Prediction of consumers refill frequency of LPG: A study using explainable machine learning.

Launched in 2016, the PMUY Programme of the Government of India aimed to provide 8 crore LPG connections to women in rural households over four years. After acquiring a new connection, some households appeared uninterested in ordering subsequent subsidized LPG refills, impacting programme's sustainability, and targeting strategy. We propose a prediction model using "Explainable Machine Learning" to anticipate the beneficiaries' refill frequency with a view to improving LPG-refills and social targeting. In this paper, we suggest an enhanced stacked SVM (ISS) model for classification, which is contrasted with state-of-art ML models: Random Forest (RF), SVM-RBF, Naive Bayes (NB), and Decision Tree (C5.0). Some of the performance matrices that are used to evaluate the models include accuracy, sensitivity, specificity, Cohen's Kappa statistics, Receiver Operating Characteristic curve (ROC), and area under the curve (AUC). The proposed approach, which was validated with 10-fold cross validation, produced the best overall accuracies for data splits of 50-50, 66-34, and 80-20. The "Explainable AI (XAI)" model has also been used to describe how models and features interact, and to discuss the importance of features and their contributions to prediction. The recommended XAI will aid in efficient "beneficiary targeting" and "policy interventions".

Unveiling the environmental efficiency puzzle: Insights from global green innovations.

The latest surge of global uncertainty and disruptions in global supply networks put policymakers under pressure to emprise green innovations as a vital tool to address environmental concerns. However, producing green innovations doesn't always help in achieving environment-related sustainable development goals. Therefore, in this study, we endeavour to investigate to what extent green innovations are efficient in improving environmental efficiency. To this end, a network bias-corrected data envelopment analysis and clustering analysis is applied. The data used in this study covers 42 countries from different regions, spanning from 2000 to 2020. The results reveal that most countries have not made major advancements in environmental efficiency signifying the low level of green innovations utilization to achieve environment-related sustainable development goals (SDGs). Additionally, the results demonstrate a U efficiency curve for inputs-oriented green innovations efficiency over time, indicating that the initial stages of green innovations production are associated with a decreased return. However, over time, the efficiency exhibits an upward trend. The benchmarking analysis reveals that South American and European Union nations set the bar for other countries in terms of efficiently leveraging green innovations to achieve SDGs. Our findings also suggest that environmental efficiency is more dependent on green-supporting policies such as green energy production and green taxes. As a result, we conclude that achieving environmental SDGs while utilizing green innovations does not always result in the development of other SDGs. Therefore, policymakers need to prioritize pursuing a green developmental approach and supporting policies to achieve environment-related SDGs and other SDGs.

Capital flow and environmental quality at crossroads: designing a sustainable policy framework for the newly industrialized countries.

It is extremely difficult for emerging economies to achieve the Sustainable Development Goals (SDGs), and in order to close this policy gap, a comprehensive policy framework is needed. The purpose of this research is to determine the proportional impacts of domestic and foreign capital to environmental degradation in newly industrialized nations (NICs). For this reason, panel data methodology is used to evaluate, for the years 1991 to 2018, how the ecological footprint is affected by stock market capitalization, foreign direct investment, economic growth, urbanization, and energy intensity. Using the squared terms of stock market capitalization and foreign direct investment, respectively, it is also looked at whether domestic and foreign capital may have non-linear effects on the environment. According to the empirical findings, whereas local capital growth worsens the environment, increasing international capital prevents environmental degradation. There is an inverted U-shaped link between domestic capital and environmental degradation in the event of non-linearity, but foreign capital has a monotonically declining effect on environmental degradation. The study outcomes are utilized to design a policy framework to address the objectives of SDG 7, SDG 11, and SDG 13.

How do economic and financial factors influence green logistics? A comparative analysis of E7 and G7 nations.

Logistics is an important sector that supports every sector of the economy, and thus, the development of nations is impossible without efficient logistics. Alongside this, the logistics sector generates various kinds of emissions that degrade the quality of the environment. Developed countries are striving to introduce green logistics to avoid environmental damages caused by transportation. Also, developing countries will start focusing on developing green logistics sooner or later. Keeping this in view, a comparative panel study on the group of seven (G7) and Emerging Seven (E7) nations is conducted to study the impacts of various economic and financial variables on green logistics. The data from 1996 to 2018 is analyzed using some reliable methods that produce efficient and consistent results during heterogeneity and cross-sectional dependence. The findings disclosed that cointegration is present in E7 and G7 panels. For E7 countries, the results disclosed that research and development (R&D), FDI, portfolio investment, and trade openness reduce green logistics. However, in the G7, R&D, FDI, portfolio investment, and trade increase green logistics. The empirical analysis did not show any meaningful impact of financial development and economic growth on green logistics in both groups of nations. Lastly, based on the comparative analysis, various policies are suggested for E7 to catch up with the G7 regarding logistics development. Also, policies for G7 are suggested to boost green logistics.

A Gender Differentiated Analysis of Healthy Life Expectancy in South Asia: The Role of Greenhouse Gas Emission.

The sluggish progress concerning SDG-9 and SDG 13 has made South Asia an epicentre of household and ambient greenhouse gases emissions. Furthermore, the regional progress concerning attainment of SDG-3 is considerably low. The major research objectives are twofold. First, to explore the impact of GHGs emissions from agriculture, transportation, and manufacturing sector on disaggregated life expectancy. Second, to examine the mitigating impact of renewable energy use, trade integration, and human capital development for practice policy recommendations. These research objectives are realized by employing recently advanced cross-sectional auto regressive distributed lag (CS-ARDL) model on panel data of five South Asian countries such as Bangladesh, India, Pakistan, Nepal, and Sri Lanka from 1990 to 2019. The estimation outcome reveals that the emissions from transportation, manufacturing, and agricultural sectors significantly deteriorate healthy life expectancy of male and female healthy life expectancy in South Asia with different intensity. Especially, we find that long-run impact of GHG is more profound on male healthy life expectancy than female life expectancy. The result further shows that renewable energy and human capital substantially improve healthy life expectancy, whereas the effects of trade integration are insignificant. The finding of moderating variables shows that renewable energy, human capital development, and trade integration have high potential to reduce GHGs emissions. The findings of this study urge South Asia for investments in human capital development and renewable energy along with fostering regional integration to decrease GHG and improve healthy life expectancy.

Modeling the impact of climatic and non-climatic factors on cereal production: evidence from Indian agricultural sector.

The underpinned study examines the effects of climatic and non-climatic factors on Indian agriculture, cereal production, and yield using the country-level time series data of 1965-2015. With the autoregressive distributed lag (ARDL) bounds testing approach, the long-term equilibrium association among the variables has been explored. The results reveal that climatic factors like CO2 emissions and temperature adversely affect agricultural output, while rainfall positively affects it. Likewise, non-climatic factors, including energy used, financial development, and labor force, affect agricultural production positively in the long run. The estimated long-run results further demonstrate that CO2 emissions and rainfall positively affect both cereal production and yield, while temperature adversely affects them. The results exhibit that the cereal cropped area, energy used, financial development, and labor force significantly and positively impact the long-run cereal production and yield. Finally, pairwise Granger causality test confirmed that both climatic and non-climatic factors are significantly influencing agriculture and cereal production in India. Based on these results, policymakers and governmental institutions should formulate coherent adaptation measures and mitigation policies to tackle the adverse climate change effects on agriculture and its production of cereals.

Analyzing global inequality in access to energy: Developing policy framework by inequality decomposition.

Energy poverty is a critical policymaking problem in the world, while the outlined solutions in academic and policy literature talks about the solutions, without addressing the possible cause of the problem. The interaction between labor and energy market might pave a way to address the issue. Within the context of energy poverty, this interaction might turn out to be a major roadblock in the way to attain the objectives of Sustainable Development Goals (SDGs). From this perspective, this study aims at analyzing the constituents of inequality in access to energy, and in that pursuit, it has employed Kaya-Theil Decomposition method. The study is carried out at the global level over the period of 1990-2019. The study outcomes demonstrate all the inequality components to be rising during the study period. Presence of a possible feedback loop in the association might create the Vicious Circle of Energy Poverty around the globe. This study contributes to the literature by addressing the demand-side dimension of the energy poverty issue, while using the Kaya-Theil Decomposition method as an estimator of demand-side factors. Based on the study outcomes, a policy framework has been recommended, and it is aimed at helping the nations to achieve the objectives of SDG 7, SDG 8, and SDG 10.

Examining the temporal impact of stock market development on carbon intensity: Evidence from South Asian countries.

The growing size of stock market in the South Asian countries might have contributed to raising the level of industrial production and energy consumption. This upturned energy usage might have widened the scope for carbon emissions because these nations heavily rely on fossil fuels. In this milieu, therefore, in the present study, we assessed the impacts of stock market development, per capita income, trade expansion, renewable energy solutions, and technological innovations on carbon intensity in the four South Asia countries from 1990 to 2016. The empirical results based on the CS-ARDL approach revealed that stock market development, per capita income, and trade expansion invigorated carbon intensity in the South Asian countries. On the contrary, the increased usage of renewable energy solutions and technological advancement helped in reducing the energy-led carbon intensity. Further, the interaction of stock market with renewable energy, and subsequently with technological advancement delivered insignificant coefficients, which indicates the inefficacy of renewable energy and technological advancement in regulating stock market-led carbon intensity during the study period. Therefore, by considering the need for complementarity between economic growth and environmental targets, we proposed a multipronged policy framework, which may help the selected countries to attain the Sustainable Development Goals, with a special focus on SDG 7, 8, 9, and 13.

Carbon tax and energy innovation at crossroads of carbon neutrality: Designing a sustainable decarbonization policy.

Decarbonation has been a primary policy prerogative for Sweden, and carbon tax has been a primary policy instrument in this pursuit, and the revenue generated out of carbon tax has been a driver for energy innovation. However, the benefits of energy innovation have not been experienced across various sectors in Swedish economy, and it might be anticipated that the potential aim of achieving carbon neutrality might not be accomplished to the fullest. Hence, being faced with the need of policy realignment for Sweden, this study has made an attempt to discover the dynamics between carbon tax revenue and energy innovation over a period of 1990-2019, following Quantile-on-Quantile Regression framework. The results obtained from the study show that the impact of carbon tax revenue on energy innovation might turn out to be ineffective beyond a certain threshold limit. A similar pattern has also been observed for the impact of energy innovation on carbon tax revenue. This study gives an indication that there might be a non-linear association between both these model parameters. The study outcomes have paved a way to design a policy framework for helping Swedish economy to attain the objectives of Sustainable Development Goals, while paving the ways to achieve carbon neutrality.

Examining the nexus between export diversification and environmental pollution: evidence from BRICS nations.

In recent years, industrial growth has enabled the BRICS nations to increase their export earnings from both traditional and new products. However, in terms of modernization of industries, these nations can be considered as laggards, because the present production processes appear to be carbon-intensive and energy-inefficient. In this backdrop, the present study, by using the second-generation econometric procedures, is intended to examine the impact of industrialization, export diversification, technological innovation, income inequality, and resource rents on the carbon dioxide emissions in the BRICS nations from 1990 to 2018. The long-run coefficients revealed that the industrial expansion, reduction in export diversification, low concentration on traditional exports, and high concentration on new exports exacerbated the air quality in the BRICS nations. On the other hand, technological advancement contributed to restoring environmental quality during the study period. Furthermore, it is observed that the present research endeavors in the BRICS nations are insufficient in circumventing industrial pollution, as the value of the joint coefficient of technological advancement and industrialization is found insignificant but negative. Hence, based on the computed results, a multipronged policy framework is proposed, so that these nations can achieve the targeted sustainable development goals (SDGs) in the coming years.

Does green financing help to improve environmental & social responsibility? Designing SDG framework through advanced quantile modelling.

Striving to achieve the Sustainable Development Goals (SDGs), countries are increasingly embracing a sustainable financing mechanism via green bond financing. Green bonds have attracted the attention of the industrial sector and policymakers, however, the impact of green bond financing on environmental and social sustainability has not been confirmed. There is no empirical evidence on how this financial product can contribute to achieving the goals set out in Agenda 2030. In this study, we empirically analyze the impact of green bond financing on environmental and social sustainability by considering the S&P 500 Global Green Bond Index and S&P 500 Environmental and Social Responsibility Index, from October 1, 2010 to 31st July 2020 using a combination of Quantile-on-Quantile Regression and Wavelet Multiscale Decomposition approaches. Our results reveal that green financing mechanisms might have gradual negative transformational impacts on environmental and social responsibility. Furthermore, we attempt to design a policy framework to address the relevant SDG objectives.

Does financial development reinforce environmental footprints? Evidence from emerging Asian countries.

In the preceding two decades, the expansion of financial services has played a vital role in pursuing economic growth agendas in the developing Asian nations. However, its harmful effect on environmental quality cannot be denied. In this backdrop, in the present study, we investigated whether the financial sector development moderated the ecological footprint, carbon footprint, and land footprint in the eight developing nations of South and Southeast Asia from 1990 to 2015. In doing so, we included the per capita income, energy solutions, and trade expansions as determinants of the ecological indicators. The results of the second-generation unit root tests and Westerlund's cointegration test reported the long-run stability and cointegration, respectively. To navigate the possible cross-country dependency, we employed the cross-sectional augmented autoregressive distributed lag approach (CS-ARDL). The results confirmed that per capita income, energy solutions, trade expansion, and financial sector development invigorated the ecological footprint, carbon footprint, and land footprint in the long run. Further, it is reported that the development in the financial sector has a significant moderating impact on the nexus between energy and environmental footprints. In other words, the financial sector development drove the association between the overall environmental quality and energy solutions in the long run. Similarly, we observed that the financial sector development worked as a significant mediator between environmental proxies and trade expansion. By including the ecological footprint, carbon footprint, and land footprint as environmental proxies, the study provides the wider environmental spectrum. Based on the outcomes of the study, we proposed a novel scheme, which may help to address the harmful environmental impacts of the financial sector development in the selected developing nations.

Examining the impacts of economic and demographic aspects on the ecological footprint in South and Southeast Asian countries.

The re-examination of the existing economic and environmental policies in the South and Southeast Asian countries seems to be necessary, as these countries are struggling to achieve the goals of sustainable development. For designing a long-term environmental policy, we intended to examine whether the selected economic and demographic indicators have influenced the ecological footprint in the eight developing countries of Asia from 1990 to 2015. The use of pooled mean group (PMG) approach allowed driving the long-run common coefficients, which may facilitate us to develop a common policy framework for fortifying the environmental quality. The computed results confirmed that the selected variables are cointegrated in the long run, and the variables, i.e., per capita income, nonrenewable energy usage, urbanization, fertility rate, and population density are observed as the significant drivers of the environmental pollution. Moreover, the consumption of renewable energy restored the environmental quality in these countries. Based on the results, we recommended the need for the diversification of the energy-basket for enhancement of the use of renewable energy resources. Further, through sensitization of the necessity of environmental conservation, the governments should promote less carbon-intense economic and demographic practices across the industries and sectors.

The relationship between economic growth and carbon emissions in G-7 countries: evidence from time-varying parameters with a long history.

This paper re-investigates the time-varying impacts of economic growth on carbon emissions in the G-7 countries over a long history. In doing so, the historical data spanning the period from the 1800s to 2010 (as constructed) for each country is examined using the time-varying cointegration and bootstrap-rolling window estimation approach. Unlike the previous environmental Kuznets curve (EKC) studies, using this methodology gives us avenue to detect more than one, two, or more turning points for the economic growth-carbon emissions nexus. The empirical findings show that the nexus between economic growth and carbon emission seems over a long history to be M-shaped for Canada and the UK; N-shaped for France; inverted N-shaped for Germany; and inverted M-shaped (W-shaped) for Italy, Japan, and the USA. In addition, the possible validity of EKC hypothesis is examined for both the pre-1973 and post-1973 sub-periods. Based on this investigation, we found that an inverted U-shaped is confirmed only for the pre-1973 period in France, Italy, and the USA. These empirical evidences provide new insights to policy makers to improve environmental quality using economic growth as an economic tool for the long run by observing changes in the environmental impact of this growth from year to year.

Analyzing technology-emissions association in Top-10 polluted MENA countries: How to ascertain sustainable development by quantile modeling approach.

This study investigates the relationship between technological progression and ambient air pollution in top-10 polluted Middle East and North African (MENA) countries by using monthly data for the period of 1990-2017. The Quantile cointegration proposed by Xiao (2009), Quantile-on-Quantile regression (QQ) proposed by Sim and Zhou (2015), and Quantile Autoregressive Granger causality developed by Troster et al. (2018) are applied. In particular, we examine to which extent, quantiles of technological progression affect the quantiles of ambient air pollution, by developing separate indicators for both the mentioned aspects using Principal Component Analysis (PCA). Our empirical findings unfold mutual dependence between technological progression and ambient air pollution. Furthermore, the results of Quantile Autoregressive Granger causality test conclude a bidirectional causal relationship between technological progression and ambient air pollution.

Analyzing the association between innovation, economic growth, and environment: divulging the importance of FDI and trade openness in India.

The objective of this paper is to explore the nexus of innovation-environment and economic growth in the context of the Indian economy. To achieve the study objective, we explored the role of technological innovation, FDI, trade openness, energy use, and economic growth toward carbon emissions. Using the data of 1985-2017, the study employed ARDL bound testing and vector error correction model (VECM) methods to capture the effects of technological innovation, trade openness, FDI, energy use, and economic growth on CO2 emissions. Empirical estimation has confirmed the existence of long-run cointegration. Similarly, in the long run, it is found that trade openness, energy use, and economic growth positively reinforce CO2 emissions. In contrast, technological innovation and FDI negatively reinforce CO2 emissions in the long run. Furthermore, VECM indicates that the relationship among innovation, trade openness, and energy use is bidirectional in the long run. Whereas, unidirectional relation has been found that is coming from GDP to carbon emissions, FDI, innovation, trade, and energy use. In the short run, unidirectional link found which is coming from FDI, innovation, and energy use to carbon emission. However, the association between emissions and trade openness is bidirectional. The conclusions put forward policy implications that innovation is a way to reduce environmental degradation.

Tourism and inequality in per capita water availability: is the linkage sustainable?

This paper shows the bilateral association between tourism development and inequality in per capita availability of water. The study is conducted on the countries with high tourism receipt, and thereafter, this study shows whether the directions of tourism development in these countries are going to be sustainable or not. In order to achieve this, we have used tourism investment and tourism receipt as two indicators of tourism development and have assessed their differential impacts on the disparity in water availability by applying DOLS and causality analysis approach. Empirical results show long-run impact of tourism on inequality in per capita availability of water, along with the presence of bidirectional causal association among the tourism development and inequality parameters. This study further reveals the impact of tourism on the regional disparity in distribution of water that can appear due to the differential approach taken toward tourism development. Based on study outcomes, several policy directions where offered for the investigated blocs.