Energy transition and environmental quality prospects in leading emerging economies: The role of environmental-related technological innovation

The world has witnessed a significant rise in greenhouse gas emissions since the end of the 20th century as several economies begin to emerge into industrial hubs and manufacturing giants across the globe. Thus, in the wake of global interest in clean energy development and campaign for sustainable climate and ecosystem, the role of the emerging countries in the debate is unarguably vital and demanding. Importantly, this study seeks to examine the commitment of the leading emerging countries (E7) of Brazil, China, India, Indonesia, Mexico, Russia, and Turkey to energy transition and carbon-neutral 2050. We employ the cross-sectionally augmented auto-regressive distributed lag approach that accounts for potential country-specific factors to examine the role of environmental-related technological innovations (ERT) in achieving climate neutrality in the E7 over the period from 1992 to 2018. Notably, the findings revealed that a 1 percent increase in ERT yields (cid:1) 0.33% (short-run) and (cid:1) 0.17% (long-run) reductions in carbon emission, thus suggesting that the E7 economies could be heading toward environmental sustainability with the application of ERT. Additionally, the result revealed that the application of ERT in the energy utilization profile significantly reduced the undesirable impact of primary energy utilization. However, the result showed that such an impact is not enough to trigger a transition to environmentally desirable cleaner energy that could mitigate carbon emissions. This is because the larger share of the E7 countries' primary energy utilization is from conventional and/or non-renewable energy sources. The environmental Kuznets curve hypothesis is also validated.


| INTRODUCTION
From a historical perspective, advanced economies mainly the United States of America (US) and those in Europe (precisely Western Europe) have dominated the major point of discussion about greenhouse gas (GHG) emissions mitigation following the early industrial revolutions (Alola, Adebayo, et al., 2021;Alola, Akadiri, et al., 2021;Allen, 2009;Friedrich & Damassa, 2014;Kasa, 1973). However, the world has seen a dramatic change in emissions trajectory and the composition of major emitting economies toward the end of the 20th century until date. This change occurs as many other economies begin to emerge into industrial hubs and manufacturing giants across the globe. Some of the countries in this category have been classified into various groups. As a prominent group of countries, the world's Emerging seven (E7) economies consisting of China, India, Brazil, Mexico, Russia, Indonesia, and Turkey are increasing gaining more attention in the subject of global climate change (Alola & Nwulu, 2021;Etokakpan et al., 2021;Huang et al., 2021;Zoaka et al., 2022).
Based on available reliable data, emissions levels have greatly increased among the E7 economies over the last few decades and this bloc of countries is arguably the largest contributor to the global emissions in recent times. Countries like China have emerged as the topemitting nation accounting for over 27% of total emissions as of 2017 according to the United Nation Emission Gap Report (UNEP, 2018). Jiang et al. (2022), noted that greenhouse gasses (GHGs) have been a major challenge to global environmental sustainability, and energyrelated carbon emissions, in particular, stand out as a major concern in countries like China. Other countries among the E7 also contribute to a significant chunk of the global carbon emissions for instance about 7.1% of the total greenhouse gas (GHG) emissions were attributed to India. In the South and Central America region, Brazil accounts for the highest emissions with about 35.02% of the region's total carbon dioxide emissions (British Petroleum, 2020). Emission is also fast growing in Turkey, Indonesia, Russia, and Mexico as seen in Figure 1.
As of 2018, China leads in emission among these countries followed by India, Russia, Indonesia, Mexico, Brazil, and Turkey, respectively, and carbon emission level is yet to peak in most of these economies.
On the other hand, the literature is currently replete with the dangers of unabated emissions of anthropogenic CO 2 and other greenhouse gases (GHGs) emissions (IPCC, 2007, 1 ;Jolly et al., 2015;Anderson & Bows, 2011;Alola, Adebayo, et al., 2021;Alola, Akadiri, et al., 2021). Besides, growing emissions levels have been identified as a major factor contributing to rising levels of environmental disasters with predictions of more dangers ahead if nothing is done to curtail cumulative emissions in the meantime (IPCC, 2021;UNEP, 2021). Furthermore, Mora et al. (2018) noted that an approximate 584.4 GtC (gigatons of CO 2 ) was emitted from human activities including the burning of fossil fuel, industrial activities, and land use between 1860 and 2014. This was also estimated to have resulted in about 0.9 C of global warming as the global average temperature has maintained an upward trend over the decades as seen in Figure 2.
Therefore, in the wake of the rising potential dangers of climate change and environmental disaster vis-à-vis increasing GHG emission levels, the impact of innovative technology on carbon emission levels and its significance for achieving the global zero-carbon target is gradually attracting the attention of researchers. At the moment, the bulk of the research relating to the environmental impacts of innovation has addressed countries in the OECD bloc and a couple of Asian economies (Álvarez-Herránz et al., 2017;Amin et al., 2020;Godil et al., 2021;Shahbaz, Raghutla, et al., 2020). However, there is the concern that countries in some of these blocs may not necessarily be at the same tier of economic progress or development. To the best of the authors' knowledge, none of the existing studies has addressed the innovation-emission nexus for the specific case of the E7 economies except for the most recent study by Tao et al. (2021). However, just like most studies on other blocs mainly considered the innovation-emission nexus, their study also did not examine whether the expected desirables environmental impact of innovation holds in the E7 when interacting the level of innovations with the weights of the overall energy use per capita among these countries. This aspect is however very crucial when considering the quest for wealth creation as seen in the push to maintain economic growth which is a major trait among all economies and most especially for emerging F I G U R E 1 CO 2 emission in the E7 (end of 2018). Authors' computation using data from British Petroleum (2020 c. Thirdly, within an income-sustainability framework, the study further aims to examine the EKC conjecture for the E7 countries when technological innovation is being accounted for.
Following the introduction as the first chapter, the other part of this study has been subsequently structured into four sections with the review of the literature in Section 2 while providing the details about the methods of data analysis in Section 3. Subsequently, the discussion of findings comes up in Section 4, and Section 5 wraps up the study with policy matters.

| THEORETICAL AND EMPIRICAL UNDERPINNING
The theoretical underpinnings behind this study are the environmental Kuznets curve (EKC) conjecture (Kuznets, 1955) and the Jevons technological innovation paradox (Jevons, 2001). On the aspect of economic growth-environment nexus, the EKC conjecture argues that although the environment may be in jeopardy of pollution at an initial rate of economic growth, the detrimental environmental effects of growth will later clear out at a growth peak after which higher growth would only produce a cleaner environment Onifade, 2022). To compensate for the initial pollution levels at a higher stage of income according to the EKC conjecture, important factors such as technological innovation among others, have to be integrated into the environment-income nexus.
It is a conventional belief that technological innovations can enhance environmental sustainability, especially from the perspective of improvement in energy efficiency. However, William Stanley Jevons in 1865 (Jevons, 2001) in his seminar work demonstrated that energy efficiency (through innovations) may not really enhance sustainability as often expected through a reduction in aggregate energy consumption or resource use, on the contrary, it would rather increase consumptions. This view has been popularly regarded as the Jevons paradox and the paradox has been a long-held environmental point of discussion among economists. Inter alia, Bunker (1996) argued that large-scale economic production activities for profit-seeking in a typical economy where the focus is on growth can lead to an increase in overall energy use, even in the presence of potential higher energy efficiency that is achievable through energy technological innovations. Hence, the question of what roles technological innovations play in environmental sustainability may not necessarily follow a straightforward answer especially when the issues bordering on energy use and the quest for economic growth are accounted for.
F I G U R E 2 Global average temperature trend . Computed by authors using data from Ritchie and Roser (2020). The blue color shows the median temperature anomaly  average, while the dotted line is the trendline. The orange and gray lines are for upper and lower confidence intervals, respectively. The horizontal axis is for average temperature ( C) and years are on the horizontal axis. [Colour figure can be viewed at wileyonlinelibrary.com]  (2016) also revealed similar results that buttressed Jevons's argument.
They studied a panel of selected countries and their finding showed that there is a higher tendency to have higher energy consumption and CO 2 emission from nations with a higher level of energy efficiency. In other words, carbon emission has the tendency to rise in countries with more innovative capacity to improve energy efficiency. This is because the environmental deficits of increased energy consumption rates such as carbon emission due to energy innovation can outweigh the benefits of the increased energy usage itself. Therefore, technological innovations may not really enhance solutions to environmental challenges, especially given the insatiable quest for economic growth that is often propelled by higher energy demand on the ambient of fossil energy consumption. Hence, the validity of the EKC phenomenon also needs to be well scrutinized by accounting for the impact of innovation.

| DATA AND EMPIRICAL METHOD
The summarized details of the data used for the empirical analysis are provided in Table 2. The analysis covers observations from the E7 countries between 1992 and 2018. The dataset used did not cover the pre-1992 periods due to restrictions in data availability on technological innovation for some of the countries, especially Turkey and Indonesia.

| Empirical model
Equation (1) was structured as a baseline model for exploring the roles of technological innovation and energy use in the environmental quality of the E7 Economies. An interaction term between technological innovation proxy and energy use was also incorporated into the model to assess its influence within the framework of the economic growth recorded among the rapidly emerging seven countries.
In the functional Equation (1)

| Empirical procedures
The analytical approach in this study opens with a critical examination of the datasets for an understanding of their properties. Such critical examinations position researchers for making a well-informed decision  (Adebayo et al., 2022;Erdo gan et al., 2022;Gyamfi et al., 2021;Gyamfi et al., 2022;Onifade, Gyamfi, et al., 2021). The findings relating to the tests affirm the presence of CD (see Section 4 for the full results).
Given the valid insights on the presence of CD, the stationarity test to be adopted for variables and corresponding cointegration examinations must be capable of addressing the CD challenge. As such, the IPS and CIPS techniques were applied in exploring the stationarity properties of the variables. These unit root methodologies are useful for observing variation within panels and the techniques also provide essential features for observing the second-order generation in a typical panel analysis. The equational expression of the CIPS procedures is given in Equation (2), while the corresponding test statistics estimator is presented in Equation (3).
In Equation (3), the CDF reflects the cross-sectional dependent aug- observations. This cointegration method is modeled after an error adjustment process as depicted in Equation (4) to ascertain long-run relationships between variables vis-à-vis the estimated group statistics (Gt, Gα,) as well as panel statistics (Pt, Pα).
In Equation (4) In the error adjustment procedure of a simplified panel ARDL model, as shown in Equation (5), the adjustment term is represented by On the other hand, the δ i coefficient denotes the expected groupspecific correction speed which ought to be negative and significant to uphold its validness while the corresponding short-run estimates are captured by the β ij and π ij parameters. The traditional panel ARDL still retains its validity regardless of the cointegration order but the estimates become unreliable if errors are cross-sectionally correlated.
Thus, to bypass this setback, the panel CS-ARDL augments the model with the cross-sectional averages of the explanatory variables, the dependent variables, and a combination of their lag values to effectively correct the cross-sectional correlation in the error component.
Hence, the augmented representation of the model for the CS-ARDL is given in Equation (6).
In Equation (6), the cross-sectional average of the variables Y it and X it are denoted by Y t and X t , respectively, while the level components of the cross-sectional averages are utilized in capturing the longrun equilibrium interactions as encapsulated in the bracket.
The pace of equilibrium correction is denoted by δ i , while ϑ i captures the needed long-run estimates. The results of the estimates were provided in the discussion section. From there, the estimates from the panel PMG-ARDL approach of Pesaran et al. (1999) were also reported for sensitivity checks and comparative analysis before finalizing the analysis with a granger causality report following the Dumitrescu and Hurlin (2012)   Further results from the preliminary evaluations confirmed that the dataset for the study suffers from cross-sectional dependence (CD) as seen in Table 5. All the test statistics lend credence to the presence of CD and as such, the unit-root test conducted also took cognizance of this crucial issue. In Table 6, the findings from the CD-  Table 6, the study adopted the CS-ARDL panel estimator to examine the long-run coefficients as reported in Table 7.

| Coefficient and causality estimates
The output of the empirical results from the CS-ARDL model provides critical information that is apt for policy directives for the E7 economies unlike the results from the PMG techniques that are unreliable due to the challenges of CD that have been established in the preliminary analysis. Hence, following the CS-ARDL estimates in Table 7, the results reveal that both energy consumption and economic growth (real income levels) occur as significant drivers of environmental pollution in the E7 countries. According to the estimates, a percent rise in energy consumption level and economic growth levels induce pollution from CO 2 emissions by 0.51% and 0.68%, respectively. The observed impacts of these two variables reflect the destructive consequences of the environmentally detrimental economic growth push among the E7 countries. The upward trend in the level of economic growth is anchored on increased energy demands that are essentially sustained by fossil fuel usage which is known to constitute the largest chunk of the total primary energy consumption in the emerging seven (E7) economies. The observed environmentally T A B L E 6 Unit root and cointegration results

CIPS approach IPS approach
Intercept and trend Intercept & trend destructive impacts of economic growth and energy consumption, in the long run, are also consistent with the short-run estimates from the model. Also, there is a two-way causality between energy consumption, economic growth, and carbon emissions among these countries as seen in Table 8 (Amin et al., 2020;Shahbaz, Raghutla, et al., 2020;Tao et al., 2021).
However, on the aspect of the impacts of the interaction between innovation and energy consumption, the empirical analysis produced contrary evidence for upholding the innovationenvironmental sustainability nexus as a percent rise in the interaction of these variables significantly induces pollution from CO 2 emission by around 0.096%. Although this magnitude is relatively low compared to the impacts of other variables, it, however, portends crucial information about the E7 economies. A possible explanation for this result among the emerging seven (E7) countries is that the environmental gains from innovations tend to be significantly undermined or at least overwhelmed by the magnitude of the impacts of the unsustainable energy portfolios that features environmentally detrimental energy sources as the largest share of the overall total primary energy consumption. Another important point is that the innovation being witnessed among the E7 countries vis-à-vis the energy required to actualize their desired economic growth target has perhaps mainly accelerated higher rates of overall energy use rather than creating a reduction in energy intensity via higher efficiency as expected. Thus, the scenario at play partly aligns with the arguments of Jevons (Jevons, 2001) that innovations may not enhance overall environmental sustainability as expected by a reduction in energy consumption on a broad scale, even though it can reduce carbon emissions levels. Besides, looking at the granger causality in Table 8, it can be further observed that the only directional causality from innovations relates to energy consumption and the latter variable has witnessed exponential growth in the E7 countries over the last couple of decades (British Petroleum, 2020).
Lastly, while a detrimental impact of economic growth was confirmed in the study in terms of environmental sustainability, there is also evidence that this detrimental effect is expected to be neutralized by income expansion as seen by the significant negative impact of the income square coefficient in the CS-ARDL model. This result thus approves the EKC conjecture for the E7 countries within the incomesustainability framework when technological innovation is accounted for thereby lending credence to some evidence in support of the EKC validity in emerging economies (Baloch et al., 2021). In the results in

| CONCLUSION AND POLICY REFLECTION
The impacts of technological innovation and energy use on the environmental quality of the E7 economies have been explored in this study. While doing so, the interaction between the variables was also incorporated into the model to assess its influence among the E7 economies using data covering 1992-2018. The result confirmed the EKC conjecture and suggested that innovation cushions pollutant emissions in the E7 economies. Both energy consumption and economic growth were found to be an adversary to the sustainability of the environment in these emerging economies. Furthermore, while innovation cushions pollutant emissions among the countries, its desirable environmental impacts become unnoticeable when interacting with the level of energy consumption among these economies.
A major explanation for this development lies in the overwhelming share of conventional energy use in the overall energy portfolios of the E7 economies. As such, the gains from innovations can be said to be undermined in the E7. The causality results also provided some corroborative evidence for the estimates and these inform useful policy directives for the E7 economies and other emerging economies at large.

| Policy
Considering that the environmental-related technological innovation shows a mitigation impact on carbon emission, more responsibility is bestowed on the emerging economies to ensure technology and innovation-driven investments. Moreover, because environmentalrelated technological innovation has the potential of moderating the role of primary energy utilization on carbon emission, this further suggests that more intervention should be geared toward energyspecific technologies and innovations. By so doing, more desirable outcomes about the mitigation of carbon emissions could be attained over time, especially with the right attitude toward environmental responsibility.
In concrete terms, the authorities of the E7 nations can take advantage of diverse approaches to exploiting the environmental ben- and other ingenious establishments that are saddled with specific environmental targets. Furthermore, there is a need for the E7 nations to address their energy portfolios such that the proportion of conventional energy use in total primary energy consumption is reduced to the barest minimum. In this regard, the authorities of the E7 should be committed to providing adequate investment supports for innovative technologies, especially renewable energy technologies to rightly position the E7 economies on the expected environmental sustainability path.

| Limitations and the future research directions
The current study adopts novel approaches for the empirical analysis from the case of the E7 economies thus providing a solid foundation for more investigations to be conducted in other blocs. However, while the roles of energy use were aggregated in total primary energy consumption in the current study, future studies can extend the established framework to examine the roles of disaggregated energy use (individual energy types) within the innovation-environmental nexus analysis for the E7 countries or other blocs.

ACKNOWLEDGMENTS
Authors' gratitude is extended to Asst. Prof Dr Festus Bekun for an additional proofreading assistance.

AVAILABILITY OF DATA AND MATERIALS
The data for this present study are sourced from the database of the

CONFLICT OF INTEREST
I wish to disclose here that there are no potential conflicts of interest at any level of this study.