In the recent years the concerns for climate change and global warming are widely discussed in academia, policy circles and in business decision making. The overarching growth process led to the exploitation of forest cover and natural resources and subsequently causes a rise in carbon emissions and the ecological footprint (Danish, et al., 2019; Danish, and Khan 2020; Destek and Sinha, 2020).
A plethora of research consider major drivers like renewable energy, forest depletion, eco-innovations, export diversification, agricultural activities and economic growth among others to impact environmental welfare. Unarguably the United Nations deliberations on Sustainable Development Goals (SDGs) to be achieved by 2030, emphasizes on the need for clean and affordable energy for all, technological innovations and inclusive and sustainable growth, as ways to mitigate climate change problems and preserve the biodiversity and terrestrial eco-system on the basis of urgency. Thereby addressing Sustainable Development Goals − 7,8,9,13 and 15 (UNDP 2015)2.
To measure the indicators of environmental degradation researchers have used extensively the levels of carbon emissions (CO2) (Yilanci and Pata, 2020). However, the measure of CO2 emissions only assesses the levels of air pollution and ignores pollution of water and soil (Yilanci and Pata, 2020; Pata, 2021). Yet another strand of literature uses Ecological Footprint (EF) (Omri and Mabrouk, 2020; Akalin, 2021) as an indicator of environmental degradation. EF denotes the biologically used land area and water mass needed to create resources for the use of an individual or society (Nathaniel et al., 2021; Salman et al., 2022).
To streamline the unsustainable growth patterns specific policy instruments are imperative. During the COP26 summit the global leaders urged the nations to develop the production capability and enhance the domestic capacity through technological progression and structural transformation (UNFCCC 2022). Innovations to enhance the welfare of the environment is referred to as “ecological innovation” (Eco-Innovations). It is also sometimes discussed as ‘’green technology’’. Eco-Innovations are a particular form of innovations that attempts to reduce the adverse impacts of energy use and product expansion on the environment. It has recently attracted scholarly discussion in the literature (Danish and Ulucak 2020; Chien, et al.,2021; Lingyan et al., 2021; Melnykovych et al., 2018; Razzaq et al., 2021).
Besides, the objective of environment-friendly growth can be achieved through the advancement of technological sophistication and maximizing the use of renewable resources. A steady supply of energy is essential for sustainable development in the long run (Dincer, 2000). In accordance with the SDG-7, it is imperative for the nations to provide cheap, affordable and cleaner sources of energy. Against this milieu renewable energy (RE) is regarded as the important and chief source of energy for improvement of the quality of the environment (Destek and Sinha, 2020; Khan et al., 2022).
In the recently held 26th Annual United Nations Climate Change Conference (COP26) in Glasgow around 100 member nations pledged to halt deforestation and implement the process of afforestation by 2030. Among the countries Brazil, China and Russia were the major signatories. The leaders emphasize on the critical and interdependent functions of the forest cover for protection of biodiversity and urged the nations on the sustainable land use to attain the trajectory on Sustainable Development Goals (SDGs). The report further urges on large scale afforestation to move towards the SDGs goals particularly SDGs-15 on protection and restoration of terrestrial eco system and sustainable use of the eco system.
In addition, in the developing region agriculture accounts for major concerns in Sustainable development (Ullah et al., 2018, Pata., 2021). According to Pata (2021), it is essential for sustainable development to transform the food and agricultural system that takes into account the climate change problems and thereby meeting the 2030 goals. It is estimated that about 70 percent of water withdrawal globally is due to the agricultural activities (Ullah et al., 2018; Pata,.2021). It is the third largest contributor to environmental damage after energy and industrial production (Pata,.2021; Olanipekun et al., 2019; Alvarado et al., 2021).
A plethora of research has identified among others, economic growth, energy use, forest depletion, agricultural expansion and trade openness as major drivers for CO2 emissions (Pata, 2018; Ullah et al., 2018; Waheed et al., 2018; Pata,.2021). Nonetheless it is not until the turn of this century that scholarly discussion delved on the role of trade diversification in exacerbating the degradation of the environment (Ozokcu and Ozdemir, 2017; Rasli et al., 2018; Apergis et al., 2018; Liu et al., 2018; Mania, 2020).
Now to design new policy to accelerate Eco-Innovations alongside fostering the use of the RE and to arrest overexploitation of forest resources, and moderate Eco-Innovations implication on agriculture, to check the rise in EF, yet ensuring an all-inclusive economic growth, will require a sample set of observations to set the empirical example. To this end this study has chosen the BRICS-T economies.
1.1. Why BRICS-T countries?
The set of BRICS-T economies (Brazil, Russia, India, China, South Africa and Turkey) have maintained a steady rise in economic growth since the decade of the 1990s (Dogan, et al., 2020; Usman et al., 2021). They account for 43 per cent of the global population and occupy around 30 per cent of land area across the global landscape in 2017 (Danish et al., 2019; WDI, 2019). Further in accordance with the WDI (2019) estimates the share of the BRICS-T in global GDP is around 23 per cent and share of global trade is around 17 per cent. The production of agricultural output in China is around 656.9 billion in US dollars. While the figure in Brazil approaches about 100.9 billion US dollars. These group of countries account for 40 per cent of forest area. Additionally, they account for about 40 per cent of global greenhouse gas emissions in 2017 (Danish et al., 2019; WDI, 2019). Unarguably China, India, Brazil and Russia are the four of the five countries with high EF in the world (Daniel Balsalobre-Lorente et al., 2021). Given the above milieu we consider the BRICS-T as the most important sample for empirical investigations to create a benchmark on policy analysis on the major variables affecting the EF.
To develop a suitable policy framework for the BRICS-T to combat against the environmental crisis vis-à-vis the target variables it is essential to choose an appropriate methodology. Since the set of countries chosen for empirical investigations entails different levels of economic development, our study validates the role of ecological innovations, forest cover, agricultural production and other control variables by using the state of art methods on machine learning and econometrics. The panel-based regularized least square method and the panel correlated standard test alongside the Augmented Mean Group and non-parametric time varying panel model with fixed effects are consistent and show robust specification. They have the advantages in controlling cross-sectional dependence, country-related heterogeneity, omitted variable bias and non-additive related fixed effects.
The paper henceforth is designed as follows: Section 2 delves on the major findings in the literature. The subsequent section, explains the data sets and choice of variables. In section 4 we discuss the major empirical results. Section 5 concludes with major policy discussions
2 SDG-7 safeguards cheap and sustainable energy for all; SDG-8 ensures inclusive and sustainable economic growth; SDG-9 confirms on expanding industrialization and promote innovation and creation of resilient infrastructure and SDG-13 urges climate action to mitigate climate change problems. Further SDG-15 fosters bio-diversity loss and promotes sustainable management of forests.