The investigation into the association between carbon emissions, trade globalization, natural resources rents, economic growth, and financial development have been undertaken by several kinds of literature. Unfortunately, a consensus regarding the connection of trade globalization, natural resources rents, economic growth, and financial development on carbon emissions are yet to be reached due to the difference in methodology utilized, period of study, countries employed, and many more.

The increasing economic expansion in Uruguay is fueled by considerable use of energy and complimented by the rapid cross-border flow of goods and services via globalization. Along with these factors, the availability of natural resources provides Uruguay with leverage to stimulate economic expansion. With the surge in economic growth in Uruguay, the financial sector will also improve, over time.

Unfortunately, an energy-driven economy such as the Uruguay economy continues to have a negative environmental externality in the form of carbon emissions. Demand for energy in the industrial sector continues to increase as a result of globalization, and the current innovations in the energy sector were insufficient to minimize this level of emissions. Underdeveloped financial institutions offer finance for economic operations (low-cost borrowing to families and enterprises), which encourages energy demand while simultaneously degrading the environment (Kirikkaleli et al., 2022). A robust financial sector can help to improve environmental sustainability by allocating more resources towards clean energy and mobilizing the money needed to invest in environmentally friendly infrastructure and assure environmental sustainability (Batool et al., 2022).

Furthermore, it should be noted that Uruguay is rich in natural resources, and the country’s developmental rate may not be sustainable. As a result, the country may have to depend on its natural resource reserves to meet its energy needs. The majority of these natural resources contain the composition of molecular hydrocarbon, and when consumed, they oxidized, resulting in CO₂ emissions (Ma et al., 2019). As a result of the availability of natural resources and the growth, trajectory worsens environmental quality.

This study evaluates the impact of natural resources, economic growth, financial development, and trade globalization on carbon emission in Uruguay. This present study uses a dataset ranging from 1980 to 2018. However, the unavailability of data hampered the period of study and sample size. For this study, carbon emissions are the endogenous variable, and these variables: natural resources abundance, economic growth, financial development, and trade globalization are the exogenous variables. All the variables of the investigation are transformed into a natural log to reduce heteroscedasticity. However, the sources, metrics for the variable of concern are presented in Table 1.

The model for this study is constructed as follows: C O 2 = f ( G D P t ,   N R R t ,   T G L O t ,   F D t ,   ) (1) C O 2 =   β 0 + β 1 G D P t +   β 2 N R R t +   β 3 T G L O t   +     β 4 F D t   +   ε t (2) Where: CO₂, GDP, NRR, FD, TGLO, and ε denote carbon emissions, economic growth, natural resources, financial development, trade globalization, and the error term, t indicates the period of consideration (1980–2018).

The trade-off between GDP and the environment has been established in energy literature. Therefore, we anticipated that the coefficient between CO₂ emissions and GDP is positive, i.e., ( β 1 = δ C O 2 δ G D P > 0 ) . Resource extraction accelerates economic growth and degrades environmental quality. As a result, it is anticipated that natural resource abundance will have a negative impact on environmental quality. i.e., ( β 2 = δ C O 2 δ N R R > 0 ) . Trade globalization considers the participation of Uruguay in terms of foreign trade. When trade globalization has a high (low) value, it indicates that Uruguay’s participation in trade with other nations is at a higher (lower) degree. When β 3 has a positive sign. i.e., ( β 3 = δ C O 2 δ T G L O > 0 ) , it indicates that trade globalization is expected to develop pollution-intensive sectors, thereby degrading the environment in Uruguay. Conversely, having a negative sign for the coefficient of trade globalization. i.e., ( β 3 = δ C O 2 δ T G L O < 0 ) , suggests that globalization through the conduit of trade globalization is expected to improve the quality of the environment. However, certain research, such as Usman et al. (2022) conclude that financial development has a positive connection with CO₂ emissions. They argue that financial development encourages research & development as well as green energy initiatives thereby stimulating innovation and, as a result, contributes to the enhance the quality of the environment. .i.e., ( β 4 = δ C O 2 δ F D < 0 ) , Some research, however, such as Pata (2018), Batool et al. (2022), and Adebayo et al. (2021b), argue that financial development increases the deterioration of the environment. They asserted that the financial sector is usually financially motivated rather than environmental consciousness and that convenient availability of financial services stimulates the usage of the resource. As a result, financial development is expected to degrade the environment if it is not eco-friendly. i.e., ( β 4 = δ C O 2 δ F D > 0 ) .

Pesaran et al. (2001) developed the ARDL bounds testing approach to investigate long-run interconnectivity among variables having a mixed integration order I (1) or I (0) but not I (2). When utilizing this method, the dependent variable (i.e., CO₂) needs to be I (1) (Pesaran et al., 2001). The benefit of this approach are as follows: (1) it is suitable for small sample size (Kirikkaleli et al., 2021); (2) it accommodates a mixed order of integration during analysis (Kalmaz and Awosusi, 2022); (3) endogeneity issues are solved.

The previous unrestricted ECM is used to evaluate cointegration. Δ C O 2 t =   ω 0 + ∑ l = 1 p ω 1 Δ C O 2 t − 1 + ∑ i = 1 p ω 2 Δ G D P t − 1 +   ∑ i = 1 p ω 3 N R R t − 1 +   ∑ i = 1 p ω 4 Δ T G L O t − 1 + ∑ i = 1 p ω 5 Δ F D t − 1 + φ 1 C O 2 t − 1 + φ 2 G D P t − 1 +     φ 3 N R R t − 1 +   φ 4 T G L O t − 1 + φ 5 F D t − 1 +   ϵ t (3) Where: Δ , ω i   ( i = 1 , … .5 ) , an d φ i ( i = 1 … .5 ) indicate the difference operator, short and long term coefficients, ϵ denotes the error term and ω 0 indicates intercept. By including the ECM into the ARDL, Eq. 3 is transformed into Eq. 4: C O 2 t =   ω 0 + ∑ l = 1 p ω 1 Δ C O 2 t − 1   + ∑ i = 1 p ω 2 Δ G D P t − 1 +   ∑ i = 1 p ω 3 N R R t − 1 +   ∑ i = 1 p ω 4 Δ T G L O t − 1 + ∑ i = 1 p ω 5 Δ F D t − 1 + φ 1 C O 2 t − 1 + φ 2 G D P t − 1 +     φ 3 N R R t − 1 +   φ 4 T G L O t − 1 + φ 5 F D t − 1 + α E C T t − 1   +   ϵ t (4) Where: the degree of short-run modification to achieve long-term equilibrium and ECT symbolizes the error correction term. This coefficient’s predicted sign ( α ) is, as expected, significant and negative. The ARDL approach was used to investigate the dynamic connection between CO₂ emissions and its determinants after discovering the cointegration connection in Eq. 4.

However, when the coefficients of the interaction are disclosed, the direction of the interaction amongst parameters is unpredictable, i.e., the causal relationship between CO₂ and GDP or vice versa. But, such an analysis could not be pursued using non-linear analysis. As a result, the frequency domain causality technique was used in this work, which is an innovation of Breitung and Candelon (2006). The spectral BC causality technique is another name for this test. In comparison to a causality time-domain method that solely shows time series variability. For simplicity, it can identify causal interaction between two series at long, medium, and short term. This test uncovers the magnitude of frequency-domain assessment, which may be employed to discover nonlinearity and causal cycles at both high and low frequencies. One of the major strengths of this approach is the ability to uncover causal connections between sets at different frequencies. The approach is centered on the reconstructed Vector Autoregressive (VAR) interaction between x and y, which is written as: x t =   θ 1 x t − 1 + . … +   θ 1 x t − 1 + β 1 y t − 1 + … +   β l y t − 1 +   ε t (5) To select the optimal lag ( l ), the study used the Akaike Information Criterion (AIC). The null hypothesis is stated as: H 0 : R ( ω ) β = 0 (6) The vector that connects the y coefficients is denoted as   β : R ( ω ) =   cos ( ω ) cos ( 2 ω ) … . cos ( l ω ) sin ( ω ) sin ( 2 ω ) … . sin ( l ω ) (7) t = 2 π ω , which indicates t as period and is connected to the frequency ω .

The outcomes of this current study exhibit a positive relationship between trade globalization and carbon emissions. This research indicates that the policies towards trade globalization are anticipated to have a negative impact on Uruguay’s environment. It has become obvious that trade globalization is a major determinant that contributes to environmental degradation. This conclusion is reinforced by the notion that Uruguay is primarily reliant on fossil fuels, implying that the country maintains its competitive advantage in the manufacture of pollution-intensive commodities through the usage of fossil fuels. Thus, Uruguay’s determination to progressively integrate its economy could improve and encourages the growth of polluting industries, causing the country a net exporter of these goods, thereby contributing to the increase in carbon emissions in major sectors like the agricultural, manufacturing, and energy sectors. Our outcome aligns with the findings of Murshed et al. (2022) who conclude that trade globalization degrades the environment in Argentina. However, the study of Ahmed and Le (2021) established a contrary viewpoint by establishing that trade globalization mitigates CO₂ emissions in six selected ASEAN countries. As a result of the findings, a fresh debate regarding policy formation are been opened up based on the perspective of developing countries.

Additionally, natural resource policies serve as a critical bedrock for managing resources, usage, and conservation. This current research emphasized the impact of natural resources in terms of CO₂ emissions concerning the challenges of climate change in the country as well as the depletion of natural resources. As a result, we expect the insights of this study can serve as a baseline for developing regulations linked to natural resource and environmental management. The current study’s outcomes show that natural resources impede the quality of the environment in Uruguay, wherein CO₂ emission levels surge. This result is consistent with the previous remark that the revenue from the natural resource is primarily diverted towards further production pathways or exploitations of natural resources that could contribute to subsequent environmental degradation. This outcome agrees with Adebayo et al. (2022) whose investigation was focused on the dataset of newly industrialized countries and found that natural resources increase CO₂ emissions. Awosusi et al. (2022b) in Colombia, Caglar et al. (2022) in BRICS economies, and Liu et al. (2022) in G7 economies concluded that natural resources degrade the environment.

This current study discovered that a rise in Uruguay’s economic growth contributes to an increase in the country’s CO₂ emissions. It indicates that the trajectory in both the long and short term suggests that Uruguay tends to enjoy and accept more economic benefits at the expense of environmental quality. This finding is predictable considering that the most of developing economies, like Uruguay, are experiencing rapid economic growth in the last decade while also simultaneously increasing the overall CO_2e emissions levels. The excessive dependence on the utilization of fossil fuels to satisfy the requirement of the business and residential sectors raises CO₂ emissions. Under such circumstances, the implications of Uruguay’s undesirable environmental ramifications of economic development are validated. This current study’s results are consistent with those of Adebayo et al. (2021c), who discovered that GDP increases the CO₂ emission level in Japan. He et al. (2021) conducted research in the top ten energy transition economies and discovered that GDP has a positive impact on CO₂ emissions. Adebayo et al. (2021g), Adebayo and Rjoub (2021), and Akadiri and Adebayo (2021) discovered a positive connection between GDP and CO₂ emissions in South Korea, Argentina, and India, respectively.

Furthermore, we discovered that financial development does not impact environmental deterioration in Uruguay. Given that developing countries like Uruguay, have a financial sector, that is, still undeveloped, borrowed monies are intended to be invested in polluting industries without the threat of getting penalized under environmental protection regulations. Moreover, considering that the developing countries in the Latin American region depend heavily on the importation of fossil fuels, the additional financial resources are unlikely to necessitate the investment in environmentally friendly industrial operations. This current study’s results agree with those of Ayobamiji and Kalmaz, (2020), who detected that financial development has no significant impact on the level of CO₂ emission in Nigeria. Adebayo et al. (2021a)’s research in Argentina detected that financial development has no significant impact on CO₂ emissions. Also, the finding of Adebayo et al. (2021b) for Latin American nations indicates that financial development does not significantly influence CO₂ emission in these economies. However, this outcome contradicts the recent studies of Su et al. (2021), who detected a negative interconnection between financial development and CO₂ emissions in Brazil, and Batool et al. (2022) found a positive connection between financial development and CO₂ emissions in a selected developing nation in Southern and Eastern Asian region.

This current research probes into whether trade globalization affects carbon emissions. Moreover, we also ascertain the impact of economic growth, financial development, and natural resources on CO₂ emissions in Uruguay. The empirical assessment was conducted with bounds testing procedures, the ARDL approach, and the spectral causality test, which offers precise insights. Premised on our evaluation, the bounds testing procedures, as well as the critical values of Kripfganz and Schneider (2018), confirm that there is a cointegrating interaction between CO₂ emissions and these determinants (trade globalization, economic growth, financial development, and natural resources). Moreover, from the outcome of the ARDL approach, we observed that trade globalization, economic growth, natural resources contribute to CO₂ emissions in Uruguay. Furthermore, we uncover that financial development does not impact CO₂ emissions in Uruguay. The outcome of the spectral causality test detected that trade globalization, economic growth, and natural resources forecast CO₂ emissions with the exclusion of financial development. Taking into account the outcomes, the research made certain policy recommendations.

The following policy ramification is made based on the empirical outcome of this present study: the adverse effect of trade globalization on the environment suggests that policies should be tailored towards international trade must be reassessed, and the restrictions placed on the exportation of polluting-intensive commodities must be reinforced. Such an effort would restrain the growth of polluting industries while promoting the growth of comparatively cleaner sectors. As a result, carbon emissions from the agricultural, manufacturing, and industrial sectors can be greatly decreased.

Secondly, the empirical findings indicate that natural resources degrade the environment. Considering this finding, there is a need for the government to mitigate the overexploitation of natural resources, which can be achieved through tightening and strengthening the prevailing natural resource tax legislation. Furthermore, green tax guidelines that are both sustainable and environmentally beneficial should be implemented to encourage green investment.

Next, in light of the impact of economic growth on CO₂ emission, the government must align its present economic growth policies towards the green initiatives so that subsequent economic expansion in Uruguay does not undermine the quality of the environment. This emphasizes the need for Uruguay to experience a sustainable energy transition, in which the country’s energy demand is satisfied by generating energy through renewable energy sources.

The empirical outcome concludes that financial development does not impact CO₂ emissions. From this perspective, Uruguay should exert effort towards ensuring that the financial sector achieves the goal of a sustainable environment. As a consequence, initiatives to implement green financing techniques should be prioritized; thereby ensuring that the support for green investments initiatives is critical. Likewise, we proposed that the government of Uruguay should raise funds that support programs aimed at combating global warming; therefore, climate finance is essential to enhance the environmental outcomes associated with financial development.

Despite the study’s considerable contribution to environmental literature, particularly in Uruguay. Meanwhile, this present study has several drawbacks. These drawbacks stem from the study’s utilization of only a few parameters. Future research may incorporate more parameters and investigate their impact on various environmental metrics. Also, upcoming research should undertake this connection with the framework of the Environmental Kuznets curve or Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT). Given the unavailable datasets, it would be desirable to address these constraints in the future study. Upcoming studies can employ a non-linear approach to determine the effect of the studied variables.