carbon dioxide gases are released and caused the environmental hazard (Jayaraman et al. 2015). However, due to high energy consumption the environmental hazard is evident in Pakistan in the short and long run (Javid and Sharif 2015). The environment becomes polluted by the extensive use of energy in Tunisia, in Eastern, Western, and Central China (Sghari and Hammami 2016; Zhang and Gao 2016a, 2016b). In South Africa, energy consumption and carbon dioxide emissions intensity both are negatively impacting environmental sustainability. There is unidirectional causality between economic growth and carbon dioxide emissions. The study also evident the Inverted U-shaped EKC between economic growth and carbon dioxide emissions (Bekun et al. 2019). Raza et al. (2019) studied the positive effect of energy consumption on carbon dioxide emissions in the short, medium, and long run. However, Granger causality passed through the one-way causation from energy consumption to carbon dioxide emissions in the USA. In evidence of China’s western, intermediate, and eastern zone, gross regional products negatively influenced the carbon dioxide emissions, leading to environmental protection (Ahmad et al. 2019). In another evidence of China, the effective contribution of economic growth and energy has mitigated carbon dioxide emissions (Zhang et al. 2019). In the discussion of renewable energy consumption, it is evident that German, as the leading European economy, is the largest renewable energy consumer. The effective contribution of renewable energy helped boost economic growth and environmental purity (Rafindadi and Ozturk 2017). However, financial development is an important indicator of economic growth and perform as the function of economic growth to influence carbon dioxide emissions. Jalil and Feridun (2011) examined the long-run relationship between financial development and carbon dioxide emissions. In China, financial development negatively influences carbon dioxide emissions, reduced environmental degradation and their exists an inverted U-shaped EKC. In the case of Turkey, financial development does not affect carbon dioxide emissions (Ozturk and Acaravci 2013). Shahbaz et al. (2013) illustrated that financial development has reduced carbon dioxide emissions in Indonesia. However, the inverted U-shaped EKC among financial development and carbon dioxide emissions has been observed. At the same time, the positive and negative influence of financial development on carbon dioxide emissions leads to linear and non-linear impacts. Charfeddine and Khediri (2016) investigated that financial development negatively influenced carbon dioxide emissions and also proved inverted U-shaped EKC in UAE. Nevertheless, financial development negatively affects carbon dioxide emissions, promoting Turkey ' s financial sector and environmental protection (Katircioğlu and Taşpinar 2017). In another evidence of Turkey, financial development has increased carbon dioxide emissions and deprived environmental quality (Pata 2018).

Panel studies of carbon emissions and economic growth nexus

The literature above has reviewed the relationship between carbon dioxide emissions, economic growth, and energy consumption at country level. The study has reviewed the past studies of these relationships in more than one country or panel countries. In the case of ASEAN, the consumption of energy to improve economic productivity has degraded the environment by emitting carbon dioxide gas. While later, the emissions of carbon dioxide have been reduced by achieving desirable productivity and growth in ASEAN ' s economies, proven the Inverted U-shaped EKC hypothesis. In contrast, Singapore and Thailand are failed to control the environmental hazard and found the most degraded countries from ASEAN (Saboori and Sulaiman 2013a). In evidence of low-high income economies, the constructive participation of energy caused the high carbon discharges in emerging economies or those economies in which the per capita income is meager. At the same time, the high-income countries are evidenced the environmental sustainability. However, the inverted U-shaped EKC manifested in those economies that have achieved the desired economic growth and environmental sustainability (Waslekar 2014). Zeb et al. (2014) have studied that the SAARC economies are indulged in high energy consumption, which has risen the CO2 emission and environmental pollution. In six oil-exporting countries, the total energy consumption and high dependency on oil consumption has worsen the environmental quality in all six oil-exporting countries. The reduction in the environment’s sustainability is caused by CO2 emissions, resulting from high reliance on oil consumption. However, the countries who have corresed the turning point of EKC, the improvement in their economic growth is reducing the carbon dioxide emissions. There are shreds of positive influences of energy intakes and economic growth on carbon dioxide emissions in different economies. Al-mulali et al. (2015) in low-lower middle-income nations, Saidi and Hammami (2015) in fifty-eight countries, and Salahuddin et al. (2015) in GULF countries have proved the positive relationship between energy and environmental pollution. The long-term evidence of ecological degradation in GULF economies is verified by Salahuddin et al. (2015). In a provincial level study, Zheng et al. (2015) evidenced the positive relationship of energy with economic growth and air contamination in China. However, some provinces have evident the negative influence of economic growth and energy consumption on carbon dioxide emissions in China. In evidence of a large panel of fifty-eight countries, energy consumption has positively contributed to economic growth and CO2 emissions in six regions. Economic growth’s positive influence on carbon dioxide emissions led to global warming and other environmental threats. However, economic growth and carbon dioxide emissions have shown inverted U-shaped EKC (Kais and Sami 2016). Following nonrenewables, fossil fuel energy was found substantial to enhance alarmed economic growth, while air pollution is verified through the high consumption of non-renewables (Adams et al. 2018). Non-renewable fossil fuel energy is the most important tool to enhance the economic growth of fifteen developing economies but failed to rehabilitate environmental sustainability. At the same time, inverted U-shaped EKC hypothesis is also verified for a panel of fifteen developing Asian countries (Hanif et al. 2019). In the study of MENA economies, the sustainable consumption of energy and economic growth has lessened the carbon dioxide secretions, reduced the environmental pollution hazard (Gorus and Aydin 2019). However, in SAARC countries, urbanization and GDP per capita have exaggerated carbon dioxide emissions, led to the U-shaped EKC hypothesis (Anser et al. 2020a).

After equating the effects of total energy and non-renewable energy ingesting on ecological conditions, the renewable energy resources are found most productive to enhance environmental sustainability. Renewable energy consumption has an affirmative influence on economic growth assisted environmental protection in G7 countries (Tugcu and Topcu 2018). Following some panel studies, renewable energy resources enhanced the growth of developing economies and sustainability in the environment by reducing CO2 emissions (Ito 2017; Carfora et al. 2019). Renewable energy is a vibrant indicator to enhance economic growth and mitigate carbon dioxide emissions, leading to economic progression in OECD countries (Inglesi-Lotz 2016; Gozgor et al. 2018). In the evidence of panel study, renewable energy is the foremost indicator to promote economic performance level in Poland compared to sixteen emerging economies. However, renewable energy assisted in reducing Poland’s environmental hazard following energy conservation policies (Ozcan and Ozturk 2019). In the case of MENA economies, renewable energy consumption slightly influenced the mitigation of carbon dioxide emissions. However, renewable energy is considered a weak indicator concerning contribution to environmental protection (Charfeddine and Kahia 2019). In addition, the high renewable energy consumption has executed economic prosperity, and reduced carbon dioxide emissions endorsed environmental protection in the short and long run. Fossil fuel energy consumption has badly affected the environmental conditions of SREB emerging economies. However, the economic growth and carbon dioxide emissions have developed the EKC inverted U-shaped hypothesis in SREB economies in the long run (Yang et al. 2021). Anser et al. (2020a) in developing Latin America and the Caribbean countries and Alharthi et al. (2021) in MENA countries evident the EKC inverted U-shaped hypothesis between economic growth and carbon dioxide emissions. Renewable energy consumption negatively influenced CO2 emissions, while fossil fuel energy consumption contributed to environmental pollution in concerned economies (Anser et al. 2020a; Alharthi et al. 2021). In the case of ASEAN countries, non-renewable energy exaggerates carbon dioxide emissions, while renewable energy consumption has reduced environmental pollution. Further, the EKC inverted U-Shaped hypothesis is verified by the negative influence of squared economic growth on carbon dioxide emissions (Anwar et al. 2021). Based on the above previous studies literature, the study can investigate the influences of financial development, renewable and non-renewable energy consumption on carbon dioxide emissions following these hypotheses mentioned below:

H1: There is a positive relationship between financial development and CO2 emissions to validate U-Shaped EKC hypothesis in developing European and Central Asian economies.

H2: There is a negative relationship between renewable energy consumption and CO2 emissions in developing European and Central Asian economies.

Research gap

The above-mentioned studies have provided a very straightforward relationship between energy consumption, economic growth, and carbon dioxide emissions. Therefore, the first research gap addressed in the present study based on the investigation of nonlinearity in the association between energy consumption, financial development, and carbon emissions. Meanwhile, most researchers focus on developing and developed economies from Asian, African, American, MENA, and GULF nations. Therefore, the present research focuses on important cross-sections of developing European and Central Asian economies, which have been seldom inspected in the past studies to spotlight the relationship between renewables and non-renewables, economic growth, and carbon dioxide secretions. However, financial development is an important indicator of economic prosperity, which is rarely reviewed in the literature and requires panel investigation of the relationship between energy consumption, financial development, and carbon dioxide secretions. Further, the EKC hypothesis needs exploration in study areas of developing European and Central Asian economies, which have been unsatisfactorily inspected in the past studies. Therefore, it is essential to inspect the validity of inverted U-shaped EKC hypothesis for environmental sustainability in developing European and Central Asian economies.

Data, methodology, and specification of model

Data

The study explores environmental sustainability and investigates EKC hypothesis in European and Central Asian economies. To confirm the existence of inverted U-Shaped EKC, the selection of variables is based on carbon dioxide emissions as a dependent variable. The independent variables are energy taken in both forms, the non-renewable and renewable forms. However, financial development, the square of financial development, capital formation, and productivity in labor are other concerning factors collected from 2010 to 2019.

The data of these variables is collected through “World Development Indicators.” There are 18 countries from the Europe and Central Asia region (World bank list of economies 2020) considered to measure environmental sustainability. Countries’ selection is based on their income level, reliance on nonrenewables, renewables, and carbon dioxide emissions. All the selected countries have developing status, and their income level is lower and upper middle income. Table 1 and Fig. 1 illustrate the high indulgence of developing economies in energy consumption. However, this generates carbon dioxide emissions, which is a threat to environmental sustainability. Therefore, this research has selected developing countries that are consuming renewable and non-renewable energy sources and facing environmental issues. The detail of countries is given below in Table 1 and Fig. 1:

Table 1

Table of selected European and Central Asian developing countries

Countries	CO2 emissions(metric ton per capita)	GDP(per capita growth)	Fossil fuel consumption(% of total energy)	Renewable energy consumption(% of total energy)
Albania	1.753	2.87	60.15	38.871
Armenia	1.836	4.221	72.588	12.747
Azerbaijan	3.77	0.444	96.642	3.362
Belarus	6.521	1.86	99.602	0.307
Bosnia and Herzegovina	6.327	3.303	82.256	33.108
Bulgaria	6.108	3.026	72.419	26.954
Georgia	2.35	5.136	76.324	27.725
Kazakhstan	15.423	3.016	96.847	3.149
Kyrgyz Republic	1.611	2.275	74.75	23.89
Moldova	1.646	5.084	87.091	13.142
Montenegro	3.571	2.813	64.459	45.035
Romania	3.82	3.629	76.862	22.493
Russian Federation	11.906	1.65	88.427	11.573
Serbia	5.98	2.477	83.569	21.564
Tajikistan	0.569	4.54	43.733	47.021
Turkey	4.594	4.214	87.095	12.814
Ukraine	5.458	1.351	78.409	21.558
Uzbekistan	3.469	4.644	96.716	3.284

Source: World Development Indicators (2010–2019), World Bank List of Economies (2020)

Fig. 1

Renewable energy and non-renewable energy 10 years average values

Source: Based on WDI data (2010–2019)

Explanation of variables

Carbon dioxide emissions (EVD_CO2)

Carbon dioxide is a greenhouse gas emitted by energy consumption in the growth-generation process. Carbon dioxide emissions’ measuring unit is as a metric ton per capita. CO2 has a positive association with energy intake and economic growth (Kais and Sami 2016; Bekun et al. 2019). Therefore, it should be negative to verify the hypothesis of EKC inverted U-shaped (Hanif et al. 2019; Anser et al. 2020a; Alharthi et al. 2021; Anwar et al. 2021; Yang et al. 2021).

Non-renewable energy consumption as fossil fuels (FFEC)

Fossil fuels are produced by ancient plants, buried or dead organisms. This frequent energy type is consists of carbon, coal, oil, gas, and petroleum. Fossil fuel energy ingesting is measured as the total percentage of energy. In addition, fossil fuels emit greenhouse gas such as carbon dioxide. Therefore, the expected relation of fossil fuel consumption with CO2 is positive (Mudakkar et al. 2013; Hanif et al. 2019; Anser et al. 2020b; Alharthi et al. 2021; Anwar et al. 2021; Yang et al. 2021).

Renewable energy consumption (REEC)

Renewable energy consumption is easily replaceable in natural processes and an essential energy type. Renewable energy intake is measured as the total % of final energy consumption. Renewable energy is an environmental and growth-friendly source and does not hurt environmental sustainability. The expected relation of renewable energy with CO2 emissions is negative (Carfora et al. 2019; Ozcan and Ozturk 2019; Anser et al. 2020b; Alharthi et al. 2021; Anwar et al. 2021; Yang et al. 2021).

Financial development (FN_DEV)

Financial development ties into the private sector’s economic growth and poverty reduction plan. The financial sector comprises a series of institutions, tools and markets, and also a legal and regulatory framework that allows for credit risks transactions. Financial development is measured as the domestic credit to private sector through % of GDP. Financial development has a positive expected relationship with CO2 emissions, examined in previous research (Charfeddine and Khediri 2016; Pata 2018).

Financial development squared (FN_DEV2)

Financial development squared is the double effect of financial development and is used to proxy double domestic credit to private sector. There is a need for doubled financial development to prove the EKC inverted U shaped hypothesis. The expected effect of squared financial development on CO2 emissions is negative, proved by past studies (Shahbaz et al. 2013; Charfeddine and Khediri 2016).

Gross fixed capital formation (KFOR)

KFOR is defined as the fixed amount of increase in capital stock, which is considered the future investment to promote production and growth. The fixed amount is generated through the annual growth percentage. It is expected that capital formation would positively relate to CO2 emissions (Saidi and Hammami 2015). However, it can be negative only if the resources will be used efficiently and in a sustainable manner (Hanif 2018a, b; Hanif and   Gago-de-Santos 2017; Yang et al. 2021).

Labor productivity (PRO_LB)

Labor productivity is the increase in output through labor and can be measured in any economy by its adult population. Labor productivity is used as a total labor force and aims to enhance the growth level of the economy. The expected sign of labor productivity with CO2 emissions is positive, evidenced in previous researches (Saidi and Hammami 2015).

Specification of model and methodology

In this study, financial development, renewable and non-renewable energy consumption, and carbon dioxide emissions are measured theoretically and in an econometrical way for the evidence of the inverted U-shaped EKC hypothesis (Kuznets 1955). The theoretical point of view is that economic growth and energy intakes positively relate to carbon dioxide emissions, which is the leading cause of environmental pollution, leads to the early stage of the EKC hypothesis. However, the desired level of economic growth helps to reduce environmental pollution and develop ecological sustainability. Thus, according to the theory, the squared economic development has reduced environmental degradation, validate the EKC inverted U-shaped hypothesis. Thus, we need to establish the econometric model of financial development and carbon dioxide emissions to verify the EKC inverted U-shaped hypothesis in European and Central Asian developing economies based on the studies of Shahbaz et al. (2013) and Charfeddine and Khediri (2016).

The study examines the non-linear relationship between financial development, renewable and non-renewable energy consumption, and carbon dioxide emissions. First, we have to develop the nonlinear functional form among variables which is given below:

The above equation is a non-linear functional form of environmental degradation (EVDCO2). In the above functional form, carbon dioxide emissions (EVD_CO2) depend on fossil fuel energy consumption (FFEC), renewable energy consumption (REEC), financial development (FN_DEV), financial development square (FN_DEV2), capital formation (KFOR), and labor productivity (PRO_LB).

Econometric description of model

The above equation is for the statistical description of the model to measure the empirical model ' s worth in terms of statistics. The above equation is passing through different statistical techniques to prove the statistical fitness of the model. Here in this step, the empirical model observes statistical terms to elaborate its statistical worth. In the second step of descriptive statistics, the strength of the relationship among variables is an important step. The correlation matrix tells us about the relationship among variables and multicollinearity. After this statistical summary, this model passes through the unit root test in terms of Levin, Lin and Chu, and Im, Pesaran, and Shin, to measure stationary level among variables. The mixed level of integration among variables leads to apply the ARDL technique on the model based on EKC inverted U-shaped hypothesis in European and Central Asian developing economies.

The above Eq. (2) is for the long run ARDL to prove or disprove the EKC inverted U-shaped hypothesis among financial development, renewable, fossil fuel, and carbon dioxide emissions in a long period in Europe and Central Asia developing countries.

Bound test of cointegration

Before applying the long run ARDL on the empirical model, there is one initial step before this, the bound test for cointegration. This initial step is based on the cointegration equations to exist the cointegration among variable’s equations. The bound test cointegration is based on null and alternative hypothesis, which are written down, respectively.

Null Hypothesis: H0: ά1 = 0; α2 = 0; α = 0; β = 0; β = 0; γ6 = 0; γ7 = 0 (No Cointegration exists)

Alternative Hypothesis: H1: ά1 ≠ 0; α2 ≠ 0; α ≠ 0; β ≠ 0; β ≠ 0; γ6 ≠ 0; γ7 ≠ 0 (Cointegration exists)

The equation of bound test for cointegration is written as:

The above Eq. (3) shows the bound testing cointegration equation to prove the existence of long run relationship among variables. The alternative hypothesis will verify the cointegration equations among variables.

Pesaran, Cross-sectional Dependency (CD) test

Before measuring the inverted U-shaped EKC premise in the long and short run by applying ARDL, the one-step before ARDL and after bound testing for cointegration is the Pesaran CD test to approve the cross-sectional dependency among variables. There are also null and alternative hypotheses. The null hypothesis tells us that there are no cross-sections among variables, while the alternative hypothesis is the opposite of the null hypothesis. The acceptance of the null hypothesis will prove the no-cross sectional dependency and lead to apply the ARDL on the long and short term models. The values of both the bound test and Pesaran cross-sectional dependence are sanctioned by Pesaran et al. (2001).

Short, long run ARDL, and ECM

After the bound testing for cointegration equation to prove long-run existence and Pesaran cross-sectional dependency, an essential step is required to measure the inverted U-shaped EKC hypothesis in the long and short term. The next step will be the error correction model ECM to stabilize the long-run effect.

Short and long-term ECM equation is written below:

The above Eq. (4) shows the short and long term dynamics with ECM to prove or disprove the inverted U-shaped EKC premise in eighteen European and Central Asian countries. The dynamics starting from ∑ and Δ are short-term dynamics and showing their equation. The rest of equation shows the long-run model. ECM shows the speed of the adjustment tool to stabilize the long period. Moreover, εi is an error term that helps to ascertain the error.

Diagnostic tests

In the end, the EKC model is passing through some diagnostic tests of normality and serial correlation. However, functional form and heteroscedasticity need to check to prove the error-free empirical model of eighteen countries of Europe and Central Asia.

Results and discussions

After designing the empirical model of EKC in the third section, this section has proved that model through empirical results in an econometric and statistical way. The detail of tables of results and their detailed explanation is given below:

The empirical findings are starting from the summary of the descriptive statistics. First, there is a need to measure the credibility of the model in the statistical term. The descriptive statistics results are given in Table 2 and show that the empirical model ' s concerned variables have statistical worth. The variables have distance from their mean values, which is elaborated by standard deviation, while the skewness shows that each variable has a positive direction except fossil fuel energy consumption. At the same time, kurtosis indicates that each variable is considered leptokurtic and has a thin tail and high peakedness from their mean point. Moreover, the Jarque-Bera probability value shows the significance of variables in terms of statistical worth and suggests that the empirical model is appropriate for further justifications.

Table 2

Summary statistics

	EVD_CO2	FFEC	REEC	FN_DEV	FN_DEV2	KFOR	PRO_LB
Mean	4.410	79.958	16.891	4.876	85.546	18.428	10336474
Median	4.124	84.810	14.261	4.933	30.837	8.917	3294861.
Std. Dev.	2.685	14.500	14.286	7.872	500.530	163.808	18645996
Skewness	0.843	-1.206	0.996	4.705	15.919	16.764	2.723
Kurtosis	3.733	4.191	3.011	53.229	266.492	287.256	9.563
Jarque-Bera	42.329	90.486	49.633	32644.35	880524.9	1024071.	909.296
Probability	0.000	0.000	0.000	0.000	0.000	0.000	0.000

In Table 3 of the correlation matrix, the strength of association among variables is measured. Fossil fuel energy consumption (FFEC) and renewable energy consumption (REEC) have a moderate relationship with carbon dioxide emissions (EVD_CO2). However, renewable energy negatively correlates with carbon dioxide emissions. Besides, financial development (FN_DEV) and squared financial development (FN_DEV2) have a weak and negative relationship with carbon dioxide emissions. The critical value less than 0.30 indicates the weak relationship among variables. In this regard, capital formation (KFOR) have a weak but positive correlation with carbon dioxide emissions. Further, labor productivity (PRO_LB) has a positive and strong relationship with carbon dioxide emissions. However, there is no issue of multicollinearity as the variables have less than the critical value of 0.80. After the statistical description of the empirical model, the next step is the unit root test discussed in Table 4 to measure the order of integration among variables.

Table 3

Correlation matrix

	EVD_CO2	FFEC	REEC	FN_DEV	FN_DEV2	KFOR	PRO_LB
EVD_CO2	1.000
FFEC	0.447	1.000
REEC	−0.483	−0.720	1.000
FN_DEV	−0.179	−0.034	0.078	1.000
FN_DEV2	−0.098	−0.019	0.059	0.735	1.000
KFOR	0.027	−0.027	−0.041	−0.002	−0.012	1.000
PRO_LB	0.731	0.289	−0.351	−0.090	−0.041	−0.032	1.000

Source: Authors’ own calculation based on Eviews 10

Table 4

Unit root testing

		Level		First difference
Variables		Intercept	Intercept and trend	Intercept	Intercept and trend	Concluded order
EVD_CO2	L.L. and C	−4.68 (0.00)	−7.11 (0.00)	-	-	I (0)
	I.P.S	−2.06 (0.01)	−3.43 (0.00)	-	-	I (0)
FFEC	L.L. and C	-	-	−5.75 (0.00)	−5.14 (0.00)	I (1)
	I.P.S	-	-	−8.03 (0.00)	−6.75 (0.00)	I (1)
REEC	L.L. and C	-	-	−8.51 (0.00)	−9.10 (0.00)	I (1)
	I.P.S	-	-	−7.63 (0.00)	−7.00 (0.00)	I (1)
FN_DEV	L.L. and C	−21.97 (0.00)	−15.45 (0.00)	-	-	I (0)
	I.P.S	−9.33 (0.00)	−5.71 (0.00)	-	-	I (0)
FN_DEV2	L.L. and C	−307.79 (0.00)	−263.53 (0.00)	-	-	I (0)
	I.P.S	−74.80 (0.00)	−67.09 (0.00)	-	-	I (0)
KFOR	L.L. and C	−7.22 (0.00)	−6.51 (0.00)	-	-	I (0)
	I.P.S	−6.48 (0.00)	−4.65 (0.00)	-	-	I (0)
PRO_LB	L.L. and C	-	-	−2.85 (0.00)	−3.60 (0.00)	I (1)
	I.P.S	-	-	−4.31 (0.01)	−2.71 (0.00)	I (1)

Source: Authors’ own calculation based on Eviews 10

Table 4 illustrates the unit root test result to confirm the order of integration among variables. The study examines the L.L & C and I.P.S unit root tests to measure the stationarity among variables. According to the findings, carbon dioxide emissions (EVD_CO2) have the order of integration at level I(0). However, financial development (FN_DEV), squared financial development (FN_DEV2), and capital formation (KFOR) are also integrated at level I(0). At the same time, fossil fuel energy consumption (FFEC), renewable energy consumption (REEC) and labor productivity (PRO_LB) are integrated at the first difference I(1). The mixed level of stationarity referred to Panel-ARDL to apply to the empirical model of financial development, energy consumption and carbon dioxide emissions.

The unit root test has referred to the Panel-ARDL to apply to a short and long-term model. Before this, the initial step is the bound testing, which is given in Table 5. The bound test is to verify the long term existence among variables. The bound test is based on two bound values, the upper and lower bound values generated from Pesaran et al. (2001). The F-statistic value is 6.06, larger than the upper and lower bounds values, and rejected the null hypothesis by accepting the alternative hypothesis. The greater the F-statistic value than lower and upper bound values showed the cointegration equations among variables and verified the model’s long-run existence (Hanif et al. 2019). After this, to examine the cross-sectional dependency.

Table 5

Bounds test

EVD_CO2/FFEC; REEC; FN_DEV; FN_DEV2; KFOR; PRO_LB
F-stat	Lower Bound at 95%	Upper Bound at 95%
6.066	2.486	3.702
W-stat	Lower Bound at 95%	Upper Bound at 95%
35.374	17.403	25.913

Source: Authors’ own calculation based on Eviews 10

Table 6 illustrates the findings of Pesaran cross-sectional dependence proposed by Pesaran et al. (2001). The statistic value 0.347 of the Pesaran CD test is insignificant at 0.310, accepting the null hypothesis (no cross-sectional dependence among variables) and rejecting the alternative hypothesis (cross-sectional dependence among variables). Thus, the findings reveal no cross-sectional dependence in the panel model, which leads to short-run and long-run Panel-ARDL analysis.

Table 6

Pesaran Cross-sectional Dependence (CD) test

Test name	Test statistics	P-value
Pesaran’s CD	= 0.347	Prob value = 0.310
Off-diagonal elements’ average absolute value	= 0.827	--

Source: Authors’ own calculation based on Eviews 10

Note: Null hypothesis: no cross-sectional dependence

Table 7 of short-run analysis using Panel-ARDL shows that carbon dioxide emissions significantly and positively influenced by the previous year effect. Fossil fuel energy consumption’s current and previous year effects have significantly enhanced the carbon dioxide secretions. However, fossil fuel energy consumption has exaggerated environmental pollution in the short run, also examined by the previous study of SREB emerging economies (Yang et al. 2021). Further, its non-linear effect has also shown an increase in carbon dioxide emissions in the short run. On the other hand, renewable energy consumption has no considerable influence on carbon emissions in the short run. At the same time, its non-linear effect has reduced carbon dioxide emissions in the short run. Financial development has a positive relationship with carbon dioxide emissions in the short run, causing environmental pollution. However, financial development negatively influences carbon dioxide emissions and considers a significant source of mitigation in environmental pollution. The decline in carbon dioxide emissions by squared financial development has confirmed the EKC inverted U-shaped relationship in the short run. Further, the positive and negative influences of financial development on carbon dioxide emissions indicate the linear and non-linear effects on carbon dioxide emissions in the short run, evidenced by previous research (Charfeddine and Khediri 2016). On the other hand, capital formation does not affect carbon dioxide secretions in the short run. At the same time, labor productivity has a significant role in enhancing environmental pollution in developing European and Central Asian economies.

Table 7

Short-run ARDL approach

Dep Var = EVD_CO2
Regressor	Coeff	Std Error	t-stats
C	−0.094	0.217	−0.432
EVD_CO2(−1)	0.984***	0.334	2.939
FFEC	0.040***	0.008	4.853
FFEC(−1)	0.039**	0.017	2.241
FFEC2	0.084***	0.034	2.471
FFEC2(−1)	0.0321**	0.017	1.888
REEC	−0.002	0.008	−0.284
REEC(−1)	0.004	0.007	0.564
REEC2	−0.069**	0.036	−1.917
REEC2(−1)	−0.046**	0.021	−2.190
FN_DEV	0.024**	0.011	2.025
FN_DEV(−1)	0.003	0.004	0.744
FN_DEV2	−0.026**	0.013	−1.920
FN_DEV2(−1)	0.031	0.066	0.482
KFOR	−0.011	0.014	−0.838
KFOR(−1)	−0.039	0.032	−1.227
PRO_LB	0.574***	0.229	2.506
PRO_LB(−1)	−0.555	0.633	−0.876

Note: ***, **, indicate 1%, and 5% significance levels

In the long-run analysis of Table 8, the fossil fuel energy consumption value is 0.12, which is significant at 1%, indicates its positive effect on carbon dioxide emissions in the long run. This positive carbon dioxide emissions reliance on fossil fuel energy consumption has exaggerated environmental pollution. Some past studies of Zhang et al. (2012) in China, Saboori and Sulaiman (2013b) in Malaysia and Hanif et al. (2019) in fifteen developing countries have examined the positive influence of fossil fuel energy consumption on carbon dioxide emissions. However, Anser et al. (2020b) in developing Latin America and the Caribbean countries, Alharthi et al. (2021) in MENA countries and Yang et al. 2021 in SREB emerging economies proved that fossil fuel energy consumption has increased the carbon dioxide emissions. The results also show that the non-linear square term of fossil fuels has a positive relationship with carbon dioxide emissions in the long run. According to the results, one unit increase in fossil fuels consumption has further increased the environmental pollution by about 0.33 units by increasing carbon emissions in the atmosphere. Thus the results indicate the positive linear and non-linear association between fossil fuels consumption and carbon emissions in the European and Central Asian region.

Table 8

Long-run ARDL approach

Dep Var = EVD_CO2
Regr	Coeff	Std Error	t-stats
FFEC	0.121***	0.048	2.512
FFEC2	0.332***	0.119	2.789
REEC	−0.442***	0.150	−2.934
REEC2	−0.623***	0.238	−2.617
FN_DEV	0.987**	0.513	1.925
FN_DEV2	−0.012*	0.007	−1.675
KFOR	0.845	0.698	1.211
PRO_LB	0.876***	0.279	3.138
INPT	3.637***	1.543	2.357

Note: ***, **, indicate 1%, and 5% percent significance levels

The renewable energy consumption value is −0.44, which is significant at 1%, indicates that renewable energy intake negatively influenced the carbon dioxide secretions and reduced the carbon dioxide emissions by about 0.44 units, almost half of renewable energy consumption. In this modern time of industrialization, developing countries turn towards renewables, beware them from environmental hazards, protecting their ecological sustainability and economic prosperity. Therefore, renewable energy is considered as the vibrant indicator help mitigate the carbon dioxide emissions evidenced by some past studies of Inglesi-Lotz (2016) and Gozgor et al. (2018) in OECD, Carfora et al. (2019) in developing economies, and Ozcan and Ozturk (2019) in Poland. However, in developing Latin America and the Caribbean countries, MENA countries and SREB emerging economies, renewable energy consumption has significantly mitigated carbon dioxide emissions (Anser et al. 2020b; Alharthi et al. 2021; Yang et al. 2021). According to the results of the non-linear square term of renewable energy, one unit increase in renewables consumption has further decreased the environmental pollution by about 0.62 units. Thus, the results showed a negative linear and non-linear association between renewable energy consumption and carbon dioxide emissions in the developing European and Central Asian countries.

Financial development (FN_DEV) value is 0.98, significant at 5%, illustrated that the increased financial development has enhanced carbon dioxide emissions in the long run, evidenced by a previous study (Pata 2018). Thus, the developing countries are just focusing on their financial and economic prosperity while ignoring environmental conditions, causing environmental pollution. The positive association between financial development and carbon dioxide emissions have proved the early stages of the EKC U-Shaped hypothesis in European and Central Asian countries. However, the positive linear dependency of carbon dioxide emissions on financial development and the EKC U-Shaped hypothesis is proved by Shahbaz et al. (2013) in Indonesia and Charfeddine and Khediri (2016) in UAE.

The value of squared financial development (FN_DEV2) is −0.01, which is significant at 10 percent. The squared financial development negatively affects carbon dioxide emissions, promoting environmental sustainability in the long run. This negative association among squared financial development and carbon dioxide emissions has fulfilled the hypothesis of the EKC inverted U-shaped in eighteen developing countries of Europe and Central Asia. It is manifest that the developing economies have concentrated on sustainable energy sources such as renewable energy that enables to achieve desired financial development, helped mitigate carbon dioxide emissions. However, the non-linear negative influence of squared financial development on carbon dioxide emissions and the existence of the EKC inverted U-shaped hypothesis is proven by Jalil and Feridun (2011) in China, Shahbaz et al. (2013) in Indonesia, and Charfeddine and Khediri (2016) in UAE.

In the context of capital formation, it has no significant impact on carbon dioxide discharges. At the same time, labor productivity’s positive influence on carbon emissions has promoted environmental degradation in Europe and Central Asian developing countries, which is evident by Saidi and Hammami (2015). The overall findings of long-run Panel ARDL examined that the EKC U-shaped and inverted U-shaped hypothesis are proven in Europe and Central Asian developing economies. However, renewable energy alleviates carbon dioxide emissions, while fossil fuel energy consumption promotes environmental pollution.

According to the error correction model results in Table 9, the value of ECM is −0.08, which is significant at 1%. This negative sign has shown the presence of speed of adjustment term of ECM to reduce the error in the model. The negative sign illustrates that the speed of the adjustment tool has reduced the error by about 8% from the short run to the long run each year. This means that ecological sustainability is increased each year by about 8% by reducing the environmental hazard in European and Central Asian developing economies. The adjustment in error from the short run to the long term in each year through ECM is evidenced by Charfeddine and Khediri (2016).

Table 9

Error correction ARDL model

Dep Var = EVD_CO2
Regr	Coeff	Std Error	t-ratio
FFEC	0.121***	0.048	2.512
FFEC2	0.332***	0.119	2.789
REEC	−0.442***	0.150	−2.934
REEC2	−0.623***	0.238	−2.617
FN_DEV	0.987**	0.513	1.925
FN_DEV2	−0.012*	0.007	−1.675
KFOR	0.845	0.698	1.211
PRO_LB	0.876***	0.279	3.138
dEVD_CO2	0.935***	0.248	3.760
dFFEC	0.098	0.398	0.248
dFFEC2	0.108	0.074	1.459
dREEC	−0.059	0.082	−0.728
dREEC2	0.963	0.633	1.521
dFN_DEV	0.080	0.074	1.072
dFN_DEV2	0.101	0.121	0.832
dKFOR	0.068	0.239	0.286
dPRO_LB	0.925	0.734	1.260
ECM(-1)	−0.081***	0.023	−3.436

Note: ***, **, indicate 1%, and 5% percent significance levels

The diagnostic tests are given in Table 10, showing no serial correlation and functional form problem in the model. The skewness and kurtosis residuals have not shown any problem in the model and favored the model ' s normality. Further, the diagnostic test illustrates that there is no heteroscedasticity problem in the model. Thus, the overall model of carbon dioxide emissions, financial development and energy consumption has efficiently proved its statistical worth rather than a statistical deficiency in the model.

Table 10

Diagnostic tests

Test Stat	LM-Version	F-Version
Serial correlation	CHSQ(1) = 0.246[0.620]	F(1,288) = 0.237[0.626]
Functional form	CHSQ(1) = 0.041[0.840]	F(1,288) = 0.039[0.843]
Normality	CHSQ(2) = 19.591[0.123]	--
Heteroscedasticity	CHSQ(1) = 0.005[0.942]	F(1,297) = 0.005[0.942]

Conclusion

The study aims to examine the non-linear relationship between carbon dioxide emissions, energy consumption, and financial development. Further, the study inspects the EKC inverted U-shaped hypothesis in European and Central Asian developing economies. The eighteen developing economies of Europe and Central Asia are selected based on their income level, lower and upper-middle-income levels. At the same time, the data is gathered over the years 2010–2019 to measure environmental sustainability by relating the carbon dioxide emissions with fossil fuel energy consumption, renewable energy consumption, financial development, squared financial development, capital formation, and labor production. According to the empirical findings, the descriptive statistics and correlation matrix have evidenced the model ' s accuracy and not showed any problem like multicollinearity in the model. The mixed order of integration I(0) and I(1) among variables has preferred the Panel-ARDL test. Before applying the P-ARDL, the bound test has verified the cointegration equations in the model, confirming the long-run existence in the empirical model. Simultaneously, Pesaran cross-sectional dependency test has not shown the cross-sectional dependency in the model.

According to P-ARDL findings, the short-term analysis has confirmed the positive influence of fossil fuel energy consumption, financial development, and labor productivity on carbon dioxide emissions. Capital formation and renewable energy have no substantial influence on carbon dioxide emissions in the short run. At the same time, the non-linear influences of fossil fuel and renewable energy are positive and negative on carbon dioxide emissions in the short run, respectively. However, the negative impact of non-linear squared financial development has reduced the carbon dioxide emanations and proved the EKC inverted U-shaped premise in the short run. After this, the long-run analysis has proved that fossil fuel energy consumption and labor productivity have risen the carbon dioxide secretions. In contrast, renewable energy consumption has reduced environmental degradation by its negative influence on carbon dioxide emissions in the long run. Thus, fossil fuel consumption has a positive and renewable energy consumption negative non-linear impact on carbon dioxide emissions in the long run. Financial development positively influences carbon dioxide emissions and favors the early stages of the EKC U-shaped hypothesis in the long run. However, squared financial development negatively impacts carbon dioxide emissions, which resultantly mitigate air pollution and promote environmental sustainability in European and Central Asian developing countries. The negative influence of non-linear squared financial development on environmental degradation has proven the EKC inverted U-shaped hypothesis in the long run. In contrast, capital formation has a positive but insignificant impact on carbon dioxide emissions in the long run. Further, the study has shown the significant non-linear relationship between carbon dioxide emissions, energy consumption, and financial development in European and Central Asian developing economies. According to the Error Correction Model results, the ECM value is −0.81, which is significant. Its negative sign identifies that the speed of adjustment term reduces the error by about 8% each year from short run to long run. Moreover, the diagnostic tests have not indicated functional form problems, normality issues, heteroscedasticity, and serial correlation in the empirical model.

This study suggested that there is a need for comprehensive policies to use energy sources. First, there should be a look over the excessive consumption of non-renewable energy such as fossil fuels. It is suggested that the governments of developing economies should implement subsidize renewable energy. There should be low-cost renewable energy provided to households and firms to promote environmental sustainability and limit fossil fuel energy consumption. There is a need to update the technology, which requires the attention of policymakers. Regarding technological advancement, solar panel installation and electrification rather than burning woods and coal can help mitigate air pollution. In the end, it is suggested that the policymakers should develop the environmental sustainability model considering EKC inverted U-shaped, which will help promote their financial sector development without hurting environmental sustainability.

Limitations of the study

This study has developed the non-linear relationship between carbon dioxide emissions, energy consumption, and financial development in developing European and Central Asian economies. However, this research has limitations regarding its study area. In addition, this research has taken the countries listed as European and Central Asian countries and has developing status.

Future direction of the research

This research has a future direction regarding the study area and the adoption of energy sources to maintain environmental sustainability. This type of research will be helpful to highlight the environmental issues in other developing regions of the World. This research has measure the overall impact of fossil fuel and renewable energy sources. However, future research can examine the new form of renewable energy sources such as hydroelectricity, modern biomass, and solar paneling to measure environmental sustainability. Most importantly, this research has examined the environmental issues before Covid-19. It will be interesting to examine the influences of renewable energy and non-renewable energy consumption during and hopefully after Covid-19.