List of acronyms Asia-Pacific Economic Cooperation - APEC Autoregressive Distributed Lag - ARDL Ecological Footprint - EFP Economic Policy Uncertainty - EPU Energy-related uncertainty in
Introduction
Problem statement
Recent global events, including trade wars, political polarization, the financial crisis, and the Covid-19 pandemic, have heightened concerns about increasing uncertainty (Ahir et al., 2022) Research indicates that this rising uncertainty adversely impacts economic activities, affecting both resilience and vulnerability (Ghirelli et al., 2021) Historical data from the post-World War II era reveals that fluctuations in oil prices have been linked to diminished economic growth (van de Ven).
The World Uncertainty Index (WU1) has sparked empirical research into how uncertainty affects economic activity This index includes an energy uncertainty component, which builds on the work of Afkhami et al (2017) with 87 terms, and incorporates 15 keywords from Dang et al (2023) to effectively capture shocks and crises within the energy sector.
The Energy-related Uncertainty Index is significantly influenced by various crises, including oil shocks, the global financial crisis, the European debt crisis, the Covid-19 pandemic, and the Russian invasion of Ukraine This uncertainty is quantified using the Economic Policy Uncertainty (EPU) index, which has gained prominence in macroeconomic studies The EPU index plays a crucial role in managing macroeconomic variables, impacting the competitiveness and liquidity of financial markets, influencing investor and business behavior, and ultimately affecting the overall economic landscape.
Geopolitical tensions, such as the territorial conflict between China and India, sanctions against China regarding carbon emissions, and human rights issues with the Uyghurs, are driven by various factors The industrialization and over-exploitation of natural resources have resulted in significant global environmental pollution and ecological destruction, threatening human survival and development Environmental issues have emerged as critical social challenges in both developed and developing nations The ecological footprint, which measures human economic activities' impact on the environment, serves as an indicator of natural resource appropriation.
The connection between the energy-related uncertainty index and natural resource governance has garnered significant research interest, yet empirical evidence remains contentious, lacking universal policy recommendations Various approaches to analyzing the relationship between energy uncertainty and natural resources are explored within the energy economics literature.
Research Objectives and Research Questions
This scientific research paper evaluates the Energy Uncertainty Index (EUI) through statistical analysis and quantitative research methods The primary goal is to identify the causes of the EUI and propose solutions for its reduction in developed countries The central research question investigates the relationship between the EUI and natural resource governance, while also exploring the existence of an Environmental Kuznets Curve (EKC).
This study is organized into several key sections Section 2 explores theories pertinent to the research, focusing on natural resource management, the energy-related uncertainty index, and its correlation with the ecological footprint It also reviews prior empirical studies that examine the effects of the energy-related uncertainty index on the ecological footprint and related macroeconomic variables Sections 3 and 4 outline the research methodology and the dataset utilized, leading to the presentation of results and discussions Finally, Sections 5, 6, and 7 summarize the study's conclusions, policy implications, limitations, and suggestions for future research directions.
Literature review
Concept
Natural resources encompass all naturally occurring materials on Earth, including air, water, soil, minerals, forests, and fossil fuels (Hassan, Xia, et al., 2019) This category also includes environmental resources such as land, plants, animals, and natural energy The Ecological Footprint (EFP), developed in the 1990s, serves as a key metric for measuring natural resource consumption and has gained popularity for sustainability analysis (Ferguson, 1999) It is widely used to assess environmental performance and track progress towards sustainability, allowing for comparisons of resource requirements across different populations using a common metric of global productivity Wackernagel et al (2002) utilized the EFP to quantify the land, water, and biological resources necessary for producing human goods and services, as well as for managing waste and emissions generated by human activities annually.
The Ecological Footprint (EFP) is a standard measure of the Earth's biological resources required to support humanity's resource use and waste generation (Nicu & Faloric,
In 2023, analyzing the components of Environmental Footprint (EFP) allows for a better understanding of their contributions to overall demand, enabling the development of targeted strategies to optimize EFP savings A higher EFP value indicates greater natural resource consumption in specific countries, making it increasingly challenging for these resources to regenerate.
2.1.2 Energy-related uncertainty' index (EUI)
Recent events, including trade wars, political polarization, the global financial crisis, and the Covid-19 pandemic, have heightened concerns about increasing uncertainty (Ahir et al., 2022) Research indicates that this rising uncertainty is expected to adversely affect economic activities (Ghirelli et al., 2021).
The Energy-Related Uncertainty Index measures uncertainty by analyzing the frequency of the terms "energy" and "uncertainty" in local articles (Dang et al., 2023) This index incorporates a component of uncertainty based on the methodology of Ahir et al (2022) and extends the energy component introduced by Afkhami et al (2017), reflecting various shocks and crises within the energy sector Notably, the index exhibits a strong reaction not only to oil shocks but also to significant global events, including the financial crisis, the European debt crisis, the Covid-19 pandemic, and the Russian invasion of Ukraine.
Framework
The energy-related uncertainty index (EUI) reflects economic uncertainty in the energy market, comprising an energy-related sub-index and an uncertainty sub-index (Dang et al., 2023) Research indicates that economic policy uncertainty (EPU) positively impacts the ecological footprint by reducing energy consumption and the use of polluting goods, ultimately decreasing environmental degradation (Hussain et al., 2022; Jiao et al., 2022) However, Chu and Le (2022) contend that EPU can lead to economic recession, prompting businesses to prioritize cost-cutting over environmental protection Jiang et al (2021) further highlight that in the U.S., economic policy uncertainty diverts government focus from environmental issues, indirectly contributing to environmental degradation Conversely, Adedoyin and Zakari (2020) suggest that while economic policy uncertainty may enhance environmental sustainability in the short term, it can result in long-term ecological degradation.
2.2.2 Gross domestic product per capita
Recent studies have explored the connection between a country's ecological footprint and its economic growth, as indicated by GDP (Chu & Le, 2022) Research has shown a clear link between economic development and environmental degradation (Raihan & Tuspekova, 2022), primarily through the increase in ecological footprints An analysis by Magazzino (2023) further confirmed a positive relationship between real GDP and environmental degradation, highlighting the impact of economic expansion on ecological health.
Trade openness can affect the ecological footprint in multiple ways, and this impact varies depending on the level of development and industrialization of a country (Destek
In developed countries, increased trade openness typically results in positive technical advancements, as it facilitates the import of advanced technologies and cleaner production methods that enhance environmental quality Conversely, in developing nations, trade openness may result in the influx of inexpensive yet polluting technologies aimed at fostering economic growth, ultimately leading to a decline in environmental quality.
Foreign Direct Investment (FDI) has a dual impact on economies, positively influencing economic growth while negatively affecting the environment (Zafar et al., 2019) When FDI is allocated to polluting sectors such as manufacturing, services, and technology, it harms ecological conditions In contrast, investments in clean sectors contribute positively to environmental health Qamruzzaman (2022) highlights that while FDI fosters economic development, it often leads to environmental degradation through investments in polluting industries Additionally, Doytch (2020) notes that FDI in developed countries amplifies the ecological footprint linked to consumption, whereas in developing nations, it increases the ecological footprint related to production.
Hassan, Xia, et al (2019) defined natural resources as a combination of oil, gas, coal, minerals, and forestry resources, highlighting their significant impact on the ecological footprint and environmental quality degradation Their study identified a two-way correlation where natural resources contribute to an increase in the ecological footprint (EFP), thereby worsening environmental quality, while also suggesting that natural resources can reduce EFP, positively influencing environmental quality Conversely, Ahmed et al (2020) found that, in the long run, natural resources tend to increase the ecological footprint.
Agriculture plays a crucial role in the economy by providing raw materials, ensuring food supply, enhancing competitiveness, and creating jobs (Gokmenoglu et al., 2019) Key agricultural activities, such as fishing, forestry, and hunting, contribute significantly to global CO2 emissions, accounting for approximately 20% of total emissions (Pellegrini et al., 2016) These practices exacerbate environmental issues, leading to increased water, land, and carbon emissions (Pata, 2021) Intensive farming and land use changes further drive resource consumption and environmental degradation, resulting in a larger ecological footprint (Hassan, Baloch, et al., 2019; Pala, 2021) The expansion of agriculture, along with associated pressures like deforestation, soil erosion, and water pollution, are major contributors to this ecological footprint.
Charfeddine and Mrabet (2017) highlighted the relationship between life expectancy and environmental degradation, suggesting that enhancing environmental quality can lead to longer lifespans As individuals seek to extend their lives and invest in sustainable practices, such as green products, this can reduce ecological footprints and positively influence life expectancy indices However, rising life expectancy and population growth necessitate job creation, which in turn drives economic growth in developed nations This increased demand for goods and food can lead to heightened production levels, ultimately resulting in adverse effects on the environment, including challenges related to nature conservation and pollution (Pata et al., 2023).
Fig 1 Theoretical Framework depicting the Impact of Energy-related Uncertainty
Method
Previous research primarily utilized time series data (Dai et al., 2023; Ulucak & Lin, 2017) and panel data (Ozokcu & Ozdemir, 2017; Qing et al., 2024) for regression analysis In studies focusing on time series data, the ARDL regression model was predominantly used to address the challenges associated with incomplete time series data.
Previous studies have employed various methods to analyze EUI (Ahmed et al., 2021; Shanna et al., 2021) In the context of panel data, most Ordinary Least Squares (OLS) methods focus on addressing imbalances in ordinary regression models while maintaining consistent estimation results This approach is essential for examining relationships and forecasting future trends of the variables involved (Charfeddine).
The ecological footprint serves as a comprehensive indicator of environmental degradation, surpassing traditional measures like CO2 emissions (Aydin et al., 2019; Dcstck & Sarkodic, 2019; Sarkodic & Strczov, 2018) Numerous studies have explored the endogenous relationship between environmental pollution and economic growth through the lens of the Solow model (Chaabouni et al., 2016; Shahbaz et al., 2019).
Most research focuses on the Environmental Kuznets Curve (EKC) theory, which examines the link between environmental quality and GDP per capita (Ansari et al., 2020; Ozturk et al., 2023) Additionally, other studies test the EKC hypothesis by analyzing factors such as the rate of forest area destruction (Cuaresma & Heger, 2019) and water pollution (Muyibi et al., 2008).
Data
Empirical research examining the link between energy insecurity and natural resources has utilized diverse data sources at various levels Notably, studies by Balsalobre-Lorente, Nur, et al (2023) and Sharma et al (2021) predominantly rely on ecological footprint data sourced from the Footprint Network.
Economic policy uncertainly - EPU (Jiao et al., 2022; Zhang et al., 2023) is a measure of the level of uncertainty and ambiguity associated with economic policy.
Gross Domestic Product (GDP) represents the total value of goods and services produced within an economy (Amer et al., 2022; Jorgenson & Clark, 2011; Ulucak & Khan, 2020) Research indicates that environmental pollution can be assessed using various indicators, with CO2, SO2, CH4, and NOx emissions commonly utilized in previous studies (Culjkovic, 2018; Chaabouni et al., 2016; Solarin et al., 2019) Furthermore, real GDP per capita is frequently employed as a measure of economic development (Altintaậ & Kassouri, 2020; Doytch, 2020), while foreign direct investment (FDI) per capita is also considered a significant factor (Doytch, 2020; Sun et al., 2022).
The NR index, as discussed by Hassan, Xia, et al (2019) and Salari et al (2021), along with average life expectancy (LIFE) highlighted by Shanna et al (2021), are critical indicators of economic and health performance These metrics are compiled from the World Bank Indicators database, providing valuable insights into global development trends.
Findings
A study by Jiao et al (2022) indicates that Economic Policy Uncertainty (EPU) negatively affects the growth of industrial value added and energy production while positively influencing the Ecological Footprint (EFP) EPU restricts investments in renewable energy and research and development, leading to environmental degradation Conversely, Green Policy Responses (GPR) reduce EPU, energy production, and EFP, thereby lessening environmental impacts (Zhao et al., 2021) In the short term, EPU from China's WTO accession initially improves EFP, but its adverse effects diminish over time Additionally, financial crises and geopolitical events negatively impact EFP (Wang et al., 2013), though heightened environmental awareness and China's emission targets help alleviate this negative effect.
Research indicates that renewable energy consumption significantly impacts the ecological footprint (EFP), highlighting the risks of environmental unsustainability in current economic growth models (Sharma et al., 2021) Factors such as increasing population density and life expectancy exert negative pressure on ecosystems, underscoring the need for effective policies that promote sustainable development Balsalobre-Lorente, Topaloglu, et al (2023) reveal a complex interplay between financial development, environmental policy, and corruption perception, all of which contribute to reducing the ecological footprint Conversely, foreign direct investment and trade openness are shown to increase the ecological footprint, illustrating the environmental-economic feedback effect in APEC countries The study also identifies a two-way causal relationship between these factors and the ecological footprint.
Kuhn et al (2020) demonstrate that land use for production adversely affects ecosystems and contributes to a larger ecological footprint As the population grows, the rising demand for housing results in resource overexploitation and intensified land use.
A study by Baabou et al (2017) revealed significant variations in the Ecological Footprint (EF) across 19 coastal cities in the Mediterranean, with Valletta, Athens, and Genoa exhibiting the highest per capita EF This increased footprint correlates with environmental sustainability policies influenced by factors such as disposable income, infrastructure, and cultural habits Additionally, the research indicated that high-income countries tend to have a larger EF compared to low- and middle-income countries, primarily driven by the costs associated with food and land.
A study by Ozturk et al (2016) reveals that the ecological footprint adversely affects trade openness, urbanization, energy consumption, and tourism GDP, resulting in environmental resource degradation It highlights that high-income countries tend to have a larger ecological footprint compared to low-income countries, largely due to the negative effects of environmental protection policies on the populace Conversely, middle- and high-income nations benefit from various factors that positively influence their ecological footprint, mitigate energy insecurity, and consequently support GDP growth and economic development.
Research by Qureshi et al (2019) indicates that while tourism growth correlates with an increased ecological footprint, its effect on air quality remains ambiguous Additionally, trade liberalization policies can effectively lower emissions, but it is crucial that these policies align with biodiversity goals to prevent harm to natural environments and ecological resources in various countries.
A recent study by Qing et al (2024) highlights the significant interaction between natural resources (NR), technological development (TECH), forest area (FOR), and renewable energy (REC) use in South Asia, emphasizing their collective impact on the region's Ecological Footprint (EFP) Ineffective management of NR, including forest degradation and overexploitation of REC, contributes to an increased EFP and adverse environmental consequences, which have become pressing concerns in UN discussions Conversely, the research indicates that advancements in TECH can help industries minimize the use of harmful fertilizers and pesticides, while REC sources like solar and wind energy reduce dependence on fossil fuels and lower greenhouse gas emissions Additionally, FOR plays a crucial role in carbon storage and provides renewable energy through biomass and biogas, positioning TECH, REC, and FOR as vital factors in mitigating environmental harm and decreasing EFP in South Asia.
Previous studies, including Bommer (1999) and Ozturk et al (2023), have examined how GDP per capita, energy use, financial development, and FDI affect the ecological footprint of South Asian economies The findings indicate that energy consumption, heavily reliant on non-renewable sources, contributes to a high ecological footprint in the region Conversely, financial development enhances environmental efficiency as the financial sector supports green initiatives, while energy use declines However, FDI tends to increase the ecological footprint due to insufficient environmental regulations, despite its role in addressing financial needs and economic growth Shukla et al (2017) highlight that renewable energy projects positively impact the environment by reducing greenhouse gas emissions, and in South Asia, such initiatives can attract investment, ensure energy security, foster technological research, and support stable economic development.
A study by Khan et al (2022) highlights the significant negative effects of poverty and income inequality on the ecological footprint (EFP) in developing Asian countries Rising poverty levels correlate with a decline in environmental quality, as indicated by the ecological footprint Furthermore, efforts to boost economic growth and industrialization to alleviate poverty can inadvertently harm the environment The large population of impoverished individuals in these regions tends to overconsume natural resources, such as food, water, and energy, further exacerbating environmental degradation.
Research gaps
Previous studies examining the link between ecological footprint and economic growth in Asian countries have highlighted significant insights but also reveal critical research gaps Notably, these studies fail to assess the impact of energy insecurity on natural resources and overlook the Environmental Kuznets Curve (EKC) and environmental pollution analysis Additionally, there is a lack of clarity regarding natural resource management and data collection methodologies, leading to instability in ecological footprint measurements While excessive CO2 emissions have been extensively discussed, the environmental damage stemming from energy insecurity remains unaddressed Furthermore, many studies neglect social variables, such as human development, which are vital for achieving sustainable development goals To enhance the analysis, there is a need for diverse environmental degradation criteria and the application of advanced econometric methods to explore nonlinear asymmetric relationships.
Contribute
This study employs ecological footprint data from the Global Footprint Network, energy market instability index data from the Economic Policy Uncertainty portal, and World Bank indicators to analyze the influence of energy-related uncertainty on natural resource governance across countries By constructing two indexes and incorporating six control variables, the research addresses critical global environmental challenges at a macro level It introduces the EUĨ variable, offering a novel perspective on uncertainty and its implications for future events Analyzing data from 2002 to 2022 across 27 countries grappling with environmental management issues underscores the urgent need to mitigate the adverse effects of human activities on the environment Ultimately, the study provides empirical evidence of the detrimental impact of production activities and suggests actionable policies for effective environmental protection.
Methodology
Model specifications
This study, grounded in the research of , aims to assess the effects of uncertainty surrounding energy and ecological footprints through a proposed model: lnEFit = a + ^InEUIit + p2lnNRit + p3FDIit + PíAGRit + PsGDPpc.
This study analyzes the ecological footprint and energy-related uncertainty index by examining country-specific data over time Key variables include foreign direct investment (FDI), agricultural ratio (AGR), natural resource revenue (NR), and average life expectancy (LIFE) to enhance model accuracy Additionally, the relationship between per capita income and its squared value is estimated to provide deeper insights into these dynamics.
(GDPpc and GDPpc2) to test the hypothesis of the existence of the EKC curve The components of the model are specifically described in Table 1.
Natural logarithm of Energy-Related Economic Policy
EFP Natural logarithm of Ecological footprint
Share of net foreign direct investment
AGR Share of agriculture (%GDP)
GDPpc Income per capita (million USD/Year)
NR Natural resource rent (Billion USD)
World Bank IndicatorsWorld Bank IndicatorsWorld Bank IndicatorsWorld Bank Indicators
Data and samples
This study analyzes macro data from 27 developed countries, including Vietnam, from 2002 to 2021 to explore the relationship between energy uncertainty and ecological footprint It aims to verify the existence of the Environmental Kuznets Curve (EKC) while addressing data limitations.
To enhance the reliability of the regression findings, the study segments the overall sample into sub-samples based on continents, specifically Asia, Europe, and America Additionally, all macro variables are defined within the 1st and 99th percentiles to mitigate the influence of outliers on the study's outcomes.
Empirical result and discussion
Descriptive statistics
Summary statistics and pairwise correlation matrix.
Panel A Summary statistics of variables
Panel B Summary statistics of variables
Panel A, Table 2 provides descriptive statistics for all variables in the model, revealing that the ecological footprint index (biEF) has a mean of 7.062, with a range from 5.765 to 8.264 and a standard deviation of 0.569, indicating significant volatility across countries and years This volatility is visually represented in Fig 1, which also shows a general decreasing trend in ecological footprints over time in most nations Similarly, the energy and environmental impact index (InEUI) demonstrates comparable volatility, with a mean of 5.453, a range of 3.914 to 6.482, and a standard deviation of 0.433, reflecting the growing concern over energy and environmental issues Additionally, the data sample showcases a wide diversity among countries, as evidenced by per capita income (GDPpc) and natural resource revenue (NR), which exhibit minimum values of 0.435 and 0.04 and maximum values of 85.793 and 58035.161, respectively.
Fig 2 The growth of Ecological Footprint (constant 2002).
The pairwise correlation test results in Table 2, Panel B, reveal a statistically significant negative correlation between energy uncertainty (InEUl) and ecological footprint (InEF), suggesting that increased energy uncertainty may help reduce the ecological footprint in various countries Moreover, other control factors, such as natural resources (NR) and life expectancy (LIFE), also exhibit significant negative relationships with InEF In contrast, foreign direct investment (FDI) and agriculture (AGR) demonstrate a positive correlation with ecological footprint.
The net effect of energy-related uncertainty on ecological footprint
4.2.1 Perform a goodness-of-fit test for the regression model
The analysis of panel data from 24 countries, as shown in Table 3, reveals a statistically significant negative relationship between InEUl and InEF across three linear regression models: POLS, FEM, and REM The findings indicate a strong impact, with the FEM and REM models yielding similar results.
536 0.968 t-statistics are reported in parentheses.
***, ** and * denotes statistical significance at 0.1 %, I % and 5%, respectively.
Table 3 presents the goodness-of-fit test results for three regression models, indicating that both the LM and F tests reject the null hypothesis (H0) This suggests that the Random Effects Model (REM) and Fixed Effects Model (FEM) are more suitable than the Pooled Ordinary Least Squares (POLS) model Furthermore, the Hausman test results confirm that the FEM is more appropriate than the REM for the original data used in this study.
Table 3 indicates that all control factors in the model are statistically significant, with Foreign Direct Investment (FDI) and Agricultural share (AGR) positively impacting the ecological footprint in countries This correlation arises as increased investment fosters business expansion and a higher agricultural share leads to greater natural resource utilization, thereby exerting more pressure on the environment In contrast, Natural Resources (NR) and Life expectancy (LIFE) demonstrate a negative influence on the ecological footprint Additionally, the findings reveal an inverted U-shaped nonlinear relationship between per capita income and the ecological footprint.
4.2.2 The net effect of energy-related uncertainty'
The study employs a fixed effects regression model to examine the new relationship within specific contexts, utilizing smaller sub-samples for analysis As presented in Table 4, the regression outcomes for these sub-samples are displayed, with Columns 1-4 representing the divisions by Vietnam, Asia, Europe, and America, respectively.
Impact of energy-related uncertainty and natural resource governance by region
R-squared 0.5009 0.979 0.974 0.970 t-statistics are reported in parentheses.
***, **, and * denotes statistical significance at 0.1%, l%and5%, respectively.
Table 4 illustrates the regression model results derived from data across various continents, revealing notable similarities Specifically, an increase in energy source uncertainty correlates with a decrease in the ecological footprint The analysis indicates that the influence of this factor remains consistent across continents, as the variations in impact are minimal when compared to the overall sample Furthermore, additional variables such as agricultural share and the environmental Kuznets curve continue to show statistical significance within the regression model.
In Vietnam, the relationship between energy source uncertainty and ecological footprint mirrors global trends, where increased energy uncertainty leads to a larger ecological footprint and vice versa However, this impact is more pronounced in Vietnam compared to the global average and other regions, highlighting the significant environmental challenges faced by a rapidly urbanizing developing country.
The control factors listed in Column 1 of Table 4 are statistically insignificant, indicating that they do not influence the relationship between energy source uncertainty and ecological footprint in both the global context and specifically in Vietnam.
Research indicates that energy uncertainty adversely affects the ecological footprint of nations globally Over-investment in sustainable economic development can threaten the environment, and energy shocks may lead to a decline in a country's ecological footprint Despite this, economic growth remains a priority, particularly for developing nations like Vietnam, where Free Trade Agreements (FTAs) accelerate urbanization and industrialization This intensifies the link between energy uncertainty and ecological footprint, making immediate reductions in ecological impact challenging Countries may hesitate to transition from non-renewable to renewable energy sources to manage this state variable However, excessive reduction of the ecological footprint can negatively impact agricultural, forestry, and fishery land, as it often involves decreased exploitation of natural resources, which in turn affects market supply, employment, and income These findings align with previous studies (Saqib et al., 2023; Saqib et al., 2024; Adedoyin et al., 2021).
Foreign direct investment and a high agricultural share contribute to an increased ecological footprint due to expanded business activities and intensive resource use, leading to environmental pressure In contrast, higher recycling rates and living standards negatively impact the ecological footprint by reducing waste and promoting resource conservation While increased living standards can elevate consumption and waste, they often come with advanced technologies and policies that minimize pollution, aligning with findings from previous studies (Ulucak & Khan, 2020).
Conclusion
This study explores the influence of global energy uncertainty on natural resources, aiming to promote a green economy in developed countries Utilizing linear regression methods—POLS, FEM, and REM—on panel data from 27 developed nations, including Vietnam, over a 20-year period (2002-2021), the findings reveal that key model variables significantly affect natural resources Notably, there is an inverse relationship between energy uncertainty and the ecological footprint, indicating that increased energy uncertainty may positively reduce ecological footprints Additionally, natural resources and lifespan negatively impact ecological footprints, while foreign direct investment and agricultural share positively contribute to ecological footprint increases This suggests that heightened investment and agricultural demands can lead to resource depletion and environmental strain Interestingly, changes in income levels do not significantly influence the ecological footprint, highlighting the need for further research into this factor's role within the study's context.
The energy uncertainty index significantly contributes to reducing the ecological footprint, positively influencing natural resource management This highlights the crucial role of energy uncertainty in global changes concerning natural resources A comparison between developed countries and Vietnam reveals an inverse relationship between energy uncertainty and ecological footprint, with Vietnam experiencing a greater environmental impact This disparity is attributed to Vietnam's status as a rapidly urbanizing developing country.
Policy implications
Recent research highlights the significant impact of energy uncertainty on natural resources and ecological footprints, underscoring the urgent need for effective policies to promote a sustainable future.
Strengthening energy sustainability through investment in renewable sources such as wind, solar, and hydropower can significantly reduce energy uncertainty and ecological footprints Encouraging green investments by fostering favorable conditions for eco-friendly projects will aid in protecting natural resources Additionally, promoting sustainable agriculture by minimizing chemical usage and embracing high technology is crucial Improving energy efficiency and resource conservation through energy-saving solutions and green building practices is essential Raising public awareness and educating communities about the importance of natural resource protection and sustainable development will drive grassroots change Lastly, international and regional cooperation in sharing technology, experience, and financial support is vital for assisting developing countries, like Vietnam, in transitioning to a green and sustainable economy By comprehensively implementing these strategies, we can pave the way for a future characterized by reduced energy uncertainty and sustainable resource use.
Limitations and future directions
Research on energy uncertainty and natural resource governance in developed countries faces significant limitations due to the absence of detailed and updated data While some nations offer usable information, inconsistencies across countries hinder effective assessment and comparison Additionally, the neglect of economic fluctuations during the observation period compromises the accuracy of analyses, as it overlooks the influence of economic factors on energy uncertainty and governance effectiveness This data deficiency not only diminishes the research's value but also complicates the ability of policymakers and managers to set priorities and implement effective strategies Therefore, there is an urgent need to enhance data collection and analysis methods, while expanding research to encompass broader economic and social factors, to achieve a more comprehensive understanding of energy dynamics and resource governance in developed nations.
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Hausman Test Chi-square p-value
GDPpc GDPpc2 LIFE AGR NR FD1 InEUI 33.53 22.43 4.17 3.67 1.20 1.08 1.05
Country Region Asian Europe America