Understanding the relationship between electric power consumption, technological transfer, financial development and environmental quality

This research paper attempts to investigate both the long-run and causality relationship among electric power consumption (EPC), technological transfer, financial development (FD), and environmental quality for the Saudi Arabia (KSA) economy from 1980 to 2019. In doing so, we propose a carbon emission function tested by incorporating multi-steps techniques such as autoregressive distributed lag (ARDL) has been exploited to determine the existence of cointegration or no; while vector error correction model (VECM) has been applied to decide the direction of causality. In this paper we have proposed two proxies of technological transfer, namely imported technology (MT) and Technical cooperation grants (TCG). The results indicate the existence of cointegration between the concerned series. Besides, the existence of a feed-back effect among variables (except TCG) in the long-run. However, in the short run feed-back effect exists among EPC and Environmental Quality (EnvQ); MT and EnvQ; EPC and MT. Thus, the paper provides original visions for policy makers to encourage the technological transfer by financing and supporting the electric energy sector which constitutes the main locomotive to improve the environment quality for the KSA.


Introduction
In recent decades, climate change due to carbon (CO 2 ) emissions is one of the major environmental, political and economic challenges since it affects the whole world. Thus, it is disrupting national economies, degrading the environment, affecting lives, changing weather patterns, rising sea levels, and weather events are becoming more extreme, etc. (United Nations 2018). Regarding the Fig. 1 which determines the progress of CO2 emissions (metric tons per capita) for the KSA we observe that for the entire period 1960-2018, there is an annual average of 11.64. The change recorded between the first and the last year is 2231%. The highest value was recorded in 2018 (15.269) and the lowest value was recorded in 1960 (0.655). Based on the available data, we can estimate that in 2025 the value should hover around 13.928. This forecast has a relatively high level of reliability since the available values have a rather linear structure, despite notable variations (correlation coefficient = 0.73 and coefficient of determination = 0.54). Therefore, improved EnvQ represents an ecological, economical, financial, and sociological issue of importance and concern worldwide. Hence, humanity is required to think and act responsibly and determine sustainable solutions especially in countries with highly energy consumption and economic growth. That could be explained as the production process is conducted by the demand for energy. Whereas this demand in turn is conducted by demographic developments, level of economic activities, and by technological and structural changes (Yeager et al. 2012).
In this paper, we will focus on electricity as the main form of final energy used to power homes, transport, trades, communications and productions. According to Zhang et al. (2013) the electricity generation is the principal source of carbon, representing more than 40% of global CO 2 emissions that contribute to degradation of the EnvQ. In fact, in the KSA, growth and exports rely almost completely on industries that benefit from circumstantial advantages related to power and raw material provision, knowing that these resources will deplete over time. Furthermore, the Saudi industrial sector is heavily concentrated in these basic industries, as they represent 56% of GDP and more than 71%. of exports, relying strongly on the KSA circumstantial advantages related to energy. In addition, the KSA economy aims to achieve significant performance for key factors of transformative industries such as innovation, ability to attract and retain talents and government regulations. This situation made the Kingdom fronted to many challenges such as improving the competitiveness of the electricity sector through restructuring and exploring power exportation opportunities, increasing the share of the renewable energy sector in local consumption and enhancing the competitiveness of the energy sector. At the same time, reducing environmental degradation by creating a friendly climate while balancing the need for reducing fiscal burden; in particular, reducing electricity consumption, are the main challenges to the KSA. Furthermore, researchers have suggested that financial development like technological transfer is an important factor that could significantly affect EnvQ, and that the omission of a financial factor can lead to erroneous empirical findings (Shahbaz et al. 2016;Khan et al. 2018;Amri 2018;Demir et al. 2020;Wang 2019;Eren et al. 2019;Ibrahiem 2020;Nguyen et al. 2020;Avom et al. 2020;Alola et al. 2019;Zameer et al. 2020). From a theoretical perspective of the impact of FD on EnvQ, researchers have presented conflicting views: negative and positive effects of FD on EnvQ. For instance, to decrease production costs and improve product competitiveness in the market, companies must periodically update the technology and production equipment that depend on adequate financial support. Besides, to cope with environmental degradation, governments generally tend to initiate various environmentally friendly projects, promote overall industrial transformation and the use of clean energy. However, the development of the financial sector could bring more and better service of consumer credit, which facilitates their intertemporal consumption and encourages them to buy more goods such as properties, automobiles and other electrical devices.
Besides, financial development plays a crucial role in this debate on the relationship between technological transfer, electricity consumption and the quality of the environment. In fact, the development of financial markets helps reduce financing costs and channel financial resources in order to purchase fresh equipment and fund new projects, which in turn, creates energy demand and affects EnvQ (Shahbaz et al. 2016). Moreover, financial development supports energy efficient technologies by encouraging technological transfer and hence shrinks EnvQ.
In this context, this study aims to investigate the role played by energy, specifically EPC, technological transfer and FD on EnvQ. As well to understand the long-run and the causal relationships between variables, we applied a multisteps methodology based mainly on ARDL and VECM Granger causality approach. This methodology demonstrates the effects of relevant technology, financial and economic factors to promote the quality of the environment in the KSA. To the best of our knowledge, there has never been any endeavors to investigate both the long-run and the interactions among EPC, technological transfer, FD and EnvQ for the KSA economy.

Literature review
The existing environment and energy literature have rarely examined the relationships among EPC, technological transfer, FD and EnvQ especially in the KSA economy. This current paper exposes specifically the most relevant studies that are related to our variables of interest by classified the existent reviews in three research strands. The first one examines the relationships among EPC, technological transfer and EnvQ. The second strand investigates the relationships between EPC, FD and EnvQ while the third explores the associations among FD, technology transfer and EnvQ. As well, each strand is classified by type of conclusion, as there are diverse results in those studies presented in the literature review. As Table 1 proves, the discoveries of these studies are inconclusive.

EPC-technological transfer-environment nexus
The studies on the relationships among energy, technology and environment has been the recent trend in the environment and energy literature (Zhang et al. 2013;Mariano et al. 2016;Wang and Wang 2018;Peng and Tao 2018;Kahouli 2018;Rumayor et al. 2019;Zafar et al. 2020;Altıntaş and Kassouri 2020). To be more specific, Mansouri et al. (2013) have studied the Saudi electricity sector focused on 18 different forecast figures for CO 2 emissions engendered by electricity for each year from 2010 to 2025. They have suggested that Saudi government must declare objectives to reduce CO 2 emissions and to invest seriously in evolving its own progressions and innovations in energy technologies. In the case of China, Wang and Wang (2018)  On the other hand, some researchers argue that the technology ameliorates the environment quality in different interpretations. Hodson et al. (2018) have estimated the importance of technology innovation, the fuel prices, and CO 2 emissions on electric power productions from four U.S. energy-economic models through the year 2050. Results have shown that realizing innovation aims to decrease CO 2 emissions owing to improved energy efficiency. Further, Ali et al. (2019) have investigated the Kuznets curve of Malaysia over a period of 1985 to 2016 by using the ARDL method. The results have suggested that improved technology can lead to a cleaner environment. Consequently, there are bidirectionally linked between environment and energy consumption as well as between structural changes and technological innovation. In another paper, Alola et al. (2019) have analyzed the role of renewable energy consumption and economic growth to ameliorate EnvQ by using ARDL approach to 16 European Union countries for the period 1997-2014. Empirical results have confirmed that renewable energy enhances EnvQ. Focusing in Thailand, Wattana and Wattana (2020) have developed three scenarios that represent penetration levels of electricity generated from renewable energy for the period 2018-2037. The results have indicated the importance of technology innovation in renewable energy that positively affects the electricity generation with a particular focus on energy security and CO 2 emissions mitigation potentials. More recently, Zameer et al. (2020) have explored the effects of technological innovation and energy use on CO 2 emissions in the Indian economy during the period 1985-2017 by employing the ARDL and the VECM methods. They have confirmed the existence of long-term cointegration and energy consumption positively stimulates CO 2 emissions. Whereas, technological innovation negatively reinforces environment quality in the long term.

EPC-FD-environment nexus
The relationship between EPC, FD and environment has been well proven this is last years for instance Sadorsky (  Emirates. Consequently, there is a long-term and one-way causality from carbon emissions to energy consumption for some countries such as the KSA, UAE and Qatar. Thus, the financial systems of GCC countries should consider environmental aspects in their decisions while preserving economic growth. In the same line, Kahouli (2018) has studied the four-way association linkages among EPC, CO 2 emissions, FD, R&D and real GDP for the Mediterranean countries from 1990 to 2016 by using SUR, 3SLS, and GMM estimators. Empirical results confirm the existence of strong feedback effects between variables. In the same context, Xu et al. (2018) have explored the contribution of FD to environmental degradation in the KSA by applying ARDL and VECM methods to observe the long-term causal relationship. The results have shown that FD contributes to the degradation of the quality of the environment and that EPC is the principal responsible for the environmental degradation in the KSA. Alternatively, the causality is mutual and bidirectional between long-term CO 2 emissions and FD. Acheampong et al. (2020) have explored the impact of the financial market and energy consumption on CO 2 emissions intensity. They have used the GMM technique for 83 countries over the period 1980-2015, they have revealed that financial markets moderate growth and energy to stimulate environmental degradation. In another perspective, Shahbaz et al. (2020) have examined the link between EPC, FD and environment by using the Toda-Yamamoto causality test. The finding indicated that FD raises CO 2 emissions and real GDP is completely associated with environmental degradation. While, EPC improves the EnvQ. According to those studies, the empirical findings are conflicted. Probably, the principal reason for these various results derives from the data, econometric approaches and the level of development of the country in which a study is being carried out. Thus, it is essential to carry out new exploration concerning the relationship between EPC, technological transfer, FD and EnvQ.

Data
In this paper we explore both the long-run and causality relationship among electric power consumption (EPC), technological transfer, financial development (FD), and environmental quality. All the data are collected from the world development indicators (WDI) online database (Appendix.1). The study covers annual data over the period of 1980-2019 for the KSA economy. The period of the current study is selected on the accessibility of data. All variables were transformed into natural logarithms.
The fundamental theoretical concept/justification for choosing these variables is stated below. Starting with the environmental quality (EnvQ) which is measured by CO2 emissions from electricity and heat production, total (% of total fuel combustion). In fact, many studies consider CO2 emissions as an environmental variable such as Hung and Derossis (1989); Alam et al. (2015); Charfeddine and Khediri (2016); Mahmood et al. (2020); Chen et al. (2020). Likewise, electric power consumption (EPC) determines the production of power plants and combined heat and power plants (kWh per capita). Furthermore, Technology transfer is the term used to describe the processes by which technology is exchanged between countries. The technology transferred can take various forms. For example, Ang (2009); Sinha and Shahbaz (2018); Wang and Luo (2020) have proved that technological transfer is an important factor influencing environmental quality. In this study, we propose two proxies. The first proxy determines the imported technology (MT), we utilize computers, communications and other services (% of commercial service imports) including such activities as international telecommunications; computers. Imports of capital goods and high-tech goods allow firms to acquire innovative environmental technologies, and it is above all thanks to the presence of multinational firms on Saudi territory that the software components of the technology can be transferred. The installation of foreign firms using advanced technologies increases the specific know-how available to the recipient economy, the appropriation and adaptation of environmental technologies depending on its absorption capacities. The second variable as a proxy of the technological transfer is technical cooperation grants (TCG). Thus, TCG comprises free-standing TCG, which are proposed to finance the transfer of technical and managerial skills or of technology; and investment linked TCG, which are required to reinforce the capacity to achieve specific investment projects (current U.S. dollars).
Following most prior studies like Mugableh (2015) (2019), we consider domestic credit to the private sector (% of GDP) as the measure of FD. From a theoretical perspective of the influence of FD on EnvQ, researchers have presented conflicting observations: negative and positive effects. First the negative effect due to decreasing production costs and improving product competitiveness in the market, companies must periodically update the technology and production equipment that depend on adequate financial support. Besides, to cope with the environmental degradation, governments generally tend to run various projects environmentally, to promote overall industrial processing and use of clean energy. Second, the positive effect explained by the development of the financial sector could bring more and better service of consumer credit, which facilitates their intertemporal consumption and encourages them to buy more goods such as properties, automobiles and other electrical devices.
Therefore, Table 2 determines the descriptive statistics of these series for the KSA economy. It denotes that all series are normally distributed as exposed by statistics of the Jarque-Bera test. Pairwise correlation analysis denotes that EPC, TCG and FD are positively associated with EnvQ. Likewise, TCP and FD are positively associated with EPC. However, the correlation between MT with EnvQ and EPC are negative. Also, the correlation analysis indicates that TCP and FD are negatively linked with MT.

Model specification
The main purpose of the current study is to investigate the determinants of EnvQ in the case of the KSA economy by taking into account the role played by EPC, technological transfer and FD. The relationship among the level of EnvQ (CO 2 emissions) as endogenous variable with the different exogenous and control variables have long been examined simultaneously (Jayanthakumaran et al. 2012;Wang and Wang 2018;Kahouli 2018;Shahbaz et al. 2020). In fact, we propose a multi-steps methodology based mainly on ARDL procedure and VECM. The ARDL procedure used to estimate the long run and short run relationship presents several advantages: First, it can be applied without having the same order of integration or to have the same optimal lags for all variables in the system. Second, it is particularly useful for this study because it doesn't require large samples or absence of endogeneity between regressors to obtain an efficient estimator. Third, the ARDL does not demand to have multiple equations because a single reduced-form equation may lead to the same findings. The present study considers the following EnvQ function: The econometric model for this study is specified as follows: The model transformed to log-linear functional form and stated as below: where EnvQ shows, carbon dioxide emissions from electricity and heat production, total (% of total fuel combustion), EPC is electric power consumption per capita, MT is imported technology measured as computer, communications and other services imports, TCG is ln EnvQ t= 0 + 1t ln EPC t .2t ln MT t + 3t ln TCG t + 4t ln FD t + t Technical cooperation grants; the both variables are used as proxies for technological transfer, FD shows domestic credit to private sector proxy for financial development. α 0 , t, and ε are respectively the fixed country effect, the time and the residual term.
At the start we will verify the order of integration of the variables by utilizing Augmented Dickey-Fuller (ADF) test of Dickey and Fuller (1981) and Phillips-Perron (PP) test of Phillips and Perron (1988). Once proving integration, the next step will be the choice of appropriate criteria; we will propose Akaike Information Criterion (AIC) for this paper to identify appropriate lag length. The AIC is preserved in view to choose the smallest lag length value and to reduce the loss of a degree of freedom (Jayanthakumaran et al. 2012 andAhmed et al., 2015). Likewise, to capture the dynamic results, an AIC is envisaged as superior and effective compared to Schwarz Information Criterion (SIC), which delivers more effective and reliable findings. When the lag length is designated, we will examine the cointegration among variables, doing so, we will suggest Johansen cointegration in our study. After confirmation of cointegration among variables, we will try to examine the long-run and short-run relationship. Furthermore, to verify the constancy of the model and to confirm finding for policy-maker, this paper applies robustness tests, i.e., Reset test, ARCH test and LM test. The cumulative sum of recursive residual (CUSUM) and cumulative sum of the square of recursive residual (CUSUMsq) tests will be used to verify the stability of the model to recommend policies for implication. Finally, we will turn to examine the direction of causality among variables. In this context, we will propose the VECM Granger causality approach in order to determine the direction of causality among EPC, MT, TCG and FD. Consequently, the empirical equation of VECM Granger causality approach is modeled as follows: When the error correction term ECT t − 1 is statistically significant with a negative sign; it is the indication of longrun causality. Furthermore, we employ Wald test to calculate the short-run causality.

Stationary tests
This paper applied the ADF and PP unit root tests on the natural logarithms of the variables in level and difference forms to explore the relationship between, EPC, technological transfer, FD and EnvQ in the KSA. The results described in Table 3 reveal that all the variables of the study are stationary at the first difference, which justifies the application of the ARDL technique.

ARDL cointegration tests
After proving that all the variables share the same integration properties, we move now to investigate the long-run and short-run coefficients by using the ARDL cointegration method. This technique is established on two main steps. Beginning with the first step, the long-run relationship of Eq.
(4) will be clarified by investigating the order of lag. This one will be involved to estimate VAR or VECM models that are attained from unrestricted VAR model and by maximized likelihood ratio (LR) criterion, minimized final prediction error (FPE), AIC, SIC, and Hannan Quinn (HQ) criteria. The results of this stage lead to conserving the optimal lag which is found to be 1, except AIC (Table 4).
Regarding the output of Johansen cointegration (Johansen 1988;1991) he has engendered two statistics, trace statistic and Eigenvalues. The result of trace statistics and Eigenvalues for the KSA assume that there are at least four cointegration relationships that exist among cited variables and the null hypothesis of no cointegration can be rejected. The results of the Johansen test are reported in Table 5.
In the same order, we apply the minimization of AIC and SC (the lag length is used to be 1) to find the order of lags. The order of optimal lags is reported in Table 6. For both AIC and SC, guides to choosing the same optimal lags (1,0,0,0,1).
In the second step, we estimate Eq. (4) to evince the long-run and short-run coefficients based on sample data between 1980 and 2019 for the KSA by applying ARDL technique (Table 7). The empirical results display the lowest value of the 1-year lag in CO 2 emissions coefficient by -2.95E-05. Furthermore, the results of EPC indicate a longrun and short-run positive effect on CO 2 emissions. More precisely, a 1% increase in EPC will lead towards 0.106% increase in environmental degradation. The result is in line with previous studies of Akpan and Akpan (2012); Bella et al. (2014); Cetin et al. (2018) and Kahouli (2018) who detected a positive and significant link among energy and CO 2 emissions in the short-run and the long-run.
Likewise, EPC contributes to an important volume of CO 2 emissions in the KSA economy, which requires policymakers to design a policy that decreases EPC through the provision of economic incentives for energy saving. However, the coefficient of MT is negative and significant in the long-run which implies that this variable decelerates environment degradation for the KSA. Precisely, a 1% increase in MT may decrease CO 2 emissions by 0.174%. These results support the finding of Kahouli (2018); Wang  Table 6 Order of optimal lags Italicized and bold statistics denote the minimized AIC and SIC values.
Number (2020) since it shows that MT reduces CO 2 emissions. This is due to the fact that technical progress is able to degrade CO 2 emissions due to government decisions which incite domestic producers to exploit environmentally friendly technologies. Therefore, MT in the shape of computers and communication are environmentally friendly. Otherwise, the modern technology transferred to the KSA promotes environmental quality. The Government of the KSA needs to consolidate input in R&D and ICT for higher technological strength which will be favorable for protection of the environment. In addition, the short-run estimate of CO 2 emissions with respect to TCG is negative and significant at the 10% level. In more details, a 1% increase in TCG may decrease CO 2 emissions by 0.121%. Nevertheless, in the long-run this coefficient is insignificant indicating that TCG has no impact on EnvQ, which suggests that TCG is not helpful to the environment of the KSA, and it does not accompany any contribution in environmental degradation. One probable reason for this insignificanct relation is that the KSA has satisfied their need by funding the transfer of technical and managerial skills of technology. Finally, the coefficient of FD is positive and significant at the 10% level. It shows that a 1% increase in FD leads to rising CO 2 emissions by about 0.293%. The results are in line with the findings of Ali et al. (2016); Kahouli (2018); Shahbaz et al. (2020) and Acheampong et al. (2020) who confirm the existence of a significant relationship between FD and EnvQ. The development of the financial sector of the Saudi economy plays a very dynamic role in economic growth which directly affects EPC, and therefore has an environmental degradation effect. In fact, the efforts to respond to the progressive energy demand coupled with the mitigation of climate change represent a hard task for governments that need several technological innovations, FD with a rational environmental policy. In this context, Shahbaz et al. (2016) have approved that developed financial markets help reduce financing costs and channel financial resources in order to purchase fresh equipment and fund new projects, which in turn, creates energy demand and affects EnvQ. Furthermore, their analysis indicates that FD supports energy efficient technologies and hence shrinks EnvQ. At this level, the FD plays a crucial role in this debate on the relationship between technological transfer, electricity consumption, and the quality of the environment.
The coefficient of lagged error term i.e. ECM are negative and statistically significant at 5 % level, confirming that the long-run relationship among EPC, technological transfer (MT and TCG), FD and EnvQ exist in the case of the KSA economy. In the same order, we apply numerous diagnostic tests to confirm the stability of the model. The results of these tests are reported in the lower portion of Table 7. It is established that there is no serial correlation and heteroscedasticity in the model according to the Breusch-Godfrey serial correlation LM test. Moreover, the value of R2 for the model shows goodness of fit. The F-statistic which measures the joint significance of all regressors in the model is statistically significant at the 1% level. The Durbin-Watson statistic is about two; thus, we can deduce the absence of autocorrelation among residuals (prediction errors) from a regression analysis. Besides, the results of sensitivity analysis of CUSUM and CUSUMsq tests suggest that the model applied in this paper is well proven. The results of both the graphs are exposed in Figs 3 and 4 (Appendix.2.). Both lines plotted within the two straight lines, which are bound by 5% level of significance. Otherwise, the plots of both statistics are within the boundaries, which establish that the pollution model does not violate any assumption. Hence, the model is stable and estimated results are trusted and well considered for policy practices.

The VECM Granger causality tests
The existence of cointegration among series approves that there ought to be at least four causal relationships; however, it fails to give its direction. Likewise, the present research investigates the direction causal relationship by applying error-correction models based Granger causality tests. Such knowledge is useful in making suitable environmental, energy, technological and financial policies for sustainable development in the case of the KSA (Fig. 2). The results on the direction of the long-run and short-run Granger causality are stated in Table 8. Regarding the long-run causality, all the ECT coefficients are negative and statistically significant proposing bi-directional causal relationships between the variables (except TCG). Otherwise, our results find that there is an indication of four causal relationships.
First causal relationships from EPC, MT, TCG and FD to the environment. Second causal relationships from environment, MT, TCG and FD to EPC. Third causal relationships from environment, EPC, TCG and FD to MT. Fourth causal relationships from environment, EPC, MT and TCG to FD. Nevertheless, an exception is shown for the TCG equation, which is negative and not statistically significant. This suggests an absence of long-run causality from the environment, EPC, MT and FD to TCG. This analysis supports the argument that FD improves EnvQ by prompting the firms to implement advanced technology which emits less CO 2 emissions during production and/or consumption. These findings are consistent with Talukdar and Meisner (2001); Shahbaz et al. (2013) and Avom et al. (2020) who suggest that ICT affects CO 2 emissions through energy and FD. Besides, EPC is Granger caused by FD is consistent with the view studied by Shahbaz and Lean (2012) that the financial sector enables firms to adopt advanced and efficient electric technology during the production and/or consumption. In fact, EPC contributes a significant amount of CO 2 emissions to the economy of Saudi Arabia. Improving electricity production techniques or a more diversified energy mix can reduce pollution from the electricity sector in the KSA. The augmented utilization of EPC causes serious degradation of the environment and only the financial and technological factors have the ability to reduce CO 2 emissions and improve the quality of the environment. However, there is a need for policymakers to design a policy that lowers the EPC by providing economic incentives for energy saving. Besides, the MT slows down the degradation of the environment for the KSA. Nevertheless, when KSA's economy is focused on the manufacturing sector.
The effect is gradually removed as the economy shifts to the service sector which needs less energy with a better strategy for environmental protection. Meanwhile, the discovery of unidirectional causality of MT with respect to the environment indicates that importing technology is an important part of the nation's economic prosperity. This is due to government decisions that encourage domestic producers to exploit environmentally friendly technologies Table 9.
In the same order, results in Table 8 reveal the evidence of three short-run bidirectional granger causality confirming the  Finally, several policy implications could be derived from this study. First, these results call the policymakers and the government of the KSA for more consideration in the subject of environmental protection, since electric power and FD cause environmental degradation (in the short-run and longrun). Thus, the KSA may impose some pollution control policies such as raising the environmental taxes, positioning restraints on activities source of environmental degradation, promising academic institutions and environmental projects that may explain how to use and apply the methods of environment protection. At this level, policy makers have to promote and consolidate the environment quality, and increase the utilization of cleaner energy sources in order to decrease CO 2 emissions and to develop the FD sector. Second, the technological transfer has improved the environment quality in the KSA. Government willing to reduce EPC has been clear with different implemented legal constraints to use the best products in terms of electricity use taking into account technological innovation in this field. This shows that the KSA government is already on the right path in improving the living standard of the nation by implementing environmental friendly projects.

Conclusion and policy implications
One of the most important strategic objectives of Saudi Arabia 2030 vision is to support efforts and commitment to deal with environmental and economic issues. In this context, this paper examines the effect of relevant technological and economic factors contributing to promote the EnvQ. In the same way, we focus on the effect of the technological transfer (MT and TCG) on CO 2 emissions by integrating several variables such as EPC and FD for the KSA for the period 1980-2019. In the light of our empirical results, we have concluded that there is mutual dependence between EPC and CO 2 emissions in the short-run and the long-run and FD is positively related in the short term with EPC. Besides, we have concluded that the development of the financial sector of the KSA plays an important role which is direct and dynamic for the improvement of environment quality. Accordingly, the technological transfer negatively affects the EPC. So, EPC has also proven to be an important factor in increasing CO 2 emissions. It is evident that there is a strong relation among FD, technologic transfer, EPC and environment for the KSA economy. Otherwise, we observe that import technology (MT) and TGG are negatively related to EnvQ. In accordance with these findings, the government ought to focus on importing technology to reduce CO 2 emissions, especially the implementation of national green technology. They should adopt multi-year energy cost techniques. Indeed, policymakers should seek and encourage cleaner sources of energy consumption to conserve electricity or use it more efficiently for consumers. In this regard, there is a need to adopt policies for the development of electricity networks in the various cities of the country to achieve energy savings. The application of this type of policy makes it possible to reduce CO 2 emissions. The Saudian government should launch policies based on renewable energies, in particular solar and wind energy, which provide electricity without causing an increase in CO 2 emissions. In accordance with these findings, the Saudi government ought to focus on importing technology to reduce CO 2 emissions, especially the implementation of national green technology. They should adopt multi-year energy cost techniques. Indeed, policymakers should seek and encourage cleaner sources of energy consumption to conserve electricity or use it more efficiently for consumers. In this regard, there is a need to adopt policies for the development of electricity networks in the various cities of the country to achieve energy savings. The application of this type of policy makes it possible to improve EnvQ.
This result contributes to designing some technological, environmental and financial policies for the KSA. In fact, the policy makers ought to create and to support environmental protection and the green economy. Additionally, the importance of FD in the KSA economy increases the share of the energy sector without harming the environment. We are well aware that the government is moving towards a nonpetroleum economic diversification strategy to have more investment flows in the energy domain while encouraging technological transfer. Therefore, to achieve this, the government is increasingly subsidizing technological projects aimed at reducing energy consumption and thus having a beneficial effect on the environment. In fact, this approach makes it possible to maintain environmental stability and to avoid any negative effects. Likewise, the incorporation of energy efficient technologies into the energy electric segment of the country can be a means of protecting the quality of the overall environment. For this raison, the KSA aims to conserve electricity or use it more efficiently for consumers. Thus, the comprehensive approach to energy policy aims to reduce cost disparities through less subsidies to conventional energy. In this regard, it is necessary to adopt techniques of the cost of energy over several years such as that provided for in their vision 2030. Indeed, policymakers should seek and encourage cleaner sources of energy consumption. They should develop policies for the development of electricity networks in the various cities of the country to achieve energy savings. The application of this type of policy makes it possible to reduce CO 2 emissions. In addition, applying a smart tax system at the same time helps prevent damage to the environment. To conclude, encouraging the technological transfer, facility spillover knowledge, promoting innovation and consolidating R&D activities by financing and support of electric energy sector strategies constitutes the main locomotive to improve the environment quality for the KSA.