CO2 Emissions In Pakistan Research Articles

Asymmetric Effects of Corruption on CO2 Emissions in Pakistan: The Role of Human Capital and Foreign Direct Investment

This study aims to examine the relationship between corruption, human capital, FDI, GDP and CO2 emissions in Pakistan from 1996 to 2022. This study utilized the NARDL approach to estimate the asymmetric association. The empirical findings revealed that corruption in positive shocks enhances CO2 emissions while, in negative shocks, it mitigates CO2 emissions. Human capital and FDI played beneficial roles in decreasing CO2 emissions. On the other hand, GDP exacerbated CO2.The results highlight the importance of stringent accountability measures to stop more environmental damage. The study recommends that to effectively tackle both corruption and environmental challenges, there is a crucial need to invest in human capital. Strengthening human capital can help enhance accountability, reduce corruption, and promote sustainable environmental practices.

Economic Growth, Industrialization, and CO2 Emissions in Pakistan: Insights from ARDL Modeling

This study explores how industrialization, economic growth (measured by GDP per capita), and CO? emissions have interacted in Pakistan over nearly five decades, from 1974 to 2022. It also considers the influence of population growth and foreign direct investment (FDI) on this relationship. To analyze the data, the ARDL model was used, ensuring the reliability of the results by confirming stationarity with the Augmented Dickey-Fuller (ADF) test. The results showed that in the long run, a 1% increase in GDP per capita and FDI inflows results in respective increases in CO? emissions of 0.33% and 0.061%. Still, a 1% rise in industrial activity lowers CO? emissions by 0.34%. In the short run, a 1% rise in GDP per capita and FDI reduces CO? emissions by 0.21% and 0.020%, respectively. Conversely, a 1% increase in industrial activity causes emissions of 0.29%. These findings are in line with the Environmental Kuznets Curve (EKC) theory, which holds that CO? emissions initially rises when a nation industrializes but as the technology advances and more rigorous rules are followed, the level of CO? emissions decreases. Based on these results, policies emphasizing investments in renewable energy, strict environmental rules enforced, and support of clean technologies and sustainable industrial practices are suggested.

The longitudinal relationship between tourism, electricity consumption, and CO2 emissions

The objective of the study is to determine the electricity use, and tourism industry environmental impacts, and increase in CO2 emissions in Pakistan. What are the linkages of foreign direct investment, intercountryal trade, gross domestict product, and CO2 emissions. The study has applied the Autoregressive distributed lag (ARDL) method to analysis the data set from 1985 to 2023. The robustness test is applied using Dynamic Ordinary Least Square (DOLS), and Fully modified ordinary least squares (FMOLS). The results reveal that the increase in the electricity use, and tourism industry has significant negative impacts on CO2 emissions in both short- and long-run. The increase in intercountry trade effects the Domestic Product growth (GDP) growth and causes to increase in use of fossil fuels, which are the major source of CO2 emissions. The increase in foreign direct investment (FDI) increase the GDP growth, and FDI also increase the CO2 emissions in Pakistan. The results suggests that the incresae in the renewal energy consumption for the electricity production and transportation can help to decrease the CO2 emissions in Pakistan.

An Historical Review of International Trade and CO2 Emissions in Pakistan: A Quantitative

Environmental protection has become an international issue, reflecting widespread concern about environmental degradation. Researchers have emphasized the importance of the environment in trade policy debates. The focus of this study is to explore the relationship that is present between trade openness and the quality of environment in Pakistan. This research investigates the famous nexus between trade and the environment. The study uses data from 1990-2021 for analysis. The emissions of CO2 (Metric tons per capita) serves as the proxy of Environmental quality as the dependent variable. Empirical analysis is done by applying Autoregressive Distributed Lag (ARDL) time series econometric technique. Trade openness is the main independent variable, whereas population, foreign direct investment, and non-renewable energy are used as control factors. The results obtained from co-integration test prove a long term relationship between CO2 emissions and trade openness. A study indicated that increased commercial openness leads to an increase in CO2 emissions, which promotes environmental degradation in Pakistan. It is proposed that trade policies take environmental protection into account.

Modeling and forecasting carbon dioxide emission in Pakistan using a hybrid combination of regression and time series models

Carbon dioxide (CO2) emissions continue to rise globally despite efforts to combat climate change. Energy industry emissions are a pressing global issue, causing devastating impacts. Hence, it is vital to accurately and efficiently forecast CO2 emissions. Thus, this study comprehensively analyzes forecasting CO2 emissions by comparing various hybrid combinations of regression and time series methods to explore the CO2 emissions in Pakistan. First, divide the yearly time series of CO2 emissions into the long-run curve trend series and the residual subseries. The long-run curve trend subseries is modeled using parametric and nonparametric regression methods, while various standard time series models are used to forecast the residual subseries. However, the forecasts of each subseries will be combined to obtain the final forecast of CO2 emissions. This work used four different accuracy mean errors, a statistical test, and a graphical analysis as performance measures to evaluate the proposed hybrid forecasting technique. The findings confirmed that the proposed hybrid combination forecasting technique is highly accurate and efficient in forecasting CO2 emissions. Likewise, according to the proposed final optimal hybrid combination forecasting model, Pakistan's per capita CO2 emissions will be 1.130215 metric tons in 2030. Pakistan's escalating emission trend signals that creative solutions must be implemented to curb it. Thus, the government must price carbon footprints, regulate electricity from zero-carbon sources, reduce population, encourage afforestation in densely populated areas, adopt clean technology, and fund research.

Asymmetric impacts of economic factors on CO2 emissions in Pakistan: evidence from the NARDL model

Asymmetric impacts of economic factors on CO2 emissions in Pakistan: evidence from the NARDL model

Nuclear energy, economic growth and CO2 emissions in Pakistan: Evidence from extended STRIPAT model

Pakistan is a developing country whose maximum amount of mixed energy is provided by electricity, oil, coal, and gas. The study objective is to analyze the six major social factors to describe the significance of nuclear energy and CO2 emissions at the decisive point coming from income, trade, energy, and urbanization. This study has tried to analyze the impact of different factors (i.e., fossil energy, GDP per capita, overall population, urban population, and merchandise trade) on Pakistan's CO2 emissions using the extended STRIPAT model from 1986 to 2021. Ridge regression has been applied to analyze the parameters due to the multicollinearity problem in the data. The results show that (i) all the factors show significant results on carbon emissions; (ii) population and energy factors are the huge contributors to raising CO2 emissions by 0.15% and 0.16%; however, merchandise and GDP per capita are the least contributing factors by 0.12% and 0.13% due to import/export and income level in Pakistan, and (iii) nuclear energy and substitute overall show a prominent and growing impact on CO2 emissions by 0.16% and 0.15% in Pakistan. Finally, empirical results have wider applications for energy-saving, energy substitution, capital investment, and CO2 emissions mitigation policies in developing countries. Moreover, by investigating renewable energy technologies and renewable energy sources, insights are provided on future CO2 emissions reduction.

Modeling the impacts of changes in nuclear energy, natural gas, and coal in the environment through the novel DARDL approach

There is no doubt that energy consumption and production are the primary sources of greenhouse gases that contribute to climate change and global warming. It will be extremely helpful to develop policies to reduce carbon dioxide emissions by analyzing and estimating the factors responsible for these harmful gases. Against this background, the purpose of this study is to perform an analysis of energy services at a disaggregated level in the environment using a novel methodology called Dynamic Autoregressive Distributed Lag (DARDL) for Pakistan utilizing time series data from 1975 to 2021. Further robustness check is performed by Kernel-based regularized least squares (KRLS). Results show that (i) energy indicators and CO2 emissions are cointegrated; (ii) there is a statistically significant effect of nuclear, hydro, natural gas, oil, and coal energy use on CO2 emissions; (iii) nuclear energy reduces CO2 emissions; (iv) Nuclear energy dwindles CO2 emissions to a great extent when a positive shock is applied to it, even if it is 300%; (v) The use of hydro energy also declines CO2 emissions; (vi) Further, CO2 emissions increases dramatically with positive shocks to coal, even if they are 25 %; and, the robustness of the results is verified through KRLS method. This implies that energy consumption is a significant determinant of CO2 emissions in Pakistan, so efforts to reduce CO2 emissions should be considered in order to ensure a sustainable future.

Towards the goal of going green: Do green growth and innovation matter for environmental sustainability in Pakistan

Climate change has become a more pressing issue as time goes on, the role of green growth and green innovation emerges as a driving force for cleaner economic growth and a healthy environment by reducing environmental contamination. Environmental pollution is influenced by a wide variety of factors, as evidenced by numerous research studies. The impact of green growth and green innovation, as well as ICT on CO2 emissions has not been adequately examined in these research studies. This study highlights the importance of green growth (GG) and green innovation (GIN) for sustainable development. Our study aims to fill the gap by investigating how green growth impacts CO2 emissions in Pakistan, specifically in light of green innovations and ICT. A key innovation of this research is its incorporation of ICT interaction with green growth and green innovation. The results from augmented ARDL analysis constitute that green growth and green innovation significantly contribute to improving environmental sustainability in Pakistan. But in contrast, ICT shows a significant positive relationship with CO2 emissions. Similarly, the interaction between GG*ICT upsurge CO2 emissions, however, the role of the interaction term GIN*ICT is positive in enhancing environmental quality. As a result, policymakers and regulators should focus on promoting a green growth agenda and green innovation to mitigate CO2 emissions and achieve sustainable development goals.

Effectiveness of energy depletion, green growth, and technological cooperation grants on CO2 emissions in Pakistan's perspective

According to Nationally Determined Contribution (NDC), Pakistan proposed to set a very ambitious conditional objective of an overall 50 % reduction in anticipated emissions by 2030, with 15 % coming from domestic resources and 35 % contingent on international grant financing, which would entail USD 101 billion just for the energy transition. Due to this consideration, the current study examines the impact of energy depletion, green growth, technological cooperation grants, and labor force on CO2 emissions in Pakistan for 1990 to 2020. This research used the STIRPAT framework and novel dynamic ARDL techniques. Additionally, a robustness check is also carried out using Kernel-based regularized least squares (KRLS) and the Granger causality approach is utilized to establish cause-effect relationships. The findings indicate that energy depletion leads to environmental contamination in the long run. In contrast, Green growth is reducing environmental contaminations in the long run. Furthermore, we found that technological cooperation grants also decline environmental contamination in the short run. Likewise, the Labor force dwindles CO2 emissions in the long run. According to Granger causality, there is bidirectional causality between GG↔CO2, and TCG ↔CO2, while there is one-way causality between END→CO2 and CO → LF. The findings show that policymakers should emphasize on the transition to green growth with extensive investment in technological innovations, so the country can achieve its CO2 reduction targets.

Analysis of energy-related CO2 emissions in Pakistan: carbon source and carbon damage decomposition analysis.

Carbon dioxide emissions (CO2es) are presently a hot topic of worldwide concern. It is of great significance for lessening CO2es to wholly understand the transformation pattern of CO2es among countries, industries, and the main factors (i.e., emission effect, energy intensity, economic development, population size, carbon per unit of land, land per capita, and environmental impact per capita effects) influencing CO2es. Thus, to mitigate the country's CO2es efficiently, it is necessary to determine the driving factors of its emissions and damage variations. For this, we use the logarithmic mean Divisia index method. This research decomposes the major two dimensions, such as carbon sources and carbon damage variations from 1986 to 2020, into eight factors. The results show that Pakistan's CO2es increased continuously during the period, with an average annual growth rate of 4.76%. Growing the country's CO2es over 1986-2020, the key influencing factors are economic development, population, and land, while energy intensity and emission factors are the main forces in mitigating CO2es. The carbon source and carbon damage dimensions reached 68.75 Mt and 208.56 Mt, respectively, which led to a rise in CO2e. The entire set of factors is averagely moving around the major outcomes that provide significant policy measures. Finally, to efficiently reduce CO2e, Pakistan should concentrate on specific industrial paths and implement challenging, comprehensive governance to attain a low-carbon chain throughout the process. Thus, based on empirical results, this research put forward policy suggestions for cleaner production to reduce CO2 emissions further, and environmental policies must be tailored to local conditions.

An Asymmetric Analysis of Renewable Energy in Mitigating Carbon Emissions in Pakistan

To achieve sustainable growth, energy is incumbent because all modern production is based on it. Unfortunately, about 80% of the global population uses polluted energy, adversely damaging the environment. The present study asses the asymmetric role of renewable energy in the mitigation of CO2 emissions in Pakistan. The Non-linear ARDL econometric approach is used to estimate the empirical results of the time series data from 1980 to 2020. The study found that positive change in renewable energy adversely declines CO2 emissions while negative change increases CO2 emissions. Additionally, the HDI and trade openness lessens CO2 emissions, while urbanization increases CO2 emissions. The study recommends that Pakistan should promote eco-friendly consumption patterns. Pakistan should focus on promoting renewable energy resources, which will help combat the upsurge in industrial and housing carbon dioxide emissions.

Analyzing the Impact of Urbanization on Carbon Dioxide Emissions: Fresh Evidence from Pakistan

Over several decades, unplanned urbanization is increasing CO2 emissions due to higher energy demand from industrial activities, transportation, and waste management. The present study assesses the link between urbanization and CO2 emissions in Pakistan from 1985 to 2020 by controlling FDI, access to electricity, and institution quality. The empirical results are estimated by using the ARDL approach while causality is extracted through the Granger Causality test. The empirical findings depict that urbanization leads to CO2 emissions. Furthermore, institutional quality declines CO2 emissions, while FDI and access to electricity significantly increase CO2 emissions. The Granger Causality results indicate a bidirectional causality between electricity access and CO2 emissions. At the same time, CO2 emissions and urbanization show unidirectional causality. The study suggests that Pakistan needs to promote an environment-friendly energy consumption pattern

Factors affecting electric vehicle acceptance, energy demand and CO2 emissions in Pakistan

This work aims to investigate the factors accelerating electric vehicle (EV) acceptance at the consumer end in Pakistan and analyzes the implications for policymakers for a fast-track EV transition. The study further investigates the high EV penetration scenario resulting from the technology acceptance model (TAM's 80% EV) and its impact on energy demand and CO2 emissions. The study design used a quantitative analysis method with the survey as an instrument for data collection regarding EV acceptance. The model under investigation was adapted from the famous Technology-Acceptance Models (TAMs) and modified with other significant predictors evidenced in the literature. Correlation and stepwise regression were performed with a multicollinearity check for model hypothesis testing. Out of six predictors, only four factors were significant in accelerating the EV transition. Financial policies were found to be highly significant, followed by environmental concern, facilitating conditions and perceived ease of use. The research then used exponential smoothing forecasts for transport demand and developed an EV penetration scenario based on modified TAM results. The results highlight the significant increase in transport demand and the opportunity for Pakistan to limit passenger transport emissions to 36.6 ​MT instead of 61.6 ​MT by 2040.

Analyzing the role of green innovation and public-private partnerships in achieving sustainable development goals: a novel policy framework.

The environment's quality is the cornerstone for every country's long-term growth. Pakistan, like other countries, is embracing modern, efficient technologies to build a sustainable environment following the SDGs. In this situation, policymakers and experts have emphasized more on environmental factors. To do this, the study explores the impact of green innovation (GI), public-private partnerships in energy (PPP), energy use (EU), economic development (ED), and power prices (PP) on CO2 emissions in Pakistan from 1980 to 2019. The research uses a novel econometric technique for estimating environmental factors, notably the dynamic autoregressive distributed lag simulations (ARDLS) model and spectral frequency domain causality (SFDC), to examine positive and negative shocks for the prediction of the short-, medium-, and long-run impact of selected determinants, respectively. Additionally, robustness checks were performed using the fully modified OLS (FMOLS), dynamic OLS (DOLS), and canonical cointegrating regression (CCR) estimations. The short and long-term empirical findings indicate that GI lowers emissions; nevertheless, PPP, EU, and ED have a significant impact on emissions in the short run, while the EU increases emissions in the long run. PP, on the other hand, reduces emissions both short and long-term. The FMOLS, DOLS, and CCR estimations indicate significant discoveries. Additionally, the SFDC finding supports the long, medium, and short-term causation theories. This research advocates green innovation for a greener manufacturing process and PPP investment in renewable energy. In addition, the Pakistani government considers these variables while designing a comprehensive protracted environmental plan to meet SDGs 7 and 13.

The asymmetric impact of public–private partnership investment in energy on CO2 emissions in Pakistan

The present study investigates the effect of public–private partnership investment in energy and renewable energy consumption on carbon dioxide (CO2) emissions, taking into account the critical role of economic growth and trade openness in Pakistan from 1992 to 2019. The linear and nonlinear autoregressive distributed lag models are employed to check the co-integration link between dependent and independent variables, further estimate short-run and long-run associations, and examine the symmetric and asymmetric effects of public–private partnership investment in energy on CO2 emissions in Pakistan. The empirical findings show that public–private partnership investment in energy reduces environmental quality by increasing CO2 emissions. Similarly, economic development and trade openness harms the atmosphere by raising CO2 emissions. On the other hand, renewable energy consumption significantly negatively affects CO2 emissions. In addition, the findings also authenticate the asymmetric link between public–private partnership investment in energy and the environment, as CO2 emissions are caused mainly by positive shocks in public–private partnership investment in energy in the short and long run. This study proposes financing renewable energy projects through public–private partnership is needed for an environmentally friendly future.

The Impact of Financial Sector Development on Environmental Degradation (Carbon Dioxide Emission) in Pakistan

The main purpose of this research article is to determine the impact of financial sector development on environmental degradation in Pakistan. The study used the time series data of the financial sector development on environmental degradation (CO2 emission) in Pakistan during the period of 1974-2018. Due to the nature of the times series data, the Augmented Dicky Fuller test is used to detect the level of stationarity in the data. Mixed orders of the stationarity in the data are reported, and the Auto Regressive Distributed Lag model is the best technique to provide efficient results. The ADF result clearly shows that the variables except for Y, Y2, and Y3 are stationarity in the first order, while the mentioned variables are stationarity at a level. And Trade openness is stationary at first difference. The bound test results (the F-statistic value is 5.208 that exceeded the values of upper bounds value, i.e., 3.28 at a 5% significance level. Therefore, the co-integrational relationship is confirmed for the model of the study at a 5% significance level. The model depicts the impact of Financial Sector Development on environmental degradation regarding CO2 emission. It was found that FSD negatively affected environmental degradation in Pakistan in both the long and short run during the period from 1974 to 2018. The impact of PG, EC and FDI is positive and statistically significant in the long run. The impact of TO on CO2 emission is negative and significant in the long run. On the other hand side, negative shock can produce harmful effects on the environment. A positive and significant relationship is reported regarding economic growth and CO2 emission. The impact of Population growth, Financial Development Index, Trade Openness, Energy Consumption, and Economic growth is also positive and significant to CO2 emission. It is quite evident from the detailed examination of the above model. This study concluded that financial sector development efficiently contributes to long-term and short-term environmental degradation. Financial sector development negatively and significantly affects environmental quality as measured by CO2. Therefore, it is concluded that the financial sector can be used as a policy tool to reduce CO2 emission in Pakistan based on the data set from 1974-2018.

Impact of subsectors of agriculture and economic growth on CO2 emissions in Pakistan: evidence from Environmental Kuznets Curve.

Modernization produces carbon dioxide (CO2) emissions but is also able to achieve sustainable agriculture growth by introducing the concept of renewable energy into the agriculture sector, and through this process reduce the CO2 emissions in the country. The main objective of this research is to check the environmental Kuznets curve hypothesis with CO2 emissions and economic development in renewable energy and agriculture subsectors such as fisheries and crop production in Pakistan. This study covers the time period 1984 to 2020. We have applied the autoregressive distribution lag (ARDL) bound test. The results indicate the existence of long-term association among all variables in the model. The result of co-integration in the short run shows a negative relationship between CO2 emissions and crop production in the current time period, and it shows a positive correlation with the first lag of CO2 emission, which means that current crop production reduces the CO2 emissions by 32% during a year, while in the lag period, it will increase in the short run. In the long run, a 1% increase in crop production will reduce the CO2 emission by 86%. Renewable energy shows a negative relation with CO2 emissions in the short run; a 1% increase in renewable energy will reduced the CO2 by 0.017%. Our results support the existence of the EKC hypothesis for Pakistan. In light of the findings, it is suggested that policy makers should focus more on renewable energy to decrease the level of CO2 as much as possible. Moreover, the government must provide subsidies for machines used for cropping and give special attention to subsectors such as livestock and fisheries.

The effect of gross domestic product, urbanization, trade openness, financial development, and renewable energy on CO2 emission.

The purpose of this study is to analyze the influence of GDP, urbanization, trade openness, financial development, and renewable energy consumption on CO2 emissions in Pakistan using yearly time series data from 1985 to 2018. The study utilized the cointegration technique and Granger causality for empirical estimation. The results of the study indicated that urbanization, financial development, and trade openness upsurge CO2 emission. Whereas using renewable energy resources is favorable for the environment and possesses negative relation with CO2 emission. All variables possess long-run relation with Co2 emission. Granger causality shows unidirectional causality from GDP and renewable energy to CO2 emission. The study contains insight for policymakers in Pakistan with beneficial policy recommendations to work toward a sustainable green environment.

Designing a clean environmental framework for Pakistan: analyzing the nonlinear impact of aggregate demand drivers on CO2 emissions.

Aggregate demand in every country is one of the main components of macroeconomics, and Pakistan is no exception. This paper uses a fresh econometric framework to analyze the nonlinear impact of aggregate demand drivers on CO2 emissions in Pakistan by using a nonlinear ARDL approach over the data period from 1975 to 2019. The linear findings reveal that consumption and government expenditure indicates deteriorating effects on carbon emissions in long run in Pakistan. However, nonlinear findings revealed that positive change in government expenditure and trade has positive effects on carbon emissions. The positive change in investment has a negative significant and meaningful effect on the environment in Pakistan and asymmetric findings are also country-specific. Therefore, this study offers a few important policy implications for theorists, academics, and policymakers of Pakistan as well developing economies.