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LITERATURE REVIEW
In this section, the theoretical foundations of the study - the Environmental Kuznets Curve (EKC) and
Renewable Energy Kuznets Curve (RKC) hypotheses - are discussed in depth within the framework of
empirical findings from the relevant literature. First, we focus on EKC-based studies examining the effects
of trade openness (TO) and non-renewable energy consumption (NREN) on the ecological footprint.
Second, we review literature on the more recent RKC hypothesis, which explores the relationships among
variables such as urbanization, TO, and REN. Finally, the interaction between these two hypotheses is
discussed, and the research gap addressed by the present study is identified.

Environmental Kuznets curve (EKC) hypothesis and its determinants
Many studies have been conducted on EKC over the last thirty years. They have related per capita income
with pollution variables such as CO , ecological footprint (EF), and carbon footprint [10,12] . It can be said that
2
the studies on EKC generally address four main issues. These can be summarized as income, financial
development, technological development, and environmental regulations [12,13] . However, most recently, the
Paris Climate Agreement, toward the implementation of environmental policies among countries, has
brought growth processes based on renewable energy sources to the fore. Renewable energy is a key
[13]
component linked to economic growth, social concerns, and environmental sustainability . Despite this
finding, the share of renewable energy in total energy consumption in the world is still around 10%,
[14]
although it varies from country to country . In recent years, more comprehensive variables such as the EF
have been included in the analysis as an environmental indicator. Research on the determinants of the
ecological footprint has focused particularly on the effects of variables such as TO and NREN.

The role of TO as a determinant presents contradictory findings in the literature. Some studies argue that
trade exacerbates environmental degradation. For instance, Adebayo et al. , in their analysis of MINT
[15]
(Mexico, Indonesia, Nigeria, Turkey) countries, found that TO positively affects the ecological footprint in
the short and medium term in Mexico and Indonesia, and across all terms in Turkey and Nigeria. Similarly,
[16]
Abdullahi et al. for the Economic Community of West African States (ECOWAS) countries, Zhou et al.
[17]
[18]
for Belt and Road Initiative (BRI) countries, Zahid et al. for BRICS countries, and Van Hek et al. for 10
[19]
Newly Industrialized Countries (NICs) concluded that international trade increases the EF. In contrast,
another group suggests that trade can improve environmental quality by facilitating the diffusion of cleaner
technologies. Alqaralleh states that a positive TO shock reduces environmental degradation in ASEAN
[20]
[22]
[21]
countries, while Dam et al. for E7 countries and Cutcu et al. for the USA have provided evidence that
international trade reduces the EF in the long run. Gao et al. state that the EKC is not merely an empirical
[23]
[24]
phenomenon but can be shaped by policy objectives. For example, Cao et al. , in their study on China's
minority regions, propose a policy of "flattening the EKC" through industrial and green technological
innovation to achieve sustainable development goals. Green finance also plays a critical role in this
[25]
transformation. Indeed, Zhang et al. empirically demonstrate that China's Pilot Zone for Green Finance
(PZGFRI) policy has significantly increased green innovation through capital and research and
development (R&D) support. This demonstrates that targeted financial policies can accelerate
environmental improvement by triggering technological innovation.
In addition to TO, another significant determinant of the ecological footprint is NREN. One of the most
important sub-components of the ecological footprint is the carbon footprint, and its primary source is
non-renewable energy. Therefore, there is a strong consensus in the literature that NREN increases the EF.
In a study specific to India, Roy analyzed the 1990-2016 period using the Autoregressive Distributed Lag
[26]
(ARDL) technique and found that NREN has a positive long-run effect on the EF. This finding is supported
[27]
by studies on other countries and regions. Adekoya et al. showed that NREN increases the EF in both 14