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We examine the linkages of economic freedom (ECF), energy use, and CO2 emissions in selected South Asian countries of Pakistan, India, Bangladesh, and Sri Lanka. Annual data from 1995 to 2018 are analyzed by employing second-generation methodologies. Cross-sectional autoregressive distributed lag (CS-ARDL) is used because this method incorporates the cross-sectional dependence among the data. This work uses three models, where the dependent variables are gross domestic product (GDP), CO2 emissions, and energy use. The findings reveal that ECF and energy use contributes to more economic development. ECF is improving air quality by lowering CO2 emissions. The findings suggest that these countries need to increase the percentage of renewable energy in their energy generation mix. At the same time, there is a need to integrate ECF with environmental awareness programs. This will not only increase air quality but also increase economic growth. GDP is found to be dependent on energy use; however, increased energy use from non-renewable also contaminates the environment. Therefore, South Asian countries need to invest more in research and development projects to promote renewable energy. [ABSTRACT FROM AUTHOR]

We examine the relative performance of the industry, services, and agriculture sectors in energy conservation and reduction in CO2 emissions in Pakistan using the "spatial-temporal decomposition" method by taken data from 2006 to 2016. An efficient way to achieve low-carbon economy targets is to decompose different factors contributing to CO2 emissions, including structure effect, intensity effect, GDP gap effect, energy use efficiency effect, and economic efficiency. We classify economic sectors into three groups based on performance, i.e., sectors performing below, average, and above-average performing. Our results indicate that the economic efficiency and energy use efficiency effects in the industry sector have remained above average. In contrast, the GDP gap effect has remained below average. In the case of structure effect and intensity effect, the agriculture sector has performed on average. In contrast, the service sector has shown mixed results in all factors. The government should pay special attention to energy use structure and innovation to improve desirable output technical efficiency to achieve the target carbon emission level. [ABSTRACT FROM AUTHOR]

This study uses ecological modernization and environmental transition theories to estimate the interaction among energy intensity, carbon emission and urbanization for the period of 1980–2017. We have systematically examined the empirical connections among emission, urbanization, income per capita, imports, exports, energy use, trade openness and energy intensity. The Johnson co-integration and Vector Error Correction Model (VECM) causality methods are employed for the sake of analysis. Overall findings confirm the dynamic and U-shaped relationship between emission and urbanization, and carbon emission and income per capita. The empirical results of urbanization, inflation and financial development illustrate positive association with the energy intensity, whereas trade openness, labour force participation and carbon emission show a negative association with the dependent variable. Moreover, outcomes of causality analysis provide evidence of varied causality link among the variables across the models. The study provides the implications for the decision makers in Pakistan to choose new urbanization patterns that are less reliant on energy consumption. [ABSTRACT FROM AUTHOR]

The study investigates the effect of income, institutional quality, urbanization and industrialization on energy intensity in Pakistan using vector error correction model. It finds poor institutional quality and industrialization behind high energy intensity in Pakistan while income per capita and associated urbanization playing a significant role in reducing energy intensity. Good governance practices and better quality of institutions can play an effective role in increasing the efficiency in the use of energy thus reducing overall energy intensity. Moreover, investment in apposite technical and general education, in addition to enhancing research and development activities can help make Pakistan an innovation based economy and increase its productivity and eventually become an energy efficient economy. [ABSTRACT FROM AUTHOR]

This study applied the logarithmic mean Divisia index (LMDI) model to identify and discuss the main drivers of Pakistan's CO2 emissions over the period 1990–2016. The study examined the effects of five factors based on Pakistan's three main economic sectors while considering the 11 types of fuels consumed in that country. The results showed that the energy structure effect is the greatest driving force of CO2 emissions in this country, followed by scale effect and economic structure effect. Energy intensity is the main contributor to reducing Pakistan's carbon emissions throughout the study period. A comparative review at the sectoral level shows that the industrial sector for which coal is the main source of energy supply is the one that contributes the most to CO2 emissions in Pakistan. Alongside this sector is the tertiary sector, where the transport sub-sector imposes rules of conduct based on a growing Pakistani population. Meanwhile, deforestation would be the main cause of CO2 emissions from the agricultural sector in Pakistan, as energy consumption in this sector remains very low. Improving energy efficiency through the intensification of clean energy is urgently needed if Pakistan's environmental goals are to be achieved. [ABSTRACT FROM AUTHOR]

This study explores the nature of relationship between energy efficiency, measured by energy intensity (energy consumption to GDP ratio) and the level of economic activity, measured by GDP in Pakistan during 1980-2016. This study also analyzes the relationship between sectoral shares and energy efficiency. We used Error Correction Model (ECM) for empirical analysis to tests the existence of a long-term relationship between the energy intensity and GDP while using this model to capture the Granger causality between variables. Results of Johansen's co-integration show that causality exists at least in one direction. Results of ECM predict the existence of unidirectional causality from GDP to energy intensity. These findings support conservation hypothesis on the basis of unidirectional causality running from output to energy efficiency. It is further observed that energy intensity in Pakistan is expected to increase further in the light of growing shares of industrial and services sectors in the GDP. [ABSTRACT FROM AUTHOR]

According to Jevon's paradox, energy efficiency leads to more energy consumption instead of low. So, calculating the size of energy rebound effect is need of the time to devise sustainable environmental and energy policies. This paper aims to analyze the impact of energy efficiency on energy consumption of transport sector in Pakistan by using time series data from 1980 to 2018. This incremental energy consumption channelizes through intensity and output effects. The study uses both Cobb-Douglas (C-D) and constant elasticity of substitution (CES) aggregate production functions to find the magnitudes of energy rebound effect. As the analysis of energy rebound effect is sensitive to the selection of data, model, and methodology. C-D production function deals with energy rebound effect, while CES provides extra information in the form of energy intensity and output effects along with energy rebound effect. The C-D function is estimated with linear estimation technique, while the CES function is estimated through nonlinear optimization method. The results indicate relatively low magnitudes of energy rebound effect in case of C-D function, e.g., 2% in the short run and about 36% in the long run while about 70% energy rebound, 63% energy intensity, and 7% output effect in the transport sector of Pakistan in the long run by using CES function. As anticipated, energy efficiency is less effective in terms of energy savings in transport sector due to energy rebound effect. Therefore, policy makers should incorporate energy rebound effect to achieve sustainable environmental goals along with economic growth path., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study applied the logarithmic mean Divisia index (LMDI) model to identify and discuss the main drivers of Pakistan's CO 2 emissions over the period 1990-2016. The study examined the effects of five factors based on Pakistan's three main economic sectors while considering the 11 types of fuels consumed in that country. The results showed that the energy structure effect is the greatest driving force of CO 2 emissions in this country, followed by scale effect and economic structure effect. Energy intensity is the main contributor to reducing Pakistan's carbon emissions throughout the study period. A comparative review at the sectoral level shows that the industrial sector for which coal is the main source of energy supply is the one that contributes the most to CO 2 emissions in Pakistan. Alongside this sector is the tertiary sector, where the transport sub-sector imposes rules of conduct based on a growing Pakistani population. Meanwhile, deforestation would be the main cause of CO 2 emissions from the agricultural sector in Pakistan, as energy consumption in this sector remains very low. Improving energy efficiency through the intensification of clean energy is urgently needed if Pakistan's environmental goals are to be achieved.