Lag Approach Research Articles

Reevaluating energy progress: An in-depth policy framework of energy, urbanization, and economic development

Pakistan has challenging energy-related economic concerns, including accessibility, affordability, and sustainability, all of which significantly impact the country's economic development and growth prospects. This study seeks to uncover the intricate link between energy use, power costs, urbanization, alternative energy consumption, and economic development from 1970 to 2018. Utilizing the Autoregressive Distributed Lag (ARDL) approach, Frequency Domain Causality (FDC), and Innovative Accounting Approach (IAA), the research finds that energy use and urbanization positively impact economic development in the short and long term. Conversely, alternative energy consumption declines in the short run, while rising power costs negatively affect long-term economic development. FDC results indicate that rising power costs affect economic development in the short, medium, and long run, while urbanization has a long and short-term and energy use has a long- and medium-run impact on economic development in Pakistan. IAA aligns with ARDL and FDC hypotheses. This underscores the vital role of energy use and costs in economic activity, emphasizing the need for prudent urbanization and strategic alternative energy integration in long-term policy for Pakistan.

Analysis Of The Influence Of Domestic Investment, Foreign Direct Investment, Popu-lation, Crime Rate, And Unemployment Rate On Economic Growth In Deli Serdang Regency: ARDL Model Approach

The aim of development in a country or region is to improve the welfare and prosperity of society in a fair and equitable manner, one of which is by increasing sustainable economic growth. The main objective of this study is to analyze the effect of domestic investment, foreign investment, population, crime and unemployment on economic growth in Deli Serdang Regency. The data analysis method used is the Autoregressive Distributed Lag (ARDL) approach in the time series data model and the observation time span of this study starts from 2010 to 2021 where data interpolation will be carried out in quarterly. According to the results of the analysis, the variables domestic investment and foreign direct investment have a positive significant effect on economic growth. Meanwhile, the variables of population, crime and unemployment have a negative significant impact on economic growth in the long run. However, in the short run, the variables of direct investment, foreign investment, population and crime have a positive significant impact on economic growth. On the other hand, only the number of unemployed has a negative significant effect on economic growth. Based on the results of this study, it is appropriate for the Government of Deli Serdang Regency to optimize programs that are oriented towards increasing investment both domestic and foreign, suppressing the rate of population growth and the number of unemployed and maintaining regional security in the Deli Serdang Regency area.

Energy Transition and Poverty Alleviation in Light of Environmental and Economic Challenges: A Comparative Study in China and the European Union Region

This study aims to compare the effectiveness of renewable energy and circular economy practices in reducing environmental damage and poverty in China and the European Union (EU) by using the Autoregressive Distributed Lag (ARDL) approach and the Vector Error Correction Model (VECM) technique. Analyzing data from 1995 to 2022, we compared the effectiveness of these approaches in both regions. This study offers several fresh perspectives on the fight against environmental damage and poverty, differentiating itself from existing research in a few key ways. In fact, most studies focus on a single region’s approach to sustainability. However, this research directly compares China and the European Union (EU), highlighting how factors like economic structure and development stages influence the effectiveness of renewable energy and circular economy practices. Also, this study shows how renewable energy and circular practices can simultaneously tackle both environmental damage (emissions) and social issues (poverty). Our findings reveal that factors like poverty, fossil fuel reliance, economic growth, and international trade all contribute to rising carbon emissions in both China and the EU, though their influence varies. Interestingly, China experienced greater success in curbing emissions through solar power, circular economy measures, and wind power compared to the EU. Additionally, the impact of these strategies on poverty reduction differed significantly between the two regions. Based on these results, we recommend that policy makers in both regions develop tailored strategies for tackling carbon emissions and poverty. Prioritizing renewable energy sources and circular practices is key, as they can simultaneously reduce emissions and alleviate poverty. However, it is crucial to focus on approaches that work best in each specific region, considering social, economic, and environmental factors. This study suggests that a one-size-fits-all approach will not work for fighting climate change and poverty. While renewable energy and circular economies are effective, China saw greater success with solar and wind power compared to the EU. Policy makers need to design strategies specific to their region’s economic, social, and environmental context. Further research can refine these approaches, and public education is crucial to promote sustainable behavior and empower policy makers. It is also needed to refine and improve the implementation of these strategies. Finally, public awareness and education are essential to promote sustainable behavior and empower policy makers in their fight against climate change and poverty. This study highlights the importance of a region-specific approach to energy transition and poverty alleviation. By comparing China and the EU, we gain valuable insights into the effectiveness of different strategies in tackling these interconnected challenges. The findings provide valuable guidance for policy makers looking to create a more sustainable and equitable future.

Population, carbon dioxide emissions and renewable energy consumption nexus: New insights from Vietnam

This academic paper investigates the intricate relationships among population dynamics, carbon dioxide (CO2) emissions and renewable energy consumption in Vietnam. The study used the Autoregressive Distributed Lag approach and fixed panel data method to examine the nexus between population, CO2 emissions and renewable energy consumption in Vietnam. The data is collected at the World Bank from 2000 to 2023. As the nation undergoes rapid economic development and urbanization, understanding the nexus between population growth, environmental impact and the transition to renewable energy sources becomes crucial. The study employs a multidimensional analytical approach that integrates demographic trends, environmental science and energy economics to unveil novel evidence into the complex interplay of these factors. The significant findings indicate a positive trajectory in renewable energy consumption, with notable contributions from solar, wind and hydropower sources. Concurrently, population growth, particularly in urban centres, correlates with increased CO2 emissions, emphasizing the role of demographic shifts in environmental impact. Policy implications derived from these results underscore the need for integrated strategies. Targeted policies promoting renewable energy in urban centres, incentivizing cleaner industrial practices and fostering community engagement emerge as crucial avenues for sustainable development. In essence, this study contributes valuable insights into the dynamic relationships among population dynamics, CO2 emissions and renewable energy consumption in Vietnam, offering a foundation for evidence-based policymaking and guiding future research endeavours in sustainable development.

Toward a sustainable environment within the framework of carbon neutrality scenarios: Evidence from the novel Fourier‐NARDL approach

AbstractSustainable energy policies are directly proportional to countries' achievement of the Sustainable Development Goals (SDGs). Economies that want to achieve their 2030 and 2050 targets are looking for alternative energy sources until renewable energy sources mature. In this context, this study models the environmental quality of France, which is the leader in the use of nuclear energy in Europe, from a different perspective through nuclear energy technologies. This study empirically uses the novel Fourier asymmetric autoregressive distributed lag approach. It confirms that increases and decreases in nuclear technology have different effects on the load capacity factor within the framework of the load capacity curve (LCC) hypothesis. It also provides evidence for the existence of the LCC hypothesis and offers sustainable energy policies for France. The French government should allocate funds to cleaner energies instead of investing in nuclear energy technologies. Thus, the long‐term transition to a low‐carbon economy can be accelerated instead of short‐term targets. By eliminating nuclear energy, a severe burden on the French economy, infrastructure can be created for alternative energy sources. Finally, the French government can gain momentum in achieving SDGs 7 and 13 by withdrawing support from nuclear energy technologies.

BITCOIN PRICE AND CHINESE GREEN BONDS: EVIDENCE FROM THE QARDL METHOD

This article primally explores the short-term fluctuation and long-term implications of the international Bitcoin price (BP) on the Chinese green bond (GB) market, within the sample period of 2014:M10–2023:M07. Bitcoin is the most important cryptocurrency and has a carbon-intensive feature, and its price suffers from great volatility and is closely related to the green finance market. Meanwhile, although China is the largest bitcoin mining state, it is pursuing a dual carbon target, which promotes its green bond market’s development. Thus, it is valuable to investigate the influence of BP on GBs in China. Based on the quantile autoregressive distributed lag approach, this paper indicates that the positive and negative impacts of BP on the GB market are significant in the long-term but not apparent in the short-term. These results emphasize the importance for market participants to obtain a better understanding of how BP affects GB under various market circumstances. Implementing specific policies, such as regulatory mechanisms for Bitcoin trade, market-oriented reform for the bond market, and information disclosure, can alleviate shocks from BP and accelerate the development of the GB market.

Navigating the nexus: unraveling technological innovation, economic growth, trade openness, ICT, and CO2 emissions through symmetric and asymmetric analysis

In Malaysia’s rapid economic growth and industrialization, environmental degradation and carbon emissions pose significant challenges. As urbanization continues to rise, there is a growing recognition of the imperative to tackle CO2 emissions. Trade openness and globalization drive economic activity but also heighten environmental pressures, including CO2 emissions from transportation and industry. Information communication technology (ICT) usage, shaped by infrastructure and regulations, can either improve energy efficiency or increase energy consumption. The study examines the impacts of economic growth (EG), trade openness (TON), technological innovation (TIN), and ICT on CO2 emissions in Malaysia, using both symmetric and asymmetric methods from 1985 to 2021. While many studies have explored environmental degradation, focusing on CO2 emissions and ecological footprint indicators, only a limited number have delved into the combined impact of sustainable EG, TON, ICT, and TIN on Malaysia’s CO2 emissions. Notably, these studies have often neglected the utilization of both symmetric and asymmetric methodologies. Hence, this study employed auto-regressive distributed lag (ARDL) and non-linear ARDL approaches to investigate the dynamic effects of the studied variables. The key findings from the symmetric analysis demonstrate that EG, TON, and ICT together take part in the increase of CO2 emissions in both the short and long run. Particularly, technological innovation plays a significant role in reducing CO2 emissions in the short term through the adoption of cleaner technologies. However, the results of the NARDL bound test reveal asymmetric long-term consequences of technological innovation, economic growth, and ICT on CO2 emissions. The study underscores the need for CO2 reduction policies in Malaysia, advocating for measures, such as incentivizing cleaner technologies and upgrading energy infrastructure. It also recommends implementing carbon pricing mechanisms for production and trade, alongside awareness campaigns to foster behavioral changes aimed at reducing emissions.

Disentangling the effects of globalization on growth: Evidence from Ethiopia using an ARDL approach

Globalization is a complex phenomenon with far-reaching and multidimensional influences on national growth trajectories. Previous studies examining these effects have often relied on overly simplistic measures that mask heterogeneity across contexts. This paper aims to overcome such limitations by disentangling the impacts of different globalization dimensions on Ethiopia’s economic development over 1981–2021 using an autoregressive distributed lag (ARDL) approach in order to assess the long-term and short-term effects of Ethiopia’s economic growth rates and a comprehensive globalization index encompassing the economic, social, and political dimensions of globalization. Long-run and short-run relationships are estimated via ARDL to analyze these relationships in the context of factors like investment, workforce, trade, and capital stock, while the robustness of findings is ensured through dynamic ordinary least squares, fully modified ordinary least squares, and canonical cointegrating regression techniques. Key results indicate that overall and economic globalization exhibit negative long-term associations with growth when analyzing these relationships taking into account other factors, suggesting a need for a cautious, sequenced approach to integration to optimize benefits as local capacities develop over time. However, political globalization carries positive long-run effects. Social globalization displays no clear linkage. Short-run impacts also differ by dimension. Gross capital formation, trade openness, and capital stock remain consistently growth-enhancing. The negative correlation in the labor force likely reflects structural challenges. Robustness analyses substantiate these conclusions, enhancing confidence. Findings imply a cautious, sequenced approach to integration may optimize potential benefits as local adaptive capacities develop over time. This investigation’s tailored nature provides contextually grounded empirical knowledge with broader policy applications. More refinement of country-level analyses remains warranted to fully uncover globalization’s complexity. Overall, incremental global ties alone proved insufficient for development acceleration. Findings carry relevance for managing integration strategies towards inclusive, sustainable development nationally and beyond.

Harnessing artificial intelligence‐driven industrial robotics for sustainability: Insights from leading green economies

AbstractIn 2023, global temperatures witnessed an alarming escalation, reaching an unprecedented 1.46°C above preindustrial levels, marking it as the hottest year on record. Simultaneously, atmospheric carbon dioxide surpassed 420 ppm, exceeding a stability maintained for over 6000 years by more than double. This troubling surge in CO2 intensifies global warming, leading to an increased frequency of extreme weather events and contributing to 24% of global deaths attributed to environmental concerns. These alarming environmental challenges demand urgent attention and the implementation of innovative policies. Responding to this imperative, the study examines the impact of artificial intelligence‐based industrial robotics (AIIR) and other control variables such as green energy, green finance, and green energy investment on CO2 emissions in economies supporting green initiatives, including Canada, Denmark, China, Japan, New Zealand, Norway, Sweden, and Switzerland. Using monthly data from 2008 to 2021 and a novel nonlinear autoregressive distributed lag approach, the results indicate that AIIR significantly reduces CO2 emissions in the sample economies. Additionally, green energy, green finance, and green energy investment also significantly decrease CO2 emissions. The study's outcomes bear policy implications for decision‐makers in the sampled economies, offering tangible insights for effective environmental management.

The static and dynamic effects of oil rent on competitiveness: Application to the case of Saudi Arabia during the period 1970–2022

In this paper, we explore the static and dynamic effects of oil rent on competitiveness in Saudi Arabia’s economy during the period 1970–2022. In addition, we examined the short-run, strong and long-run relationships between exports and industry, inflation, energy use (oil rents) and agriculture using the Autoregressive Distributed Lag (ARDL) approach developed. The analysis showed that government spending will contribute to enhancing the competitive environment with a difference of one year. Moreover, the industry will contribute to increasing competitiveness for a positive relationship in the long term. The results stated that there is an insignificant relationship between competitiveness, inflation, and oil rents. The analysis also shows that inflation has a negative impact with statistical significance in the short term. In addition, the error correction model (ECM) coefficient is negative and has statistical significance at 0.76 at a 1% significant level, which indicates the existence of an error correction mechanism and thus the existence of a long-term relationship between the variables.

Decentralization, institutional quality, and carbon neutrality: Unraveling the nexus in China's pursuit of sustainable development

Achieving carbon neutrality is essential for environmental sustainability and should be pursued with minimal disruption to economic growth. China's recent commitment to carbon neutrality holds significant importance in current discussions. This study investigates strategies to achieve sustainable development goals (SDGs), emphasizing carbon neutrality. It also examines the long-term impacts and causality between fiscal decentralization and institutional quality in relation to carbon dioxide (CO2). emissions Utilizing the quantile autoregressive distributed lag (QARDL) approach and the Granger causality in quantiles, our findings reveal a statistically negative ECM parameter across all quantiles. This indicates a stable, long-term relationship between fiscal decentralization (FDC), institutional quality (INSQ), and CO2 emissions. The study verifies the presence of the Environmental Kuznets Curve (EKC) hypothesis in China across different quantiles. In the long run, fiscal decentralization seems to increase CO2 emissions, but robust institutional quality mitigates this impact. The Granger causality results highlight the intricate relationships among the variables. This research emphasizes the need for policymakers to bolster environmental protection and efficiency, ensuring fiscal decentralization benefits both environmental and economic agendas.

Taxation and Consumers’ Spending Patterns in Nigeria: An Autoregressive Distributed Lag and Error Correction Model Approach

This study evaluates the effects of personal income tax and consumption tax on the spending system of consumers in Nigeria. The autoregressive distributed lag (ARDL) model has been employed for the co-integration test. The research additionally employs the Error Correction Model (ECM) to assess the pace at which any divergence from the long run equilibrium can return to normal in the current period. The findings show that Value added tax has an insignificant impact on purchasing power of consumers in both the short and long intervals. However, personal income tax and exchange rate exert substantial positive effect on consumer spending power in the long run but not in the short run. At the 1% level, the ECT coefficient is shown to be significant and unfavourable. This demonstrates a pretty slow convergence rate, with the model pushing itself towards equilibrium by 37% each year. The consequence is that any disequilibrium caused by shocks from the previous year requires 37% adjustment speed to return to long-run equilibrium in the current year. There have been several studies on how consumption tax affects households’ welfare without considering the effects of income tax and ever fluctuating exchange rate alongside these whole scenarios. This study puts all of these issues into consideration and contributes meaningfully to the existing literature that personal income tax is an integral part of the factors that affect households’ spending capacity. The study recommends that proper tax policy to enhance consumers’ spending capacity.

Analyzing the dynamics of monetary policy and economic growth in Ethiopia: an autoregressive distributed lag (ARDL) approach

Numerous studies conducted by various scholars have aimed to ascertain the impact of monetary policy on economic growth. However, these empirical investigations have not reached a unanimous consensus. Therefore, this study analyzes the effect of monetary policy. To address this objective, this study employed ARDL and error correction model (ECM) based on annual data from 1993 to 2022. Granger causality test was also employed to check the direction of causal effects of one variable on the other variable. All required pre and post estimation tests were performed and verified that the model was statistically viable. The study revealed that, in the short run, deposit interest rate, reserve required amount, and open market operation have positive and statistically significant effects on real GDP growth of Ethiopia; however, money supply has negative and statistically significant effects on real GDP growth of Ethiopia. In the long run, money supply has positive and statistically significant effects on real GDP growth of Ethiopia; however, deposit interest rate and reserve required have negative and statistically significant effects on real GDP growth of Ethiopia. To sum up, in the short run, contractionary monetary policy was promising, and in the long run, expansionary monetary policy was favorable for economic growth. The Granger causality test result shows that there is bidirectional causality between monetary policy and economic growth; except there was a unidirectional relationship between deposit interest rate and economic growth. Ultimately, this research suggests the following policy recommendation: for short-term economic enhancement, it is advisable for the government to opt for a contractionary monetary policy rather than an expansionary one. On the other hand, for long-term economic improvement, an expansionary monetary policy is more favorable than a contractionary one.

Investigating the Economic Dynamics of Mobile Money in Post-Conflict Economies: Empirical Evidence from Somalia

This study investigates the economic dynamics of mobile money in Somalia, focusing on its transformative potential to impact economic activities in the short and long term. Adopting a quantitative research design, the study utilizes secondary data from 2010 to 2022. The autoregressive distributed lag (ARDL) approach is employed to assess the impact of mobile money on household consumption, real income, exports, and imports. Theoretical insights from the quantity theory of money further guide the examination of how mobile money influences economic activities. The findings demonstrate that mobile money has a significant positive effect on household consumption, real income, export growth, and import activity both in the short and long term. The study reveals that mobile money not only facilitates financial transactions but also enhances trade efficiency and promotes financial inclusion, thereby stimulating economic activities and growth. The study underscores the need for a supportive regulatory environment for mobile money services. It highlights that financial institutions and mobile money service providers should expand innovative services to include the unbanked population. By doing so, they can leverage mobile money to foster greater economic engagement and empowerment. Policymakers are encouraged to develop strategies that promote financial inclusion and economic development to harness the full potential of mobile money. This study enriches the existing literature by uniquely investigating the economic impacts of mobile money in Somalia, a post-conflict setting, thereby broadening the understanding of how financial technologies can catalyze economic activities and growth in similar contexts.

The influence of green financing on renewable energy progress in India's tourism sector

ABSTRACT This study employs the Autoregressive Distributed Lag (ARDL) approach to assess the impact of green funding on sustainable energy practices in India's tourist sector from 2000 to 2022. Results indicate that green bonds significantly and favourably influence long-term environmental sustainability, with negligible immediate effects. The Consumer Price Index adversely affects sustainability in both short and long terms. To enhance sustainability, recommended policy measures include increased regulatory supervision, transparent market information dissemination, eco-friendly fiscal policies, and the adoption of green building technologies. Supporting sustainable globalization, innovation, adaptation, and eco-tourism regionalism can greatly benefit India's tourism industry. The study offers valuable insights for policymakers aiming to promote environmental sustainability in the sector.

An Empirical Investigation of GDP, Industrialization, Population, Renewable Energy and CO2 Emission in Bangladesh: Bridging EKC-STIRPAT Models

This research paper explores the presence of the Environmental Kuznets Curve (EKC) in Bangladesh, delving into the intricate relationships among GDP, industrialization, renewable energy utilization, and CO2 emissions. Utilizing the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, our investigation spans the 1992 to 2021 timeframe, offering a comprehensive analysis of the interplay between these crucial factors in the context of Bangladesh's environmental sustainability. In this study, the F-bound test is utilized to establish the cointegration relationship among variables. And the short-run and long-run elasticity of explanatory variables is investigated by employing the Autoregressive Distributed Lag (ARDL) approach. This research also employed a pairwise granger causality test to explore the direction of causality between them. Empirical results prove the existence of a cointegration relationship among CO2 emission, GDP per capita, a quadratic form of GDP per capita, renewable energy, industrialization, and population. The findings provide strong support for the presence of the EKC in the case of Bangladesh. Besides that, significant inverse relationship was also obtained between CO2 emission and renewable energy consumption. Additionally, the study found the detrimental long-term effects of industrialization on the environment. The EKC hypothesis argues that Bangladesh can accomplish sustainable economic development. To attain the goal country should adopt appropriate government policies and ensure their implication. This study strongly advocates using sustainable energy sources and implementing regulations on pollutant industries.

Does energy transition reduce carbon inequality? A global analysis.

Energy transition from fossil fuels to renewables is instrumental in mitigating climate change. Low-income countries have a higher share of renewable energy in their total energy consumption than rich countries (WDI, 2023). Thus, it is imperative to examine the role of energy transition in affecting relative CO2 emissions between rich and poor sections of the societies across income groups of the countries. In this context, our study contributes by constructing the carbon inequality models with renewable and non-renewable energy consumption as prime explanatory variables separately for 114 countries over a data period 1990-2019. The models are estimated individually for high-middle-low-income countries by controlling for foreign direct investment (FDI), economic growth, and innovations. Starting with preliminary econometric operations, we employ the dynamic simulated panel autoregressive distributed lag approach and Driscoll-Kraay standard error regression for empirical investigation. We find that energy transition reduces carbon inequality globally. Innovation has a negative impact, economic growth has a positive impact on carbon inequality, and FDI has an asymmetric impact based on the income level of the countries. The crucial global policy implications are discussed.

STOCK MARKET DEVELOPMENT AND ECONOMIC GROWTH: AN ARDL APPROACH

This research project employs the Autoregressive Distributed Lag (ARDL) approach to investigate the intricate relationship between stock market development and economic growth. The primary objective is to systematically analyze the causal links and quantify the impact of key stock market indicators on economic growth, and vice versa. The methodology encompasses a thorough literature review to establish a theoretical framework, followed by the collection and examination of relevant data over a defined timeframe. Unit root tests and cointegration analysis are applied to assess the stationarity and long-term relationships between the variables. The ARDL model is then employed to estimate the dynamic interactions, considering lagged values of the indicators. Diagnostic tests are conducted to ensure the robustness of the findings. The project aims to contribute empirical insights into both short- and long-term dynamics, shedding light on the complex interplay between stock market development and economic growth. The results are expected to offer valuable implications for policymakers and researchers, providing evidence-based guidance for fostering sustainable economic development. Ultimately, this research seeks to advance our understanding of the mechanisms driving economic growth in the context of stock market development. Keywords: Stock Market Development, Economic Growth, ARDL Approach, Causal Relationship, Lagged Variables, Unit Root Tests, Cointegration Analysis, Empirical Insights, Sustainable Economic Development, Policy Implications.

Linkages between economic growth, health expenditures, education, and environment: dynamic analysis of Nigeria

The study comprehensively analyzed the nexus between economic growth, health expenditures, education, and the environment in Nigeria, using data obtained from Central bank of Nigeria and World Bank. By utilizing a robust dataset spanning from 1981 to 2021, the study employed autoregressive distributed lag (ARDL) approach to uncover intricate relationships. Results, both short-run and long-run analyses, reveal that health and education spending, and gross fixed capital formation positively correlated with economic growth. Conversely, the findings demonstrated that population growth and carbon dioxide emissions (CO2) exerted detrimental effects on economic growth due to the negative impact on the health of the working population. Additionally, the inverted U-shaped relationship between the macroeconomic footprint and income confirms the validity of Nigeria's Environmental Kuznets Curve (EKC) phenomenon. Lastly, the findings of this study hold important policy implications, emphasizing the need for technological advancements and innovative solutions to address the challenges associated with economic growth, health expenditures, education, and the environment in Nigeria. Policy measures promoting birth control through contraception and family planning should be embraced to effectively manage the country's rapidly growing population.

What implications do primary energy use, urban population agglomeration, and economic development rendered to Romania's environmental sustainability?

The energy sector plays a significant role in Romania's expanding economic and security agenda. The energy sector utilizes a diverse range of resources, such as renewable energy, nuclear power, coal, and natural gas. Traditionally, the primary sources of the country's energy have been coal and natural gas, while hydroelectricity and nuclear power have played supplementary roles. The present study's major purpose is to establish how primary energy consumption, fossil fuel consumption, urban population agglomeration, and economic growth affect CO2 emissions in Romania. The time series data covering 1990 to 2021 was analyzed using the symmetric Autoregressive Distributed Lag (ARDL) approach in conjunction with robust least squares technique. The study's findings demonstrated that in both the short and long run, variables such as fossil fuel consumption, urban population agglomeration, and economic growth had a positive influence on CO2 emissions. Primary energy consumption has a detrimental influence on environmental quality in Romania. Similarly, the results of the robust least squares technique show that distinct variables have specific effects on environmental quality. It particularly shows that fossil fuel consumption, urban population agglomeration, and economic growth have a positive effect on CO2 emissions. However, empirical evidence indicates that primary energy consumption has a negative impact on CO2 emissions. It is essential for the Romanian government to take more steps to successfully address the problem of environmental degradation inside the country, with the ultimate goal of increasing economic growth.