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Weather, trade restrictions, rising oil prices, a lack of financial support for farmers, and other factors have contributed to the destabilization of South Asian food security. The purpose of this study is to determine the long-run and short-run relationships between climate change, agricultural credit, renewable energy, and food security for a sample of South Asian countries between 1990 and 2021. The Dynamic Common Correlated technique is utilized for empirical analysis since it directly addresses the issue of cross-sectional dependency while delivering accurate cointegration findings. The study's empirical findings show that climate change reduces food availability and increases the incidence of food insecurity in South Asia. In contrast, the use of renewable energy sources has a positive effect on food security in the short-run but not in the long-run, while the availability of credit to farmers has a positive effect on food security. Findings suggest that South Asian countries may reduce climate change's negative effect on food security by investing in climate services, climate-resilient infrastructure, growing drought-resistant crops, using supplemental reinforced agricultural practices, and improving their weather forecasting capabilities. [ABSTRACT FROM AUTHOR]

The main aim of this analysis is to determine the contribution of exports of communication technology, goods and services, food, and manufacturing exports and foreign investments to economic growth in Pakistan by utilizing time series data from 1976 to 2019. NARDL (non-linear autoregressive distributed lag) technique is utilized to encounter the linkages of variables via positive and negative shocks both in the long run and in the short run. The examined result of the short run indicates that the export of communication technology has a productive and adversative linkage to economic progress during positive and negative shocks. On the other side, exports of goods and services and food exports have a negative relationship with economic growth. Similarly, foreign investment exposed the constructive and negative linkage to economic growth during positive and negative shocks. Furthermore, manufacturing exports exposed an adversative and productive association to economic development in Pakistan. Moving toward the long-run analysis's results which show communication technology has constructive and adversative linkages to economic growth. Exports of goods and services and food exports also uncovered the adversative association to economic development in Pakistan. The foreign investment positive and negative shocks show adversative and productive linkages to economic growth. Furthermore, the variable manufacturing exports exposed a negative relation with economic growth in Pakistan in both positive and negative shocks. Based on the examined results, it is recommended that government policy experts must adopt new steps to boost exports to support the country's economic growth. [ABSTRACT FROM AUTHOR]

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]

The present study major aim was to examine the impact of globalization, economic growth, population growth, renewable energy usage and nuclear energy on CO2 emissions globally by taking the annual data varies from 1985 to 2020. Stationarity among study variables were tested via unit root testing, while nonlinear autoregressive distributed lag (NARDL) technique was used to demonstrate the linkages among variables with the estimation of long-run and short-run. Study results reveal that both in the short run and long run, negative globalization and economic growth shocks positively and negatively influence CO2 emissions, respectively. Besides, higher population growth is found to positively influence CO2 emissions while renewable energy consumption cannot influence the CO2 emission figures. Lastly, positive and negative shocks to alternative nuclear energy consumption are evidenced to negatively influence CO2 emissions both in the short run and long run. Hence, in line with these findings, several new policies and strategies are recommended for reducing carbon emissions globally. [ABSTRACT FROM AUTHOR]

The primary goal of this study was to examine the relationship between fossil fuel energy, electricity production from nuclear sources, renewable energy, CO2 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, CO2 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. [ABSTRACT FROM AUTHOR]

Agriculture plays an integral part in facilitating socioeconomic development in Nepal. However, it is also associated with environmental concerns which need to be controlled for the sake of ensuring environmental and agricultural sustainability in tandem. Against this backdrop, this current study aims to check whether shocks to the levels of agricultural productivity, land utilization for crop production, and fertilizer consumption influence the carbon dioxide emission figures of Nepal over the 1965-2018 period. The long-run associations between these variables are confirmed from the cointegration analysis. Besides, the outcomes from the asymmetric non-linear autoregressive distributed lag regression analysis show that crop productivity does not influence the emission levels in Nepal. However, a decline in the land area used for crop production purposes is evidenced to trigger higher emissions of carbon dioxide both in the short- and long run. On the other hand, higher fertilizer consumption is found to boost the short- and long-run carbon dioxide emission levels in Nepal. Accordingly, considering the objective of reducing agriculture-based emissions, this study recommends the Nepalese government to adopt policies that can enhance the productivity of low energy-intensive crop production, stimulate green agriculture and non-agriculture activities, and minimize the use of chemical fertilizers in arable lands. [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]

One of the major challenges to the survival of life on earth is the increasingly evolving climate change. The key source of environmental pollution is global warming. With the combustion of fossil fuels, greenhouse gas (GHG), which is generated in the external environment, is increased and air pollutant as well. The present analysis key intention was to examine the CO2 emission and climatic effects on major agricultural crop production and land use in Pakistan. The study used time span annual data varies from 1970 to 2019, and data stationarity was rectify by utilizing the unit root tests. A generalized method of moments with two-stage least squares technique was applied to expose the variables' association with CO2 emission. The study consequences uncover that the wheat, maize, sugarcane, cotton, bajra, gram, sesamum crops, and land use have constructive association with CO2 emission having positive coefficients with probability values (0.3762), (0.0435), (0.2287), (0.2303), (0.2272), (0.0192), (0.4535), and (0.0017) correspondingly, while rainfall, temperature, rice, jowar, and barley uncovered an adversative linkage to CO2 emission in Pakistan. As Pakistan is an emerging country, potential constructive measures must be introduced in directive to reduce CO2 emissions to improve the agricultural productivity. [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]

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 CO2 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 CO2 emission in the short-run dynamics. Conversely, constructive shocks of renewable energy consumption display an adversative association with CO2 emission. Furthermore, the decreasing trend in foreign direct investment tends to impede the detrimental effects of CO2 emission. Additionally, the variable expenditures also create the non-eco-friendly impacts and manifest the positive linkage through CO2 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 CO2 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 CO2 emission. Moreover, it is found that the expenditures soar the issue of pollution again in the long run. Finally, the consequence of trade on CO2 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Carbon dioxide emission and climatic variation have a detrimental influence on the atmosphere as well as on agriculture production. The key aim of the present study was to investigate the influence of carbon dioxide emission on livestock, cereal crops production, rainfall and temperature in China by utilizing the vector autoregressive model and Granger causality test for the period 1988–2017. Variables stationarity was verified by using ADF, P-P and KPSS unit root tests. The outcomes through long-run dynamics exposed that agriculture value added and rainfall have a positive influence on carbon dioxide emission, while cereal crops production, livestock production and temperature have an adverse interaction with carbon dioxide emission. Similarly, the results of the short-run analysis also demonstrate that agriculture value added, cereal crops production, livestock production, rainfall and temperature have a significant influence on carbon dioxide emission with their p-values (0.0488), (0.0885), (0.0263), (0.0096) and (0.5141) respectively. Furthermore, the Granger causality test outcomes also exposed a unidirectional linkage amid the variables. In order to improve agricultural productivity, the Chinese government should take potential steps to minimize the carbon dioxide emission from various industries that trigger climate change. [ABSTRACT FROM AUTHOR]

The accelerated urbanization in China was already coupled with a steadily increasing demand for energy usage. The present study major aim was to determine the asymmetric influence of urbanization, energy utilization, fossil fuel energy and CO2 emission on economic progress in China by using an annual time series data varies from 1975 to 2017. Stationarity amid variables was verified by applying the unit root tests, while non-linear autoregressive distributed lag (NARDL) bounds testing model was used to examine the asymmetric impacts on variables with short- and long-run dynamics. Outcomes revealed that via short-run estimates, the negative shocks of energy usage cause significantly to increase the economic efficiency, but positive shocks of energy utilization display the adverse linkage with the economic progress. Similarly, the negative shocks of GDP per capita growth demonstrate a substantial upsurge in the economic progress, and the positive shocks establish the adverse influence towards economic growth. Further, the outcomes of short-run dynamics also exposed the negative shocks of urbanization significantly affected the economic growth, but positive shocks exposed the adversative influence on economic growth. The outcomes display that fossil fuel energy consumption showed a constructive impact to economic progress, and additionally, the variable CO2 emission also uncovered a positive shocks having significant impact on economic progress. Furthermore, the outcomes of long-run analysis express that energy utilization has negative and positive shocks that expose the adverse influence on economic progress of China. GDP per capita growth exposed the constructive influence on the economic growth in both shocks. The negative and positive shocks of urbanization demonstrate a noteworthy influence on economic growth. The variable fossil fuel energy consumption also exposed an optimistic influence on economic progress, and finally the influence of CO2 emission on economic growth is insignificant as the results exposed. The reducing carbon alteration target aims to be reached for China, and in the next several decades, it will encourage the green energy options in order to decrease carbon dioxide emission to avoid environmental pollution by raising its energy intensity. [ABSTRACT FROM AUTHOR]

Carbon dioxide emission and greenhouse gas emissions are considered core issue in the world that influence agricultural production and also cause climate change. The present study seeks to investigate the linkage of methane emissions, nitrous oxide emissions, carbon dioxide emission, and greenhouse gas emissions with agricultural gross domestic product in China. The long-term association was checked by using an autoregressive distributed lag (ARDL) bounds testing approach, fully modified least squares method, and canonical cointegrating regression analysis. The results from long-run analysis exposed that carbon dioxide emission and greenhouse gas emissions have positive coefficients that demonstrate the long-run linkage with the agricultural gross domestic product having p values of 0.5709 and 0.3751, respectively. Similarly, results also revealed that agricultural methane emissions and agricultural nitrous oxide emissions have a negative association with the agricultural gross domestic product having p values of 0.1737 and 0.0559. China is a huge emitter of CO2 emission and greenhouse gas emissions. Possible conservative policies are required to form the Chinese government to tackle this challenge to decrease CO2 emission in order to increase agricultural production. [ABSTRACT FROM AUTHOR]

Global warming influencing the agricultural production in several ways due to rainfall, temperature and carbon dioxide emission. The objective of this study is to investigate the climatic and carbon dioxide emission influence to maize crop production in Pakistan for the period of 1988–2017. We used an ARDL approach and Granger causality test to check the dynamic linkage between carbon dioxide emission, maize crop production, area under maize crop, water availability, rainfall and temperature with the evidence of long-run and short-run. Analysis results revealed that maize crop production has positive coefficient that demonstrate the long-term association with carbon dioxide emission with p value 0.0395. Similarly, results also showed a long-run association among water availability, rainfall and temperature with carbon dioxide emission with having positive coefficient and p values 0.0000, 0.0014 and 0.0001. Unfortunately, the coefficient of area under maize crop showed a negative linkage with carbon dioxide emission. Possible conservative policies are needed from the Pakistani government to reduce carbon dioxide emission in order to enhance the agricultural production as well as to boost the economic growth. [ABSTRACT FROM AUTHOR]