This study aims to investigate the impact of entrepreneurship and green investments on environmental sustainability within the scope of Sustainable Development Goals for developed economies. The study conducts an in-depth analysis from 2001 to 2022 and reveals the possible effects of increases and decreases in entrepreneurship. Based on the results of the empirical analysis, an asymmetric relationship between entrepreneurship and environmental sustainability has been determined in the short and long run. Although decreases in entrepreneurial activities cause a reduction in environmental quality, increases in entrepreneurial activities contribute to environmental sustainability. Increases in green investments provide improvements in environmental quality. These results show that entrepreneurial activities and green investments significantly impact environmental sustainability in developed economies. Based on these results, this study recommends that policymakers in developed countries incentivize green investments, foster the growth of sustainable entrepreneurial ventures, and implement policies that assess and enhance the environmental sustainability of entrepreneurial activities.

1 Introduction

In recent decades, environmental protection and green development have become important goals of developed economies. This is because the development of economies has augmented societies' sensitivity toward environmental protection. In addition, the instances of environment-related catastrophes have substantially increased, and floods, droughts, heatwaves, and cyclones have become common. Economic growth, mainly when driven by fossil fuel-dependent industries, significantly contributes to increased greenhouse gas emissions and, consequently, climate change. Accordingly, global carbon emissions (CEs) have recorded a substantial growth of over 50% from the inception of the Industrial Revolution due to increased energy consumption (IEA 2021). Given the relevance of energy patterns in environmental sustainability, the COP26 agenda to control global warming by restricting it below 2°C and even mounting efforts toward achieving 1.5°C for attaining carbon neutrality (United Nations 2021) will require a massive surge in investments related to green energy.

Economies mostly use fossil energy to achieve economic growth. In this context, the International Renewable Energy Agency (2023) points out that currently, the global capacity to produce renewable energy is insufficient to restrict global warming to the desired levels; thus, the capacity to produce renewables will need to be increased by around threefold by 2030 to reach the objective of 1.5°C. This will require a massive surge in green energy innovation by uplifting investments in renewable energy research and development (R&D). Lee and Min (2015) acknowledge that green investments can stimulate the generation of renewables, boosting their availability and, thereby, augmenting sustainable growth. This makes sense since alternative energy sources, including hydro, geothermal, solar, wind, and bioenergy, are considered to be green with a favorable effect on the sustainability of the environment (Ahmed et al. 2022).

Sustainable Development Goal (SDG) 7, which highlights the concept of “reliable, affordable, and sustainable energy for everyone,” points out the criticality of focusing on three fronts, that is, reliability, affordability, and sustainability. Unless sustainable energy is affordable, it may not be economically viable for the economies to achieve energy transition. Thus, the markets for green energy must be properly developed to support the energy transition. In this regard, Ardito et al. (2019) postulate that green investments in the public sector can even influence the development of green technologies in the private sector, improving the market of cleaner technologies. Likewise, Becker (2015) identifies connections between private and public sector R&D. Thus, public sector green investments in renewable R&D can aid economies in achieving energy transition. According to Koçak and Ulucak (2019), green investments related to renewables are the essential input to the green energy innovation that supports ecological sustainability. Augmenting green innovation can lead to a surge in green growth by stimulating energy conservation and promoting green energy consumption, which in turn can increase environmental sustainability (Wang et al. 2023). The increase in innovation due to a surge in green investments can decrease fuel wastage, production costs, and equipment losses (Sharif et al. 2024).

Entrepreneurship (ENT) is the process of initiating and managing a business and is a vital force that promotes economic development (Stel et al. 2005). In recent literature, scholars have discussed ENT's role in mitigating climate change (Omri 2018). ENT helps attain socio-economic growth (Urbano and Aparicio 2016) and ecological sustainability (York and Venkataraman 2010). Past literature has divided ENT into many different types, such as imitative ENT, innovative ENT, collective ENT, individual ENT, and private ENT, with different impacts on economic progress and sustainability (Omri and Afi 2020). Scholars have presented two views on the environmental impacts of ENT. The first view postulates that ENT brings innovation to the economic initiatives that support economic growth, economic productivity, and environmental sustainability (Galindo-Martín et al. 2021; Khezri et al. 2024; Pradhan et al. 2020). The innovation in economic activities can promote energy savings, reduce waste, and augment resource conservation, promoting environmental sustainability. In this regard, York and Venkataraman (2010) suggest that entrepreneurial initiatives represent a solution to ecological problems. Patzelt and Shepherd (2011) argue that ENT supports agricultural activities, lessens deforestation and pollution, and decreases climate change. Conversely, studies have also suggested that ENT activities degrade the environment by augmenting economic growth and modernization (Dhahri and Omri 2018; Omri and Afi 2020; Riti et al. 2015). This is because the increase in growth on account of ENT and escalation in resource consumption will upsurge nations' ecological footprints (EFs), increasing the environmental burden. Overall, studies have linked ENT with environmental sustainability with different points of view and inconsistent findings.

Given this background, this study aims to analyze the effects of green investments and asymmetric effects of ENT on environmental sustainability in selected developed nations. Considering that past literature employs various proxies to represent environmental quality, such as CE, carbon footprint, EF, and others with certain limitations, this study adopted the load capacity factor (LCF) because it accurately assesses environmental sustainability by comparing the demand and supply of resources. As argued before, there is a close connection between ecological unsustainability and development. Therefore, selecting a sample of developed nations for this analysis makes sense. This is because development involves massive consumption of fossil fuels, minerals, and natural resources, which can exacerbate environmental degradation and resource depletion. Apart from this, transportation and industrial activities related to development can produce air, soil, and water contamination, degrading human health and ecosystems. Development can also stimulate habitat destruction due to potential deforestation for urbanization or agricultural activities. The 13 developed nations based on the data availability for ENT and green investments are selected for the study, including the United States, Germany, Spain, Italy, Canada, the Netherlands, the United Kingdom, Japan, Sweden, Switzerland, Norway, France, and South Korea. Figure 1 illustrates that only Sweden, Norway, and Canada exhibited LCF values exceeding 1. Conversely, all other nations displayed LCF values below 1 in 2022 (GFN 2023), indicating a higher resource utilization rate and a lower biocapacity. This suggests that a majority of the sampled nations confront challenges associated with environmental unsustainability, as they currently consume more resources than their respective territories can sustainably provide. Among the sampled nations, the United States, Japan, Germany, South Korea, Canada, the United Kingdom, and Italy are major carbon emitters (STATISTA 2022). Consequently, most of the selected economies grapple with significant ecological challenges alongside high levels of development. Notably, these economies encompass nations with advanced technologies and a burgeoning entrepreneurial landscape. Recognizing the urgency of addressing ecological degradation, these economies actively seek to increase green investments. Therefore, this study analyzes the effects of green investments and ENT on ecological sustainability to facilitate better sustainable development policies. Assessing the nexus between ENT, green investment, and the LCF will contribute to the development of policies that support the achievement of SDGs 13 (Climate Action) and 7 (Affordable and Clean Energy). SDG 13 emphasizes the urgent need to combat climate change, and understanding the interrelationship between ENT, green investment, and LCF will provide valuable insights for policymakers on how to adjust these variables to enhance environmental sustainability and mitigate climate change. Furthermore, green technology investments in energy directly impact the availability of affordable and clean energy, a key objective of SDG 7, which aims to ensure universal access to modern, affordable, and reliable energy services.

Details are in the caption following the image — **FIGURE 1**
Open in figure viewer PowerPoint

LCF situation in sample countries in 2022.

Notably, previous research studies assess the symmetric effects of ENT on the environment, assuming that positive and negative shocks in ENT will affect the environment with equal elasticity, significance, and magnitude. Moreover, these studies also assume that both shocks will influence the environment in different directions, that is, if the positive shock increases sustainability, the negative shock decreases it, and vice versa. However, macroeconomic variables often pose asymmetric impacts due to changes in business cycles, fluctuations in supply and demand, changes in fiscal and monetary policies, and others (Ahmed et al. 2021). Thus, the positive and negative shocks to ENT may pose effects of different elasticity, significance, and magnitude. Therefore, the use of a symmetric method may not reveal the correct associations between ENT and ecological sustainability. Given the diverse environmental effects of ENT documented in prior research, it will be interesting to unveil whether ENT increases or decreases the LCF. Second, it will be interesting to understand how positive and negative changes in ENT impact the LCF. In addition, the study will also unfold how green investments affect the LCF.

Considering this background, this research makes the following contribution to the literature. First, this study represents a novel endeavor to investigate the asymmetric impacts of ENT on ecological sustainability. Specifically, it will examine how positive and negative shocks to entrepreneurial activity affect the LCF. This research departs from previous studies, which primarily focused on the symmetric impacts of ENT on various environmental indicators. Second, this study investigates the impacts of green investments on the LCF within the context of developed nations, a facet largely overlooked in previous research. Given the pivotal role of green investments in driving energy transitions, mitigating global warming, and addressing climate change, evaluating their impact on sustainability is crucial for the development of effective environmental policies. Third, this study adopts a novel asymmetric Augmented Autoregressive Distributed Lag (CS-ARDL) test by incorporating positive and negative shocks into the standard CS-ARDL framework. This methodological innovation allows us to accurately assess the asymmetric effects of ENT and the long-run impacts of green investments on the LCF while simultaneously addressing endogeneity, cross-sectional dependence (CSD), and heterogeneity. Notably, the traditional asymmetric ARDL approach, frequently employed in prior research, often fails to account for CSD and heterogeneity, common challenges in panel data analysis. Consequently, this study provides more reliable findings than previous investigations within the ENT–environmental sustainability nexus. Furthermore, the study utilizes the LCF indicator, recognized as one of the most comprehensive measures of environmental sustainability, to analyze the intricate relationship between ENT and ecological sustainability. By providing reliable insights into the effect of green investments and positive and negative shocks in ENT on the LCF, this study will give authorities a deeper understanding of the actual relationship between these variables and environmental sustainability. This knowledge will facilitate the design of more effective policies to incentivize green investments and enhance ecological sustainability. Furthermore, understanding the asymmetric relationship between ENT and the LCF will empower authorities to assess the sustainability of entrepreneurial activities and implement policies that promote environmentally responsible entrepreneurial growth.

This study will proceed as follows: Section 2 indicates a review of the literature, Section 3 develops the model of the research and discusses methods, Section 4 explains and discusses the results, and the final section (Section 5) presents the concluding remarks and policy directions.

2 Literature Review

2.1 Theoretical Literature

Green investments are considered a strong determinant of environmental sustainability (Bakry et al. 2023). Green investments can encourage CE reductions and climate change resiliency (Uche et al. 2024). Green investments transcend all financial initiatives that amplify environmental progress and carbon reductions and support climate change resilience (He et al. 2023). Besides, Bakry et al. (2023) emphasized that green investments include financial support for climate sensitivity and adaptation projects. They highlight four pathways through which green investments influence environmental sustainability. These pathways include technological efficiency, resource allocation, capital support, and green economic perspectives. It is envisaged that these investments are catalysts for green transition, carbon neutrality, and overall environmental progress.

On the other hand, the environmentally relevant market failure theory attributable to Dean and McMullen (2007) could explain the ENT–environmental sustainability nexus. Notably, the environmentally pertinent market failure theorization emphasizes channels of opportunities for entrepreneurs to achieve their profitability targets while simultaneously imbibing environmental quality soothing behaviors (Dean and McMullen 2007). The theory explains that entrepreneurs could seize the opportunities inherent in market failures yet avoid environmentally harmful actions. This conceptualization necessitates the sustainable or environmental ENT ideology. Notwithstanding the theorizations, environmental economics researchers have not extensively explored the contributions of these factors to environmental progress. Meanwhile, the empirical sub-section provides a thematic exposition of extant studies for more insights.

The load capacity curve (LCC) hypothesis extended by Dogan and Pata (2022) is fundamental to understanding the interactions between economic activities and ecological performance. Notably, LCC emphasizes possible short-run detrimental effects of economic activities and their long-term favorable implications on environmental sustainability. According to Narayan and Narayan (2010), it can be determined whether the environmental Kuznets curve (EKC) hypothesis is valid by looking at the short-term and long-term coefficients of income. If the long-term coefficient of income is smaller than the short-term coefficient of income, the EKC hypothesis is valid. In other words, environmental pollution decreases as the country's income increases. When this theory is adapted to the LCC hypothesis, if the decrease in environmental quality is lower in the long run than in the short run, the LCC hypothesis is valid. The hypothesis denotes a possible U-shaped relationship between economic growth and ecological performance (Figure 2). The LCC hypothesis suggests a dynamic trade-off relationship between ecological sustainability and economic progress (Caglar et al. 2024a). It portrays a possible U-shaped relationship permissible when an economy prioritizes ecological sustainability by investing its income in green energies and environmental quality-enhancing ENT. Hinging on the above discussions, the following hypothesis is established accordingly:

Hypothesis 1.The LCC hypothesis is valid in the context of the 13 developed economies.

2.2 Empirical Literature

2.2.1 Green Investments–Environmental Sustainability Nexus

Insights from extant studies suggest the need for more empirical inputs to streamline the understanding of the intricate relationship between green investments and environmental sustainability. This position is premised on the countervailing submissions of prior studies regarding this relationship. For instance, Ren et al. (2020) examined the implications of green investments on carbon intensity in China between 2000 and 2018. The empirical discovery of the study highlights the pivotal role of green investments in carbon intensity reductions. Lee and Lee (2022) proffered a similar narrative, suggesting the appealing effects of green finance on green total factor productivity in China. Likewise, Khan et al. (2022) emphasized that green financing reduced the EF significantly in 26 Asian economies. The CE and environmental pollution inhibitory efficacy of green investments are further extolled in other studies, including Sinha et al. (2021), Hu and Zheng (2022), and Yao et al. (2022). Notably, Al Mamun et al. (2022) emphasized regional heterogeneities per green investments–CE reductions. Likewise, Fang et al. (2022), Madaleno et al. (2022), and Wang and Ma (2022) also reported heterogeneous effects of green investments, particularly in G7, the global sample, and China, respectively. These studies underscore the need to explore the perspective of other leading economies, highlighting current issues to guide policy adjustments. Besides, the prominent emphasis on CE represents a significant drawback of most prior studies since they neglected the LCF with broader implications.

There are more overwhelming inferences supporting the environmental quality-enabling effects of green investment. In this perspective, recent studies include Bakry et al. (2023) in the case of developing countries and He et al. (2023) in the context of BRICS economies. Likewise, Lee et al. (2023) exposed that green investments elevated environmental performance in China. However, Xu et al. (2023) reported heterogeneous implications of green investment in the environmental performance of Chinese Provinces. Irrespective of these overwhelming supportive submissions, Singh et al. (2023) explained that green investment remained ineffective for CE reductions in the context of G7 and G20 countries. This submission and the analogous inputs of Wang et al. (2023) in the context of China puts policy adjustment in a state of quagmire since they conflict with previous or popular understanding. Hence, more inputs within the broader perspective of other prominent global economies are expedient for policy harmonization. A streamlined empirical re-assessment is fundamental for a clearer understanding of the implications of green investments on environmental quality, mainly in advanced economies, given their position in the global economic landscape. Given the highlighted polarized inferences of extant literature, the following hypothesis is provided herewith:

Hypothesis 2.Green investments are sufficient to increase environmental quality in the 13 advanced economies.

2.2.2 Entrepreneurship–Environmental Sustainability Nexus

Scartozzi et al. (2024) explored 172 journal articles via bibliometric and systematic literature procedures to provide empirical clarification for the ENT–environmental sustainability nexus. Accordingly, they explained that extant studies focused more on ENT's social and economic implications while neglecting the environmental repercussions. In summary, they emphasized the need for more empirical investigation of the environmental concerns of entrepreneurial activities. Furthermore, Cohen and Winn (2007) explained the environmental sustainability–ENT relationship as a zero-sum game that rewards only the entrepreneur. On their part, York and Venkataraman (2010) explained that ENT contributes positively to environmental sustainability through their participation and investments in corporate social responsibilities. Shepherd and Patzelt (2011) extended supportive inferences by highlighting that ENT contributes to biodiversity conservation, counteracts climate change, and enhances ecological sustainability. Likewise, Sun et al. (2020) and Udemba et al. (2022) highlighted the environmental quality-enhancing effects of ENT in 35 sub-Saharan African (SSA) countries and Malaysia, respectively.

However, several studies, including Dhahri and Omri (2018) and Youssef et al. (2018), provided countervailing inferences by highlighting the environmental quality-dampening implications of entrepreneurial activities in 12 developing economies and 17 African countries, respectively. Similarly, Alvarado et al. (2022) and Philip et al. (2021) remarked that ENT contributed to environmental pollution in 95 countries and Turkey in both the long and short terms. Likewise, Omri and Afi (2020) provided similar inferences in the case of 32 developing countries. Similar inferences were al extended by Omri (2018) in 69 countries. The study noted that ENT contributed substantially to environmental challenges in developing countries, with lower effects in developed economies. The above inferences underscore the need for harmonized empirical articulation about the relationship between ENT and environmental performance. The prominent conflicting narratives could mar policy adjustments toward pushing the frontiers of SDG 13. Hence, the perspectives of 13 advanced economies that highlight the implications of the partial effects of ENT suffice herein.

Most recent studies have also provided countervailing narratives regarding the relationship between ENT and environmental sustainability. Accordingly, Chen et al. (2024) suggest that ENT contributes significantly to CE reductions in the East Asian economies, particularly in the long term. Analogous inferences were extended by Elmonshid and Sayed (2024) for Saudi Arabia, Hussain et al. (2024), and He and Zhou (2024) for China. These studies support that countries can rely on entrepreneurial activities to eliminate environmental pollution and ecological damage. However, they selected greenhouse gas emissions as a standalone proxy of environmental sustainability. Their inferences may be biased given that CE does not consider both sides (demand and supply) of environmental performance. Other studies, including Jha and Pande (2024), Raimi (2024), and Udemba et al. (2024), confirmed the environmental quality-enhancing effects of ENT in China and the BRICS economies. Conversely, Khezri et al. (2024) explained that various forms of ENT contributed profoundly to CEs in 14 selected economies.

Beyond the fact that prior studies did not test the implications of ENT within the LCF framework, this study also introduced the novel asymmetric CS-ARDL estimator. Accordingly, the asymmetric effects of the partial changes of increasing and decreasing ENT on environmental quality were ascertained. Such peculiar information is nonexistent in existing studies, thereby enhancing the novel contributions of the present study. Prior evaluations have not identified the possible asymmetric implications of positive and negative ENT on environmental quality in the 13 advanced economies. Given this empirical lacuna, the current study remains fundamental to identifying how these opposing changes influence environmental health in these leading global economies. These novel insights are expected to shape policy formulations and implementations regarding ecological sustainability in advanced economies, with possible spillover effects to other global economies.

When random shocks (positive ways: improvement in investment environment, increase in productivity, increase in economic growth, decrease in inflation; negative ways: financial crisis, pandemic, war) occur in the economy, the assumption that all entrepreneurs will behave similarly may not always be valid (Krishnan et al. 2022; Castellanza and Woywode 2024). In other words, when a random shock occurs in the economy, some entrepreneurs continue their activities and can resist the shocks. Entrepreneurs with solid infrastructure are significantly unaffected by random shocks and want to continue in the economy (Provasnek et al. 2017; Santos et al. 2017). On the other hand, entrepreneurs may suspend their activities for a certain period and decrease their outputs in the face of a random shock. As a result, evaluating ENT in a single way may lead to the production of biased policies. This study investigates this situation by dividing ENT into positive and negative shocks. In this context, the following hypothesis will be examined:

Hypothesis 3.There is an asymmetric relationship between ENT and environmental quality.

Before entering the economic cycle, some entrepreneurs build their entrepreneurial activities on environmental sensitivity. They put environmental regulations in the workflow's first stage and focus on environmental sensitivities carried out together with profit (Muñoz and Cohen 2018). Since these entrepreneurs integrate the environment into the first stage of the business, they do not engage in activities that destroy nature (He et al. 2020). Environmental quality may also increase for enterprises in this situation if entrepreneurial activities increase. In this context, the following hypothesis will be investigated:

Hypothesis 4.Positive shocks from entrepreneurship increase environmental quality.

On the other hand, random shocks can disrupt entrepreneurial activities. In other words, entrepreneurial activities may decrease because of a shock (economic crisis, pandemic, war) (Krishnan et al. 2022; Santos et al. 2017). Entrepreneurs who are financially problematic, do not have a solid infrastructure, and do not follow innovations may suspend their activities or choose to reduce them in the face of a crisis. Environmental awareness may also decrease because of the decrease in entrepreneurial activities. In this case, environmental quality may decline. In this context, this study will investigate the following hypothesis:

Hypothesis 5.Negative shocks from entrepreneurship decrease environmental quality.

3 Data, Model, and Econometric Strategy

3.1 Model

This paper aims to probe the role of possible asymmetric effects of entrepreneurial activities on environmental quality. To achieve this goal, we first include the LCF, an indicator of environmental sustainability, as a dependent variable in the model. Then, we add income, an essential determinant of environmental quality, and globalization to the model to eliminate the omitted variable bias. The effect of green investments on environmental sustainability has been shown in many studies, and Ganda (2018) states that it has an essential place in ecological sustainability research. Our last variable in the model indicates ENT. Entrepreneurial activities are increasing rapidly in the changing, transforming, and technological world. The increase in these activities also brings environmental concerns. Although ENT is considered linearly in many studies, no study simultaneously addresses the effects of increases and decreases. Therefore, ENT is analyzed using a nonlinear method in this study. In this context, the following model is first obtained:

{LCF}_{it} = φ_{0} + φ_{1} {EGP}_{it} + φ_{2} {GIN}_{it} + φ_{3} {ENT}_{it} + φ_{3} {GLO}_{it} + ε_{it}

(1)

3.2 Data

Table 1 shows the variables' definition, measurement, and data sources in Equation (1). Five different data sources were used in the analysis. Before proceeding to the empirical analysis, the natural logarithm of all variables was taken. The study collected yearly data from 2001 to 2022 for developed countries for which green investments and ENT data were available. The ENT variable determines the start year of the data set, whereas the LCF variable defines the end year. Hence, countries selected for the analysis include the United States, Germany, Spain, Italy, Canada, the Netherlands, the United Kingdom, Japan, Sweden, Switzerland, Norway, France, and South Korea.

TABLE 1. Definition of variables.

Variable	Sign	Measurement	Source
Load capacity factor	LCF	Biocapacity/ecological footprint, per capita	GFN (2024)
Entrepreneurship	ENT	Established business ownership rate	GEM (2024)
Economic growth	EGP	GDP per capita (constant 2015 US$)	WDI (2024)
Green Investments	GIN	Renewable energy research and development investment, USD (Constant, 2023)	IEA (2024)
Globalization	GLO	Index	Dreher (2006)

3.3 Econometric Strategy

Equation (1) shows the basic model of our study, and our main goal was to include ENT in the model by separating it into its cumulative positive and negative shocks. To achieve this goal, we follow Shin et al. (2014) and decompose the ENT variable as follows:

{ENT}_{i}^{+} = \sum_{k = 1}^{t} ∆ {ENT}_{ik}^{+} = \sum_{k = 1}^{t} \max (∆ {ENT}_{ik}^{+}, 0)

(2)

{ENT}_{i}^{-} = \sum_{k = 1}^{t} ∆ {ENT}_{ik}^{-} = \sum_{k = 1}^{t} \min (∆ {ENT}_{ik}^{-}, 0)

(3)

Now, we modify the CS-ARL model developed by Chudik and Pesaran (2015) to include cumulative positive and negative shocks in the base model:

\begin{matrix} ∆ \ln {LCF}_{it} = δ_{it} + γ_{1 i} \ln {LCF}_{i, t - 1} + γ_{2 i} \ln {EGP}_{i, t - 1} + γ_{3 i} {GIN}_{i, t - 1} + γ_{4 i} \ln {GLO}_{i, t - 1} \\ + γ_{5 i}^{+} \ln {ENT}_{i, t - 1}^{+} + γ_{6 i}^{-} {lnENT}_{i, t - 1}^{-} + \sum_{s = 1}^{m} α_{is} ∆ \ln {LCF}_{i, t - s} + \sum_{s = 0}^{u} β_{is} ∆ \ln {EGP}_{i, t - s} \\ + \sum_{s = 0}^{h} π_{is} ∆ {GIN}_{i, t - s} + \sum_{s = 0}^{e} ϑ_{is} ∆ \ln {GLO}_{i, t - s} + \sum_{s = 0}^{t} (φ_{is}^{+} ∆ {lnENT}_{i, t - s}^{+} + φ_{is}^{-} ∆ \ln {ENT}_{i, t - s}^{-}) + e_{it} \end{matrix}

(4)

where

δ_{it}

and

e_{it}

indicate constant and error terms;

γ_{1} = \dots = γ_{6}

point out long-run coefficients;

α, β, π, ϑ, φ^{+}, φ^{-}

terms show short-run regression coefficients, and finally,

∆

represents a lag operator. The estimated model is shown in Equation (4). Some preliminary tests must be completed before estimating this model. The first is whether a random shock occurring in one of the variables will spread to other countries. Countries can affect each other in a globalizing world. This situation is investigated with CSD in econometric studies. To investigate CSD, this study uses Pesaran (2004, CD) and Breusch and Pagan (1980, BP-LM) techniques. Second, whether the regression coefficients in Equation (4) change from unit to unit should be investigated. This situation is called slope heterogeneity and is investigated using the Pesaran and Yamagata (2008) approach in this study. Third, unit root properties show whether the variables are resistant to shocks. As mentioned above, countries affect each other, and the CSD occurs in most variables. Therefore, this study reveals the unit root properties of the variables with the CADF (Pesaran 2007) technique that takes CSD into account. Then, it is vital for regression estimation that the variables move together in the long term. The Westerlund (2007, ECM) approach that considers CSD is followed in this cointegration process. The CS-ARDL estimate is obtained in the next stage, and an asymmetry between LCF and ENT is investigated. There are several important reasons for using the CS-ARDL technique in this study. First, it considers the slope heterogeneity and CSD. Second, it provides long-term and short-term estimates. Third, it provides evidence on how long it will take to correct the imbalances in the model by operating the error correction mechanism. Finally, it allows the short-term parameters to be heterogeneous while the long-term parameters to be homogeneous. In other words, although 13 developed economies apply different policies in the short term, they will apply common policies for environmental sustainability in the long term. The difference in the short-term and long-term parameters of the CS-ARDL technique makes it an appropriate estimator for the common goals of the panel. For this, the

H_{0} : γ^{+} = γ^{-}

(for long-run) and

H_{0} : φ^{+} = φ^{-}

(for short-run) hypotheses are investigated with the help of the Wald test, and these hypotheses must be rejected (one and two or one of them) for the asymmetry to exist. The robustness of our long-term estimates is investigated with asymmetric fully modified ordinary least square (FMOLS) and canonical correlation regression (CCR) estimators. FMOLS runs a semiparametric technique to prevent regression issues reasoned by the long-run relationship between cointegrated equations and random shocks. Therefore, the FMOLS has a great advantage because it corrects endogeneity bias and autocorrelation. The CCR estimator eliminates endogeneity by transforming the data and thus compensates for asymptotic deviations. As a result, the FMOLS and CCR estimators can also eliminate problems arising from autocorrelation, endogeneity, and variables not included in the model (Phillips and Hansen 1990; Park 1992). Then, comments, discussions, and policy implications can be made by obtaining the coefficients.

4 Data Analysis and Discussions

The novel asymmetric CS-ARDL panel econometric procedure answered three critical research questions based on in-depth empirical analysis. These identified research questions (earlier stated) had eluded policymakers, given that prior studies failed to provide any empirical answers to these burning issues. Consistent with standard econometric protocols, several pre-estimation procedures were incorporated, including the CSD test, slope homogeneity, panel unit-root test, and panel cointegration test (Table 2).

TABLE 2. Preliminary analysis findings.

Panel A: Cross-section dependence

LCF

EGP

GIN

ENT

GLO

15.590

[0.000]

28.653

[0.000]

26.676

[0.000]

8.668

[0.000]

38.534

[0.000]

BP-LM

650.994

[0.000]

1154.496

[0.000]

760.237

[0.000]

228.752

[0.000]

1486.838

[0.000]

Panel B: Slope homogeneity
Tests	Stats.	p-value
Delta	7.118	0.000
Adj.	8.718	0.000

Panel C: Unit root
Variables	CADF
	At level		First differences
	Stat.	p-value	Stat.	p-value
LCF	−1.936	0.268	−3.807*	0.000
EGP	−1.689	0.618	−2.379**	0.012
GIN	−2.689*	0.000	—	—
ENT	−2.482*	0.004	—	—
GLO	−2.098	0.111	−3.470*	0.000

Note: [] denotes p-values.
* and ** refer to 1% and 5% at significance levels.

The outcome of the CD and the slope homogeneity tests eminently informs the rejection of the null hypothesis of cross-sectional independence and nonheterogeneous slopes. These highlight the chances of cross-sectional error overlap among the selected countries. Likewise, the outcome of the panel unit-root test underscores the mutual integration of the panel series between order-zero [I(0)] and order-one [I(1)]. Notably, the series of green investments and ENT are naturally stationary, whereas others became stationary after differencing once. It is also pertinent to highlight the capacity of the selected econometric technique to harmonize both the long- and short-term interactions of mix-integrated series.

4.1 Panel Cointegration Analysis

The panel series were subjected to long-term coevolution tests via the Westerlund panel cointegration technique (Table 3, Panel A). The outcome of the summarized cointegration test prominently underscores the rejection of the null hypothesis of no long-run cointegration among the panel variables. Therefore, it is concluded that the enlisted panel series trend along in the long term and are cointegrated.

TABLE 3. Cointegration and asymmetry results.

Panel A: Cointegration findings
	Gt	Ga	Pt	Pa
Value	−3.694	−3.912	−12.442	−4.119
z-value	2.660	6.007	2.407	4.621
p-value	0.004	0.999	0.008	0.999

Panel B: Long- and short-run asymmetry findings
Short-run asymmetry
Wald F-test	p-value	Is there asymmetry?
76.61	0.000	+
Long-run asymmetry
Wald F-test	p-value	Is there asymmetry?
143.72	0.000	+

Note: Bold values indicate cointegration.

4.2 Marginal Effects Analysis

The outcomes of the marginal effects test are summarized in Table 4. The empirical analysis exposes that economic growth consistently and substantially dampened environmental quality in the short and long term. Since the decrease in environmental quality is higher in the long run than in the short run, the LCC hypothesis (first hypothesis) is invalid. In other words, the improvement in EGP does not support the development of environmental sustainability in the 13 advanced economies. This discovery which is at variance with the submissions of Dogan and Pata (2022) in the context of G7 countries, connotes a tradeoff between economic/income expansion and environmental progress. Conversely, this discovery is consistent with that of Caglar et al. (2024b), who disproved the validity of the LCC in European countries. The outcome typifies consistent negligence to environmental sustainability in preference to economic growth, negating a critical component of SDGs that canvasses growth processes that prioritize sustainability. As highlighted in several investigations (Lin et al. 2023; Sharif et al. 2024), most economies neglect environmental progress for economic gains, which remains inimical to sustainable development. However, this trend is reversible, and environmental sustainability is achievable despite economic growth. The critical step is to reinvest substantial portions of growth proceeds into projects with environmental quality-improving potentials. It could be most profitable to channel more growth proceeds to green investments since they possess environmental quality-improving attributes. Likewise, these countries are encouraged to invest more significant national income in green energy sources rather than traditional ones, facilitating environmental pollution. Investments into and the consumption of these nontraditional energies will enhance the quality of their environments and ensure the speedy realization of SDGs 7 and 13.

TABLE 4. Findings of CS-ARDL and robustness check.

Variables	Coeff.	p-value	Variables	Coeff.	p-value
Panel A: Asymmetric CS-ARDL estimator
Variables	Long-run		Short-run
GIN	0.031	0.180	$∆$ GIN	0.030	0.120
EGP	−1.095*	0.000	$∆$ EGP	−0.888*	0.000
ENT⁻	−0.128**	0.016	$∆$ ENT⁻	−0.137*	0.002
ENT⁺	0.106***	0.066	$∆$ ENT⁺	0.060	0.115
GLO	−1.132***	0.068	$∆$ GLO	−0.831**	0.045
			ECT	−0.868*	0.000

Panel B: Robustness check
Variables	Asymmetric FMOLS		Asymmetric CCR
Variables	Coeff.	t-stat	Coeff.	t-stat
GIN	0.020	1.500	0.020	−0.280
EGP	−0.970*	−41.300	−0.980*	−26.260
ENT⁻	−0.170*	−43.520	−0.180*	−25.510
ENT⁺	0.060*	25.450	0.050*	14.110
GLO	−0.410*	−7.200	−0.340*	−4.180

*, **, and *** refer to 1%, 5%, and 10% at significance levels, respectively.

The empirical estimates underscored that green investments possess environmental quality-enhancing attributes in the short and long run. However, it is pertinent to highlight that the contributions of green investment to environmental progress remained unsubstantial in both time frames. This outcome answered the third research question by highlighting green investments' insufficient environmental quality-enhancing effects in these selected economies. Furthermore, this revelation invalidates the second hypothesis that green investments are sufficient to increase environmental quality in the 13 advanced economies. However, the outcome underscores the potential of these green investments to enhance environmental quality if more investments are made in its favor. Unarguably, green investments are critical to green development and environmental progress. This inference hinges on the submissions of some extant studies (Lin et al. 2023; Sharif et al. 2024; Uche et al. 2024) that underscored the pivotal role of green investments in environmental progress in several countries. Not discountenancing possible dissenting inferences (Singh et al. 2023; Wang 2023); however, adequate and consistent public and private financial support remains critical to environmental vitality in any economy. Among others, such investments should transcend several areas of green investments, including energy efficiency R&D and environmental quality-enhancing innovations. Hence, policymakers in these developed economies should prioritize green investments among other vital components of sustainable development. Likewise, they should ensure public and private sector participation, given that isolated practices may not yield optimal results.

The empirical analysis also highlights the critical role of ENT in environmental survival in the selected 13 developed nations. The study differentiates the effects of increasing and decreasing ENT on environmental quality in these selected developed countries. This step underlines a critical novelty of this study, given that prior studies ignored such dimensions. Besides, such information will guide policymaking regarding supporting ENT or otherwise. The empirical analysis uncovers that while increasing entrepreneurial activities facilitates environmental progress, decreasing entrepreneurial activities dampens environmental progress in these developed countries. Notably, the opposing implications of ENT on environmental quality are consistent in both time dimensions. As seen in Table 3 Panel B, ENT has an asymmetric effect on environmental quality in both the short and long term. Hence, the third hypothesis is accepted, given the differential effects of opposing changes in ENT on environmental quality. Furthermore, the verified asymmetric relationship underlines the essence of cautious policy implementations since a one-size-fits-all policy option may bias policy targets.

In the long run, increased ENT elevated environmental progress by approximately 0.11%, whereas decreased ENT reduced the quality of the environment by approximately 0.13%. The short-run effects of increasing and decreasing ENT mirror their long-run attributes with considerable policy imports. The opposing implications of positive and negative changes in ENT are fundamental to verifying the fourth and fifth hypotheses. Accordingly, the differentiated effects validate the fourth and fifth hypotheses, given that positive/negative shocks from ENT increase/decrease environmental quality in the 13 advanced economies. Notably, increasing ENT produced an insufficient positive impact in the short run; however, its long-run significant positive contributions highlight the essence of functional entrepreneurial activities for environmental sustainability. Although the results demonstrate a positive relationship between ENT and environmental sustainability in developed nations, a decline in entrepreneurial activity exerts a more pronounced negative impact on environmental quality further confirming that this connection is asymmetric. This finding underscores the importance of fostering a supportive environment for entrepreneurial endeavors. This observation aligns with existing literature that emphasizes the pivotal role of ENT in driving economic growth and fostering innovation (Galindo-Martín et al. 2021; Khezri et al. 2024; Pradhan et al. 2020). Increased entrepreneurial activity can stimulate innovation, leading to resource efficiency, reduced waste generation, and enhanced energy conservation, all of which contribute to improved environmental sustainability. Furthermore, Patzelt and Shepherd (2011) argue that entrepreneurial ventures can contribute to environmental protection by mitigating pollution, supporting sustainable agricultural practices, and curbing deforestation. York and Venkataraman (2010) further emphasize the potential of ENT as a key driver of solutions to pressing environmental challenges.

In conclusion, governments of developed countries should actively foster and encourage entrepreneurial activities, given their demonstrated potential to contribute to environmental sustainability goals. Policy efforts should be directed toward mitigating any factors that may lead to a decline in entrepreneurial activity, thereby preventing potential negative impacts on environmental quality. As highlighted by Hussain et al. (2024), Omri and Afi (2020), and Udemba et al. (2024), in the cases of China, 32 developing countries, and BRICS, ENT activities spur environmental progress. However, they should be encouraged to opt for low-carbon energies instead of their high-carbon version for environmental vitality.

As a policy roadmap, it is of the essence that 13 developed countries align all ENT activities to existing environmental sustainability policies and regulations. It is also cogent to ensure maximum compliance and adherence to SDGs that emphasize ecological stability. Furthermore, Raimi (2024) underscores the need to forestall the overriding influence of harmful ideologies, social structures, and power dynamics hindering the contributions of ENT to environmental progress in most countries. This submission is noteworthy, given that ENT is profit-oriented. Likewise, Pacheco et al. (2010) explain that the environmental quality-deteriorating effects of ENT are contingent on the divergences between individual goals and collective gains. Hence, in pursuit of profits and business expansions, most entrepreneurs neglect the environmental consequences of their actions. Therefore, some stringent policies are required to keep them in check.

The contributions of globalization to environmental performance in these 13 developed countries are also articulated herein. The empirical analysis uncovers the negative implications of globalization on environmental performance both in the short and long term. The outcomes of this investigation underscore the fundamental role of globalization in the escalating environmental sprawl witnessed in these countries over time. The explanations for these unpleasant contributions of globalization may not be far-fetched. First, prior studies, including Sadiq et al. (2023), reported similar outcomes in the case of Southeast Asian countries. Second, these countries constantly pursue economic gains through several engagements, including globalization. Hence, it is only logical to expect negative repercussions from activities prioritizing economic prosperity over environmental gains. Based on this discovery, these countries should align all their economic and noneconomic relationships with other countries for sustainable development requirements. They should ensure that globalization engagements do not override environmental survival. Instead, all activities that negate the established environmental sustainability protocols should be avoided.

4.3 Robustness Analysis

Further insights pertaining to the relationship between environmental quality and the enlisted control variables were derived from two robustness analyses. In this regard, two novel analytical techniques were extended for updated perspectives, including the asymmetric FMOLS and CCR. Remarkably, the evidence from the robustness tests (Table 4, Panel B) remained consistent with the results of the baseline estimator. On this premise, the adaptation and implementation of the underlying policy inferences is expected to ensure environmental sustainability in the 13 advanced economies. Remarkably, the outcomes highlight that enhancing ENT and green investments remains fundamental to the enthronement of ecological progress in these economies.

5 Conclusion, Policy Perspective, and Limits

This study uses novel econometric methods to determine how ENT impacts environmental sustainability. The existing literature is insufficient to explain the impacts of ENT on the environment. This study focuses on developed economies, in particular, targeting a sample where entrepreneurs can integrate into the economy more easily. Furthermore, this study presents an in-depth ENT–environment nexus by modifying the CS-ARDL method and separating ENT into positive and negative shocks. Empirical analyses confirmed the existence of an asymmetric relationship between LCF and ENT. In other words, negative movements in ENT lead to environmental quality moving toward a negative path. On the other hand, positive fluctuations in ENT contribute to ecological sustainability. These results stem from the superiority of our modified Asymmetric CS-ARDL estimator. In addition, green investments also support ecological quality. Economic growth and globalization activities are detrimental to environmental sustainability. Based on these results, our study offers a policy perspective within the framework of SDGs.

The primary sources of ENT are motivation and the enrichment of profit perspectives. The findings of our study confirm that the decrease in ENT is unsuitable for environmental sustainability. Therefore, entrepreneurial activities should be increased in a controlled manner in 13 developed economies. For this, governments need to activate policies that encourage ENT. This can be achieved through two channels. First, successful entrepreneurs should be brought together and asked what difficulties they face in entering the markets. According to their answers, ENT courses should be organized by expert teams in 13 developed economies. The aim here is to prepare individuals for ENT both scientifically and sociologically. These courses can be organized through municipalities, and individuals who do not dare to be entrepreneurs can contribute to the economy through these courses. Moreover, in these courses, where environmental awareness will also be explained, individuals will prioritize environmental concerns before starting entrepreneurial activities. Otherwise, an uncontrolled increase in entrepreneurial activities will direct entrepreneurs to fossil energy sources and support the aim of making a quick profit. Environmental concerns will be kept in the background because of a lack of financing. Second, positive financing privileges can be provided to educated entrepreneurs. Low interest rates can be applied to entrepreneurs who prioritize environmental awareness, and tax advantages can be provided. Thus, individuals will increase their environmental awareness before becoming entrepreneurs and prioritize the environment in their entrepreneurial activities. Therefore, these policies will encourage clean and accessible energy sources (SDG 7) and contribute to the climate action (SDG 13) movement.

The positive environmental contribution of green investments should continue to be utilized. Since the 13 economies in question are developed, they are in a comfortable financial position. Because of this advantage, these economies can accelerate the climate action movement by making more green investments. Since renewable energy sources require serious infrastructure and substantial financing, the results obtained from the analysis are essential for the 13 economies. In these economies, green investments are mainly carried out through the state. In this case, rapid policies should be implemented so that at least 50% of the state and 50% of the private sector. The state should activate policies encouraging the private sector to increase green investments. Green investments, especially those made by large companies, are essential. Statements should be made to the representatives of the largest companies in 13 countries, and financing packages should be announced to attract them to this area. In this way, most large companies using fossil resources can accelerate the transition to green energy sources. Countries can give these companies unused lands and thus accelerate renewable energy R&D studies. Then, 13 developed economies can take an essential step toward SDG 7.

Economic growth must create environmental pollution. Here, countries should move to accelerate the transition from fossil to green resources without compromising growth. In other words, countries should continue to grow and move away from fossil fuels and toward green resources. This cannot be achieved with short-term policies. However, it can be achieved with long-term and determined policies. Especially in the transition from fossil to green resources, serious infrastructure moves are required, and since this is a long process, energy efficiency policies should be pioneered. With the maturation of green resources, energy efficiency policies should be terminated, and fossil fuels should be moved away. In this way, economies can continue to grow and minimize environmental damage by polluting the environment to a minimum. Globalization activities provide harmful environmental conditions for 13 developed economies. Therefore, ecological damage caused by globalization should be minimized and, if possible, eliminated. For this purpose, the environmental activities of multinational companies operating globally should be examined in detail. Policies that reduce these companies' intensive use of fossil resources should be implemented. In this context, tax advantages that encourage green energy can be provided. Moreover, strict environmental policies should be implemented in trade activities, and fossil-based products should be limited.

Because of the nature of science, this study has some limitations. In addition, this study provides critical future directions. First, because of the limited data on ENT, this study covers the data from 2001 to 2022. If future studies can extend the data range, they can investigate the validity of the LCC by adding income and the income square. Second, this study uses the established business ownership rate as a proxy for ENT. Future studies can deeply examine the relationships between ENT and the environment using different subheadings for ENT. Third, this study analyzes panel data because of insufficient data length. Future studies can investigate the environmental quality of individual countries with recent time series techniques (Fourier Augmented ARDL, Fourier asymmetric ARDL, quantile on quantile, time-varying causality). Fourth, our study uses LCF as the dependent variable. Future studies can test the EKC hypothesis with environmental pollution indicators for the same sample. Thus, it can be seen whether the results change according to environmental indicators. Lastly, this study allows only ENT to be asymmetric. Future studies can investigate by allowing financial deepening, foreign direct investment, and trade openness variables to be asymmetric in addition to ENT.

References

Ahmed, Z., A. E. Caglar, and M. Murshed. 2022. “A Path Towards Environmental Sustainability: The Role of Clean Energy and Democracy in Ecological Footprint of Pakistan.” Journal of Cleaner Production 358: 132007. https://doi.org/10.1016/j.jclepro.2022.132007.
10.1016/j.jclepro.2022.132007
Web of Science® Google Scholar
Ahmed, Z., M. Cary, and H. P. Le. 2021. “Accounting Asymmetries in the Long-Run Nexus Between Globalization and Environmental Sustainability in the United States: An Aggregated and Disaggregated Investigation.” Environmental Impact Assessment Review 86, no. January 2021: 106511. https://doi.org/10.1016/j.eiar.2020.106511.
10.1016/j.eiar.2020.106511
Google Scholar
Al Mamun, M., S. Boubaker, and D. K. Nguyen. 2022. “Green Finance and Decarbonization: Evidence From Around the World.” Finance Research Letters 46: 102807.
10.1016/j.frl.2022.102807
Web of Science® Google Scholar
Alvarado, R., B. Tillaguango, M. Murshed, et al. 2022. “Impact of the Informal Economy on the Ecological Footprint: The Role of Urban Concentration and Globalization.” Economic Analysis and Policy 75: 750–767.
10.1016/j.eap.2022.07.001
Web of Science® Google Scholar
Ardito, L., A. Messeni Petruzzelli, F. Pascucci, and E. Peruffo. 2019. “Inter-Firm R&D Collaborations and Green Innovation Value: The Role of Family Firms' Involvement and the Moderating Effects of Proximity Dimensions.” Business Strategy and the Environment 28, no. 1: 185–197.
10.1002/bse.2248
Web of Science® Google Scholar
Bakry, W., G. Mallik, X.-H. Nghiem, A. Sinha, and X. V. Vo. 2023. “Is Green Finance Really “Green”? Examining the Long-Run Relationship Between Green Finance, Renewable Energy and Environmental Performance in Developing Countries.” Renewable Energy 208: 341–355.
10.1016/j.renene.2023.03.020
Web of Science® Google Scholar
Becker, B. 2015. “Public R&D Policies and Private R&D Investment: A Survey of the Empirical Evidence.” Journal of Economic Surveys 29, no. 5: 917–942.
10.1111/joes.12074
Web of Science® Google Scholar
Breusch, T. S., and A. R. Pagan. 1980. “The Lagrange Multiplier Test and Its Applications to Model Specification in Econometrics.” Review of Economic Studies 47, no. 1: 239–253.
10.2307/2297111
Web of Science® Google Scholar
Caglar, A. E., S. B. Avci, Z. Ahmed, and N. Gökçe. 2024b. “Assessing the Role of Green Investments and Green Innovation in Ecological Sustainability: From a Climate Action Perspective on European Countries.” Science of the Total Environment 928: 172527.
10.1016/j.scitotenv.2024.172527
CAS PubMed Web of Science® Google Scholar
Caglar, A. E., M. Daştan, Z. Ahmed, M. Mert, and S. B. Avci. 2024a. “ The Synergy of Renewable Energy Consumption, Green Technology, and Environmental Quality: Designing Sustainable Development Goals Policies.” In Natural Resources Forum. Blackwell Publishing Ltd.
10.1111/1477-8947.12577
Google Scholar
Castellanza, L., and M. Woywode. 2024. “Types, Determinants, and Outcomes of Entrepreneurial Behaviours During Crises.” Entrepreneurship & Regional Development 36, no. 9–10: 1333–1362.
10.1080/08985626.2024.2324320
Web of Science® Google Scholar
Chen, Y., S. Ren, and Y. Ma. 2024. “The Impact of Eco-Preneurship and Green Technology on Greenhouse Gas Emissions—An Analysis of East Asian Economies.” Heliyon 10, no. 8: e29083.
10.1016/j.heliyon.2024.e29083
CAS PubMed Web of Science® Google Scholar
Chudik, A., and M. H. Pesaran. 2015. “Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Data Models With Weakly Exogenous Regressors.” Journal of Econometrics 188, no. 2: 393–420.
10.1016/j.jeconom.2015.03.007
Web of Science® Google Scholar
Cohen, B., and M. I. Winn. 2007. “Market Imperfections, Opportunity and Sustainable ENT.” Journal of Business Venturing 22, no. 1: 29–49.
10.1016/j.jbusvent.2004.12.001
Google Scholar
Dean, T. J., and J. S. McMullen. 2007. “Toward a Theory of Sustainable ENT: Reducing Environmental Degradation Through Entrepreneurial Action.” Journal of Business Venturing 22, no. 1: 50–76.
10.1016/j.jbusvent.2005.09.003
Google Scholar
Dhahri, S., and A. Omri. 2018. “ENT Contribution to the Three Pillars of Sustainable Development: What Does the Evidence Really Say?” World Development 106: 64–77. https://doi.org/10.1016/j.worlddev.2018.01.008.
10.1016/j.worlddev.2018.01.008
Web of Science® Google Scholar
Dogan, A., and U. K. Pata. 2022. “The Role of ICT, R&D Spending and Renewable Energy Consumption on Environmental Quality: Testing the LCC Hypothesis for G7 Countries.” Journal of Cleaner Production 380, no. P1: 135038. https://doi.org/10.1016/j.jclepro.2022.135038.
10.1016/j.jclepro.2022.135038
Google Scholar
Dreher, A. 2006. “Does Globalization Affect Growth? Evidence From a new Index of Globalization.” Applied Economics 38, no. 10: 1091–1110.
10.1080/00036840500392078
Web of Science® Google Scholar
Elmonshid, L. B. E., and O. A. Sayed. 2024. “The Relationship Between ENT and Sustainable Development in Saudi Arabia: A Comprehensive Perspective.” Economies 12, no. 8: 12080198.
10.3390/economies12080198
Google Scholar
Fang, Z., C. Yang, and X. Song. 2022. “How Do Green Finance and Energy Efficiency Mitigate Carbon Emissions Without Reducing Economic Growth in G7 Countries?” Frontiers in Psychology 13: 879741.
10.3389/fpsyg.2022.879741
PubMed Google Scholar
Galindo-Martín, M. Á., M. S. Castaño-Martínez, and M. T. Méndez-Picazo. 2021. “The Role of ENT in Different Economic Phases.” Journal of Business Research 122: 171–179. https://doi.org/10.1016/j.jbusres.2020.08.050.
10.1016/j.jbusres.2020.08.050
Google Scholar
Ganda, F. 2018. “The Influence of Green Energy Investments on Environmental Quality in OECD Countries.” Environmental Quality Management 28, no. 2: 17–29.
10.1002/tqem.21595
Google Scholar
GEM. 2024. Entrepreneurial Behaviour and Attitudes. https://www.gemconsortium.org/data, (Accessed 20th June 2024).
Google Scholar
GFN. 2023. Global Footprint Network. http://data.footprintnetwork.org. (Accessed 5th January 2025).
Google Scholar
GFN. 2024. Global Footprint Network. http://data.footprintnetwork.org, (Accessed 20th June 2024).
Google Scholar
He, J., M. Nazari, Y. Zhang, and N. Cai. 2020. “Opportunity-Based Entrepreneurship and Environmental Quality of Sustainable Development: A Resource and Institutional Perspective.” Journal of Cleaner Production 256: 120390.
10.1016/j.jclepro.2020.120390
Web of Science® Google Scholar
He, N., S. Zeng, and G. Jin. 2023. “Achieving Synergy Between Carbon Mitigation and Pollution Reduction: Does Green Finance Matter?” Journal of Environmental Management 342: 118356.
10.1016/j.jenvman.2023.118356
CAS PubMed Google Scholar
He, X., and J. Zhou. 2024. “ENT Promotion Policies and Urban Carbon Emission Efficiency: Does Environmental Concerns Matter?” Environmental Research Communications 6, no. 5: 2515–7620.
10.1088/2515-7620/ad4262
Google Scholar
Hu, Y., and J. Zheng. 2022. “How Does Green Credit Affect Carbon Emissions in China? A Theoretical Analysis Framework and Empirical Study.” Environmental Science and Pollution Research International 29, no. 39: 59712–59726.
10.1007/s11356-022-20043-1
PubMed Google Scholar
Hussain, S., E. N. Udemba, F. Emir, N.-U. Khan, W. Chammam, and A. Riahi. 2024. “Assessing Sustainable Development With the Forces of Technological Innovation, Entrepreneurial Activity and Energy Consumption: Insight From Asymmetric and Bootstrap Causality Methods.” Energy & Environment 35, no. 6: 3165–3185.
10.1177/0958305X231159442
Web of Science® Google Scholar
IEA. 2021. Global Energy Review 2021. Assessing the Effects of Economic Recoveries on Global Energy Demand and CO₂ Emissions in 2021. https://www.iea.org/reports/global-energy-review-2021/co2-emissions. (Accessed 20th June 2024).
Google Scholar
IEA. 2024. Energy Technology RD&D Budgets, https://www.iea.org/data-and-statistics/data-product/energy-technology-rd-and-d-budget-database-2, (Accessed 20th June 2024).
Google Scholar
Jha, V. K., and A. S. Pande. 2024. “Making Sustainable Development Happen: Does Sustainable ENT Make Nations More Sustainable?” Journal of Cleaner Production 440: 140849.
10.1016/j.jclepro.2024.140849
Google Scholar
Khan, M. A., H. Riaz, M. Ahmed, and A. Saeed. 2022. “Does Green Finance Really Deliver What Is Expected? An Empirical Perspective.” Borsa Istanbul Review 22, no. 3: 586–593.
10.1016/j.bir.2021.07.006
Web of Science® Google Scholar
Khezri, M., M. S. Karimi, and B. Naysary. 2024. “Exploring the Impact of Entrepreneurial Indicators on CO₂ Emissions Within the Environmental Kuznets Curve Framework: A Cross-Sectional Study.” Environment, Development and Sustainability. https://doi.org/10.1007/s10668-024-05050-1.
10.1007/s10668-024-05050-1
PubMed Web of Science® Google Scholar
Koçak, E., and Z. Ş. Ulucak. 2019. “The Effect of Energy R&D Expenditures on CO₂ Emission Reduction: Estimation of the STIRPAT Model for OECD Countries.” Environmental Science and Pollution Research 1: 14328–14338. https://doi.org/10.1007/s11356-019-04712-2.
10.1007/s11356-019-04712-2
Google Scholar
Krishnan, C. S. N., L. S. Ganesh, and C. Rajendran. 2022. “Entrepreneurial Interventions for Crisis Management: Lessons From the Covid-19 Pandemic's Impact on Entrepreneurial Ventures.” International Journal of Disaster Risk Reduction 72: 102830.
10.1016/j.ijdrr.2022.102830
PubMed Web of Science® Google Scholar
Lee, C. C., F. Liu, and J. Shi. 2023. “What Impacts Do Green Bonds Have on Carbon Emissions and How? A Dynamic Spatial Perspective in China.” Environmental Science and Pollution Research International 30, no. 55: 117981–117997.
10.1007/s11356-023-30014-9
PubMed Google Scholar
Lee, C.-C., and C.-C. Lee. 2022. “How Does Green Finance Affect Green Total Factor Productivity? Evidence From China.” Energy Economics 107: 105863.
10.1016/j.eneco.2022.105863
Web of Science® Google Scholar
Lee, K. H., and B. Min. 2015. “Green R&D for Eco-Innovation and Its Impact on Carbon Emissions and Firm Performance.” Journal of Cleaner Production 108: 534–542. https://doi.org/10.1016/j.jclepro.2015.05.114.
10.1016/j.jclepro.2015.05.114
CAS Web of Science® Google Scholar
Lin, T., L. Zhang, D. Xia, D. Zhou, and J. Li. 2023. “Towards a Low-Carbon Economy: How Does Green Credit Affect Carbon Productivity?” Journal of Environmental Planning and Management 1–29: 2245967.
Google Scholar
Madaleno, M., E. Dogan, and D. Taskin. 2022. “A Step Forward on Sustainability: The Nexus of Environmental Responsibility, Green Technology, Clean Energy and Green Finance.” Energy Economics 109: 105945.
10.1016/j.eneco.2022.105945
Web of Science® Google Scholar
Muñoz, P., and B. Cohen. 2018. “Sustainable Entrepreneurship Research: Taking Stock and Looking Ahead.” Business Strategy and the Environment 27, no. 3: 300–322.
10.1002/bse.2000
Web of Science® Google Scholar
Narayan, P. K., and S. Narayan. 2010. “Carbon Dioxide Emissions and Economic Growth: Panel Data Evidence From Developing Countries.” Energy Policy 38, no. 1: 661–666.
10.1016/j.enpol.2009.09.005
Web of Science® Google Scholar
Omri, A. 2018. “ENT, Sectoral Outputs and Environmental Improvement: International Evidence.” Technological Forecasting and Social Change 128: 46–55.
10.1016/j.techfore.2017.10.016
Web of Science® Google Scholar
Omri, A., and H. Afi. 2020. “How Can ENT and Educational Capital Lead to Environmental Sustainability?” Structural Change and Economic Dynamics 54: 1–10. https://doi.org/10.1016/j.strueco.2020.03.007.
10.1016/j.strueco.2020.03.007
Web of Science® Google Scholar
Pacheco, D. F., T. J. Dean, and D. S. Payne. 2010. “Escaping the Green Prison: ENT and the Creation of Opportunities for Sustainable Development.” Journal of Business Venturing 25, no. 5: 464–480.
10.1016/j.jbusvent.2009.07.006
Web of Science® Google Scholar
Park, J. Y. 1992. “Canonical Cointegrating Regressions.” Econometrica: Journal of the Econometric Society 60: 119–143.
10.2307/2951679
Web of Science® Google Scholar
Patzelt, H., and D. A. Shepherd. 2011. “Negative Emotions of an Entrepreneurial Career: Self-Employment and Regulatory Coping Behaviors.” Journal of Business Venturing 26, no. 2: 226–238. https://doi.org/10.1016/j.jbusvent.2009.08.002.
10.1016/j.jbusvent.2009.08.002
Web of Science® Google Scholar
Pesaran. 2004. Cambridge Working Papers in Economics No. 0435. In: General Diagnostic Tests for Cross Section Dependence in Panels. University of Cambridge, Faculty of Economics Available online: https://www.repository.cam.ac.uk/handle/1810/446, (Accessed 20th September 2024).
Google Scholar
Pesaran, M. H. 2007. “A Simple Panel Unit Root Test in the Presence of Cross-Section Dependence.” Journal of Applied Econometrics 22, no. 2: 265–312.
10.1002/jae.951
Web of Science® Google Scholar
Pesaran, M. H., and T. Yamagata. 2008. “Testing Slope Homogeneity in Large Panels.” Journal of Econometrics 142, no. 1: 50–93.
10.1016/j.jeconom.2007.05.010
Web of Science® Google Scholar
Philip, L. D., F. Emir, and A. A. Alola. 2021. “The Asymmetric Nexus of ENT and Environmental Quality in a Developing Economy.” International Journal of Environmental Science and Technology 19, no. 8: 7625–7636.
10.1007/s13762-021-03670-y
Google Scholar
Phillips, P. C., and B. E. Hansen. 1990. “Statistical Inference in Instrumental Variables Regression With I (1) Processes.” Review of Economic Studies 57, no. 1: 99–125.
10.2307/2297545
Web of Science® Google Scholar
Pradhan, R. P., M. B. Arvin, M. Nair, and S. E. Bennett. 2020. “The Dynamics Among ENT, Innovation, and Economic Growth in the Eurozone Countries.” Journal of Policy Modeling 42, no. 5: 1106–1122. https://doi.org/10.1016/j.jpolmod.2020.01.004.
10.1016/j.jpolmod.2020.01.004
Web of Science® Google Scholar
Provasnek, A. K., E. Schmid, B. Geissler, and G. Steiner. 2017. “Sustainable Corporate Entrepreneurship: Performance and Strategies Toward Innovation.” Business Strategy and the Environment 26, no. 4: 521–535.
10.1002/bse.1934
Web of Science® Google Scholar
Raimi, L. 2024. “ The Role of ENT as Catalysts for Sustainability and a Green, Resilient Economy: Critical Discourse Analysis.” In Entrepreneurship and Development for a Green Resilient Economy (Lab for Entrepreneurship and Development), 23–46. Emerald Publishing Limited. https://doi.org/10.1108/978-1-83797-088-920241002.
10.1108/978-1-83797-088-920241002
Google Scholar
Ren, X., Q. Shao, and R. Zhong. 2020. “Nexus Between Green Finance, Non-Fossil Energy Use, and Carbon Intensity: Empirical Evidence From China Based on a Vector Error Correction Model.” Journal of Cleaner Production 277: 122844.
10.1016/j.jclepro.2020.122844
Web of Science® Google Scholar
Riti, J. S., A. M. Dankumo, and H. D. Gubak. 2015. “ENT and Environmental Sustainability: Evidence From Nigeria.” Journal of Economics and Sustainable Development 6, no. 8: 130–140. http://www.iiste.org/Journals/index.php/JEDS/article/view/21914/22255.
Google Scholar
Sadiq, M., D. Kannaiah, G. Yahya Khan, M. S. Shabbir, K. Bilal, and A. Zamir. 2023. “Does Sustainable Environmental Agenda Matter? The Role of Globalization Toward Energy Consumption, Economic Growth, and Carbon Dioxide Emissions in South Asian Countries.” Environment, Development and Sustainability 25: 76–95.
10.1007/s10668-021-02043-2
Web of Science® Google Scholar
Santos, S. C., A. Caetano, P. Spagnoli, S. F. Costa, and X. Neumeyer. 2017. “Predictors of Entrepreneurial Activity Before and During the European Economic Crisis.” International Entrepreneurship and Management Journal 13: 1263–1288.
10.1007/s11365-017-0453-8
Web of Science® Google Scholar
Scartozzi, G., S. Delladio, F. Rosati, A. I. Nikiforou, and A. Caputo. 2024. “The Social and Environmental Impact of ENT: A Review and Future Research Agenda.” Review of Managerial Science 19: 1041–1072. https://doi.org/10.1007/s11846-024-00783-9.
10.1007/s11846-024-00783-9
Google Scholar
Sharif, A., E. Sofuoglu, S. Kocak, and A. Anwar. 2024. “Can Green Finance and Energy Provide a Glimmer of Hope Towards Sustainable Environment in the Midst of Chaos? An Evidence From Malaysia.” Renewable Energy 223: 119982.
10.1016/j.renene.2024.119982
CAS Google Scholar
Shepherd, D. A., and H. Patzelt. 2011. “The New Field of Sustainable ENT: Studying Entrepreneurial Action Linking “What Is to Be Sustained” With “What Is to Be Developed”.” ENT Theory and Practice 35, no. 1: 137–163.
10.1111/j.1540-6520.2010.00426.x
Web of Science® Google Scholar
Shin, Y., B. Yu, and M. Greenwood-Nimmo. 2014. “ Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework.” In Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications, 281–314.
10.1007/978-1-4899-8008-3_9
Google Scholar
Singh, A. K., S. A. Raza, J. Nakonieczny, and U. Shahzad. 2023. “Role of Financial Inclusion, Green Innovation, and Energy Efficiency for Environmental Performance? Evidence From Developed and Emerging Economies in the Lens of Sustainable Development.” Structural Change and Economic Dynamics 64: 213–224.
10.1016/j.strueco.2022.12.008
Google Scholar
Sinha, A., S. Mishra, A. Sharif, and L. Yarovaya. 2021. “Does Green Financing Help to Improve Environmental & Social Responsibility? Designing SDG Framework Through Advanced Quantile Modelling.” Journal of Environmental Management 292: 112751.
10.1016/j.jenvman.2021.112751
PubMed Web of Science® Google Scholar
STATISTA. 2022. Distribution of Carbon Dioxide Emissions Worldwide in 2022, by Select Country. https://www.statista.com/statistics/271748/the-largest-emitters-of-co2-in-the-world/#:~:text=China%20was%20the%20biggest%20emitter,global%20CO%E2%82%82%20emissions%20in%202022. (Accessed 20th September 2024).
Google Scholar
Stel, A. V., M. Carree, and R. Thurik. 2005. “The Effect of Entrepreneurial Activity on National Economic Growth.” Small Business Economics 24: 311–321.
10.1007/s11187-005-1996-6
Web of Science® Google Scholar
Sun, H., A. K. Pofoura, I. Adjei Mensah, L. Li, and M. Mohsin. 2020. “The Role of Environmental ENT for Sustainable Development: Evidence From 35 Countries in Sub-Saharan Africa.” Science of The Total Environment 741: 140132.
10.1016/j.scitotenv.2020.140132
CAS PubMed Web of Science® Google Scholar
The International Renewable Energy Agency. 2023. COP28, IRENA and Global Renewables Alliance Outline Roadmap at Pre-COP on Fast-Tracking the Energy Transition by Tripling Renewable Power and Doubling Energy Efficiency by 2030. Joint Press Release Available at: https://www.irena.org/News/pressreleases/2.
Google Scholar
Uche, E., N. Das, and N. Ngepah. 2024. “Green Environments Reimagined Through the Lens of Green Finance, Green Innovations, Green Taxation, and Green Energies. Wavelet Quantile Correlation and Rolling Window-Based Quantile Causality Perspective.” Renewable Energy 228: 120650.
10.1016/j.renene.2024.120650
Web of Science® Google Scholar
Udemba, E. N., L. D. Philip, and F. Emir. 2022. “Performance and Sustainability of Environment Under Entrepreneurial Activities, Urbanization and Renewable Energy Policies: A Dual Study of Malaysian Climate Goal.” Renewable Energy 189: 734–743.
10.1016/j.renene.2022.03.024
Web of Science® Google Scholar
Udemba, E. N., S. A. R. Shah, L. D. Philip, and G. Zhao. 2024. “The Mediating Role of Green Energy and Environmental Policies in Sustainable Development for BRICS Economies: A Tripartite Impact of Entrepreneurial Activities, Urban Development and Economic Growth on Ecological Footprint.” Sustainable Development 32, no. 5: 4649–4670.
10.1002/sd.2916
Web of Science® Google Scholar
United Nations. 2021. COP26: Together for our Planet. https://www.un.org/en/climatechange/cop26.
Google Scholar
Urbano, D., and S. Aparicio. 2016. “ENT Capital Types and Economic Growth: International Evidence.” Technological Forecasting and Social Change 102: 34–44. https://doi.org/10.1016/j.techfore.2015.02.018.
10.1016/j.techfore.2015.02.018
Web of Science® Google Scholar
Wang, J., and Y. Ma. 2022. “How Does Green Finance Affect CO₂ Emissions? Heterogeneous and Mediation Effects Analysis.” Frontiers in Environmental Science 10: 931086. https://doi.org/10.3389/fenvs.2022.931086.
10.3389/fenvs.2022.931086
Google Scholar
Wang, Y. 2023. “Can the Green Credit Policy Reduce Carbon Emission Intensity of “High-Polluting and High-Energy-Consuming” Enterprises? Insight From a Quasi-Natural Experiment in China.” Global Finance Journal 58: 100885.
10.1016/j.gfj.2023.100885
Google Scholar
Wang, Z., Y. Chandavuth, B. Zhang, Z. Ahmed, and M. Ahmad. 2023. “Environmental Degradation, Renewable Energy, and Economic Growth Nexus: Assessing the Role of Financial and Political Risks?” Journal of Environmental Management 325: 116678. https://doi.org/10.1016/j.jenvman.2022.116678.
10.1016/j.jenvman.2022.116678
PubMed Web of Science® Google Scholar
WDI. 2024. World Development Indicators, https://databank.worldbank.org/source/world-development-indicators (2023), (Accessed 20th June 2024).
Google Scholar
Westerlund, J. 2007. “Testing for Error Correction in Panel Data.” Oxford Bulletin of Economics and Statistics 69, no. 6: 709–748.
10.1111/j.1468-0084.2007.00477.x
Web of Science® Google Scholar
Xu, J., F. Chen, W. Zhang, Y. Liu, and T. Li. 2023. “Analysis of the Carbon Emission Reduction Effect of Fintech and the Transmission Channel of Green Finance.” Finance Research Letters 56: 104127.
10.1016/j.frl.2023.104127
Web of Science® Google Scholar
Yao, S., X. Zhang, and W. Zheng. 2022. “On Green Credits and Carbon Productivity in China.” Environmental Science and Pollution Research International 29, no. 29: 44308–44323.
10.1007/s11356-022-18982-w
PubMed Web of Science® Google Scholar
York, J. G., and S. Venkataraman. 2010. “The Entrepreneur–Environment Nexus: Uncertainty, Innovation, and Allocation.” Journal of Business Venturing 25, no. 5: 449–463.
10.1016/j.jbusvent.2009.07.007
Web of Science® Google Scholar
Youssef, B. A., S. Boubaker, and A. Omri. 2018. “ENT and Sustainability: The Need for Innovative and Institutional Solutions.” Technological Forecasting and Social Change 129: 232–241.
10.1016/j.techfore.2017.11.003
Web of Science® Google Scholar

Citing Literature

Volume34, Issue5

July 2025

Pages 5644-5656

Future Pathways for Net Zero Emission: Analyzing the Nexus of Entrepreneurship and Ecological Sustainability Development in Developed Economies

Abstract

1 Introduction