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The primary goal of this study was to examine the relationship between fossil fuel energy, electricity production from nuclear sources, renewable energy, CO 2 emissions, and economic growth in Pakistan. Data ranging from 1975 to 2019 were utilized, and the stationarity of this data was verified through the unit root testing. The dynamic connections between variables were investigated by utilizing the linear autoregressive distributed lag technique. Long-run analysis results uncover that fossil fuel energy, renewable energy use, CO 2 emissions, and GDP per capita have a productive relationship with economic progress in Pakistan, whereas electric power consumption, electricity produced from nuclear sources, and energy utilization have an adverse effect on economic growth. Furthermore, the consequences revealed that fossil fuel energy, renewable energy consumption, carbon dioxide emissions, and GDP per capita have a significant linkage to Pakistan's economic growth via short run, whereas we revealed that the variables electric power consumption, electricity produced from nuclear sources, and energy usage have an adversative linkage to Pakistan's economic growth. Feasible progressive policies are required from the Pakistani government to pay more attention for tackling the energy and power sectors' issues in terms of fulfilling the country's energy requirements., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Population growth has been a leading driver of global CO 2 emissions over the last several decades. CO 2 emission and greenhouse gas emissions are a key issue in the world that affects food production and also causes the climate change. The core purpose of this study was to inspect the influence of carbon dioxide emission to population growth, food production, economic growth, livestock and energy utilization in Pakistan. The STIRPAT (Stochastic Impact by Regression on Population, Affluence and Technology) model with the extension of an ARDL (Autoregressive Distributed Lag) method was utilized to demonstrate the linkage amid variables. Outcomes during short-run investigation reveal that variables population growth, economic growth, rural population growth, livestock production uncovered a productive association with CO 2 emission. Furthermore, via long-run population growth, economic growth, rural population growth, livestock production and energy utilization have positive interaction with CO 2 emission, while the variables food production and urban population growth demonstrated an adverse influence to CO 2 emission during long- and short-run interaction. Similarly, the error correction model exposed that population growth, economic progress, livestock and energy utilization have constructive interaction to CO 2 emission, while the variables food production, urban and rural population growth exposed an adverse impact to CO 2 emission. On the basis of this analysis, we will address the strategic consequences., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Carbon dioxide emission and GHGs are associated with fossil fuels which have adverse effects on the environment. The key intention of this paper was to determine the asymmetric effect of CO 2 emission on expenditures, trade, FDI, and renewable energy consumption in Pakistan. An asymmetrical technique (nonlinear autoregressive distributed lag) was employed to validate the constructive and adverse relation among variables. Furthermore, the Granger causality test was also used to verify the unidirectional association amid variables. Study outcomes revealed that the adverse shocks of renewable energy consumption exposed expressively to upsurge CO 2 emission in the short-run dynamics. Conversely, constructive shocks of renewable energy consumption display an adversative association with CO 2 emission. Furthermore, the decreasing trend in foreign direct investment tends to impede the detrimental effects of CO 2 emission. Additionally, the variable expenditures also create the non-eco-friendly impacts and manifest the positive linkage through CO 2 emission. Trade possesses statistically insignificant linkage with environmental degradation. The results also disclose that positive as well as negative variations in the foreign direct investment expose to degrade the environmental eminence. Long-run results suggest the direct association between downward trend in renewable energy consumption and CO 2 emission signifying that the pollution level decreases, and the upward trend in renewable energy consumption, however, demonstrates insignificantly positive effects. The results also disclose that positive as well as negative variations in the FDI lead to degrade the CO 2 emission. Moreover, it is found that the expenditures soar the issue of pollution again in the long run. Finally, the consequence of trade on CO 2 emission is adverse, as the outcome suggests. In order to improve the environmental policies for sustainable growth, the study provides direction toward a sustainable environment by reducing carbon dioxide emission., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The present study aims to investigate the effects of information and communication technology, foreign direct investment, trade and renewable energy use with GDP growth in Pakistan using time series data ranging from 1985 to 2017. Stationarity of data was verified by using unit root tests including ADF and P-P, while an autoregressive distributed lag (ARDL) model was used to check the dynamic association amid prescribed variables with long- and short-run analysis. Furthermore, cointegrating regression analysis with FMOLS, DOLS and CCR was applied to validate the variables causality. The outcomes during long-run analysis show that ICTE, trade and renewable energy have constructive linkage to GDP growth, while foreign direct investment has adverse influence to GDP growth in Pakistan. Similarly, the outcomes from cointegrating regression technique exposed that all variables including foreign direct investment, ICTE and trade have positive and constructive association with GDP growth except renewable energy that causes the adverse association to GDP growth in Pakistan. On the basis of outcomes, we will discuss the policy recommendations., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The largest challenge still remains in enhancing the living conditions and economic progress, while growing the environmental footprint is related to energy. The move towards renewable sources means that energy utilization can be increased and environmental impacts reduced. The key purpose of the present analysis was to investigate the CO2 emissions interaction to industrialization, energy imports, carbon intensity, economic progress, and gross capital formation by using time span data ranging from 1971 to 2019. Variable stationarity was confirmed by utilizing the unit root tests, while quantile regression analysis was utilized to check the CO2 emission influence on the independent variables. Outcomes showed that industrialization has constructive influence with CO2 emission having coefficient (0.161636) with probability value (0.0000). Similarly the variable energy imports, carbon intensity, and gross capital formation have positive coefficients (0.206843), (0.895212), and (0.442922) with probability values (0.2171), (0.0004), and (0.0002) correspondingly that exposed the positive interaction with CO2 emission in Pakistan. The variable economic progress exposed an adverse impact to CO2 emission with having coefficient (-0.002841) with probability value (0.8795). In directive to improve the economic progress, the government of Pakistan should take future action to minimize carbon dioxide emission from different sectors that cause the climate change., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The present study seeks to investigate the sector-level energy consumption of oil and natural gas and to explore the linkage between economic growth, households, agriculture, industry, power, fertilizers, and commercial sector in Pakistan for the period of 1980-2016. The energy sector of Pakistan is facing severe crisis from the last few years due to inadequate production and supply. Long-lasting deficits of natural gas and oil, the two supreme types of fuel in Pakistan, had detrimental consequences for the growth as well as for the economic development. An autoregressive distributed lag (ARDL) method and Granger causality test under vector error correction model (VECM) were employed to check the association among the variables. Furthermore, the innovative accounting method was used to investigate the responsiveness of each variable to another within the study framework. Empirical results show long-run association among the variables, as oil consumption in the agriculture and power sector show a positive effect on Pakistan's economic growth. Similarly, energy consumption from natural gas in the households and fertilizers as well as in the industry sector has had a constructive association with economic growth. In contrast, energy consumption from oil in the households and industry sectors has adverse association with economic growth, while natural gas consumption in the commercial sector has negative linkage with economic growth. Possible steps should be taken by the Government of Pakistan to enhance the production of oil and natural gas from other alternatives to meet the requirements of these sectors., (© 2020. Springer-Verlag GmbH Germany, part of Springer Nature.)

This study investigates the effects of military expenditure, final consumption expenditure, gross national expenditure, net income, broad money, and total reserves on Pakistan's economic growth. The nonlinear autoregressive distributed lag (NARDL) and robust regressions methods are used to examine the relationship among variables. The outcomes revealed that total reserves positively impacted the economic growth during positive and negative short- and long-run shocks. Final consumption expenditure and gross national expenditure negatively influenced the economic growth. Similarly, military expenditure and net income positively and negatively impacted the economic growth, while broad money has adverse and positive relation to economic growth. The results of the robust least squares and stepwise least squares approaches showed that all variables except military expenditure and reserves have positive impact on economic development. This study suggests that government should carefully monitor defence-related investment to maintain economic development. [ABSTRACT FROM AUTHOR]

Population growth has been a leading driver of global CO2 emissions over the last several decades. CO2 emission and greenhouse gas emissions are a key issue in the world that affects food production and also causes the climate change. The core purpose of this study was to inspect the influence of carbon dioxide emission to population growth, food production, economic growth, livestock and energy utilization in Pakistan. The STIRPAT (Stochastic Impact by Regression on Population, Affluence and Technology) model with the extension of an ARDL (Autoregressive Distributed Lag) method was utilized to demonstrate the linkage amid variables. Outcomes during short-run investigation reveal that variables population growth, economic growth, rural population growth, livestock production uncovered a productive association with CO2 emission. Furthermore, via long-run population growth, economic growth, rural population growth, livestock production and energy utilization have positive interaction with CO2 emission, while the variables food production and urban population growth demonstrated an adverse influence to CO2 emission during long- and short-run interaction. Similarly, the error correction model exposed that population growth, economic progress, livestock and energy utilization have constructive interaction to CO2 emission, while the variables food production, urban and rural population growth exposed an adverse impact to CO2 emission. On the basis of this analysis, we will address the strategic consequences. [ABSTRACT FROM AUTHOR]

Carbon dioxide emissions have been the primary source of extreme environmental pollution and have detrimental consequences on human life, irrespective of an economy being developed or underdeveloped. For the developing economies, in particular, it is imperative to reduce such emissions in order to sustain the growth of the respective economies. However, for designing appropriate emission reduction policies, it is appropriate to identify the sectors which contribute the most to carbon dioxide emissions and dampen the growth of overall economy. Against this background, the key intention of this study was to examine the influence of carbon dioxide emissions generated from various sources on the economic progress in Pakistan between 1971 and 2017. This study is important for Pakistan to sustain its economic progress and enable the nation to comply with commitments of the Paris Agreement and Sustainable Development Goals. The econometric analysis conducted in this study considers a nonlinear autoregressive distributed lag model which is applied to ascertain the short- and long-run economic growth impacts associated with positive and negative shocks to CO2 emissions generated from various sources. The choice of this model is driven by its capacity to perform an asymmetric analysis which is relevant for suitable policy-making purposes. The overall results, in a nutshell, reveal that carbon dioxide emissions from Pakistan's transportation sector influence the country's economic progress. Positive shocks to such carbon dioxide emissions are originate to reduce economic progress in the long run while negative shocks are evidenced to boost economic growth both in the short and long run. In contrast, carbon dioxide emissions from other major sectors are found to be ineffective in influencing Pakistan's economic growth both in the short and long run. Hence, keeping into consideration the prospects of attaining sustainable economic growth, the Pakistan government must prioritize the implementation of CO2 emissions-inhibiting policies within the transportation sector. Simultaneously, the traditional fossil fuel dependency within this sector should also be phased out. [ABSTRACT FROM AUTHOR]

This study aims to examine the impact of coal energy consumption on the economic progress in Pakistan by using annual time series data during 1972–2019. Three-unit root tests were employed to rectify the variables' stationarity. The quantile regression approach with the extension of cointegration regression test was utilized to check the variables interaction with the economic progress. The outcomes of the quantile regression uncover that coal energy consumption in power sector and coal energy consumption in brick kilns have adverse influence to the economic progress, while total coal energy consumption has a productive association with the economic progress. Similarly, the findings of cointegration regression analysis uncover that via FMOLS (Fully Modified Least Squares) and DOLS (Dynamic Least Squares) that variables coal energy consumption in power sector and brick kilns have an adverse connection with the economic progress, while total coal energy consumption uncover a productive linkage to the economic progress in Pakistan. Pakistan is still facing a deep energy crisis because of the lack of energy production from cheap sources. New possible policies are required in this direction to improve the energy sector by paying more attention to the alternative energy sources to foster the economic progress. [ABSTRACT FROM AUTHOR]

Studies of total factor productivity (TFP) in livestock production are rare, but when available provide useful information especially in the context of developing countries such as China where livestock is becoming more important in the domestic agricultural economy. We estimate TFP for four major livestock products in China employing the stochastic frontier approach, and decompose productivity growth into its technical efficiency (TE) and technical progress components. Efforts are made to adjust and augment the available livestock statistics. The results show that growth in TFP and its components varied between the 1980s and the 1990s as well as over production structures. While there is evidence of considerable technical innovation in China's livestock sector, TE improvement has been relatively slow. [ABSTRACT FROM AUTHOR]

The accumulation of carbon dioxide in the atmosphere has surged over the years as a consequence of diverse humans activities such as deforestation and farming, in particular. The rapidly growing agriculture and farm mechanization have contributed to substantial increases in energy use and carbon dioxide emissions across the globe. It is hypothesized that agriculture significantly contributes to a country's economy to which China is no exception. Hence, the main intention of the current study was to explore the asymmetrical influences of cereal crop production, forestry production, and economic progress on CO 2 emissions in China between 1970 and 2017. The non-linear ARDL (Autoregressive Distributed Lag) bounds testing method was used to determine the short- and long-run dynamics linked with positive and negative shocks to the explanatory variables. The findings indicate that positive shocks to cereal crop production deteriorate the atmospheric quality by intensifying carbon dioxide emissions only in the long run, while the impacts of negative shocks in this regard are statistically insignificant. Ironically, shocks to forestry do not exhibit any significant impact on China's carbon dioxide emission levels. Moreover, carbon dioxide emissions demonstrate a strong progressive association with the positive shocks to energy resources utilized within the Chinese economy. Additionally, positive and negative shocks to economic progress are evidenced to boost and reduce the carbon dioxide emission figures in the long run. Lastly, negative shocks to livestock production are witnessed to increase carbon dioxide emissions only in the short run. Hence, for achieving the Chinese carbon-neutrality agenda, it is recommended to prioritize the use of renewable energy resources, particularly for producing cereal crops, in order to curb carbon dioxide emissions in China. Simultaneously, the Chinese economic growth policies should integrate environmentally-friendly schemes to counter the adversative environmental influences related to the economic progress in China. • The environmental impacts of cereal crops and forestry production are assessed. • The environmental impacts of livestock production are assessed. • Positive shocks to cereal crops production boost CO 2 emissions. • Negative and positive shocks to economic progress reduce and boost CO 2 emissions. • Positive shocks to energy use boost CO 2 emissions. [ABSTRACT FROM AUTHOR]