Linking tourist's footprint and environmental tragedy through transportation, globalization and energy choice in BIMSTEC region: Directions for a sustainable solution using novel GMM-PVAR approach.

The rising temperature in the world's atmosphere is an outcome strongly linked to man-made manufactured interventions. Recreational activities in the form of tourism are such interventions that can unleash multidimensional negative externalities if not regulated properly. The Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) region has become one of the major hubs for recreational activities in the last few decades. However, the region's tourism-led environmental degradation has received scant attention in the literature. As such, this paper unveils how tourist footprint affects the region's environmental sustainability and explores potential solutions to encourage the tourism industry to be more pro-environmental. We have used the novel GMM-PVAR technique to assess how globalization, transportation, green energy, and economic growth have affected the tourism industry and carbon footprint in the BIMSTEC region from 1990 to 2019. We lean on the empirical outcomes to propose regional sustainable tourism development policies. The GMM-PVAR model indicates that renewable energy, economic growth, and the transportation sector's development positively affect the tourism industry's growth in the region. However, globalization and environmental degradation negatively influence tourists' arrival. Contrarily, transportation services, economic growth, and tourism boost the carbon footprint in the region. Although globalization and clean energy reduce carbon footprint, these indicators are insignificant, indicating that this region is still lagging in renewable energy generation and failed to reap the positive spillovers of globalization. Based on these outcomes, we propose that the region redesign its tourism industry to encourage eco-friendly tourism by leaning more on pro-environmental strategies (i.e., powering the tourism industry through the penetration of renewable energies) and tightening environmental regulations.

Understanding multidimensional poverty in pakistan: implications for regional and demographic-specific policies.

This study enriches the limited literature on multidimensional poverty by focusing on household demographic characteristics as determinants of household-specific living arrangements in Pakistan. The study employs the Alkire and Foster methodology to measure the multidimensional poverty index (MPI) using data drawn from the latest available nationally representative Household Integrated Economic Survey (HIES 2018-19). The analysis investigates multidimensional poverty levels among households in Pakistan according to various criteria (such as access to education and healthcare, basic living standards, and monetary status) and how they differ across Pakistan's regions and provinces. The results indicate that 22% of Pakistanis are multidimensionally poor in terms of health, education, basic living standards, and monetary status; and that multidimensional poverty is more common in rural areas and Balochistan. Furthermore, the logistic regression results show that households with more working-age people, employed women, and employed young people are less likely to be poor, whereas households with more dependents and children are more likely to be poor. This study recommends policies for addressing poverty that consider the needs of multidimensionally poor Pakistani households in various regions and with various demographic characteristics.

Household fuel choices and consumption intensity in Pakistan: evidence from HIES data 2001-2019.

The adoption of clean energy (electricity and gas) for domestic purposes has increased over the decades, yet the share of clean energy in total energy consumption remains low. Therefore, this study analyses seven rounds of HIES surveys in Pakistan collected between 2001 to 2019 to understand the energy use patterns and why clean fuel consumption is low among households that have already adopted clean energy. To this end, the present study applied the Probit and Tobit models to examine the determinants of using different fuel types and their consumption intensity. The results show that female-headed households are more likely to adopt and consume more clean fuels such as electricity and gas. Moreover, education, wealth, and urban location have a positive association with clean fuel adoption and consumption. The study also finds that age and household size have a non-linear impact on clean fuel consumption intensity. The study recommends policies to achieve SDG 7 by improving accessibility and affordability by increasing income and the supply of clean fuel. Further, it emphasizes enhancing the knowledge about the benefit of using clean energy through education programs.

Is the environmental Kuznets curve valid for transport sector in Pakistan? New evidence for non-renewable energy and urbanization using the QARDL approach.

The transportation industry is a significant contributor to greenhouse gas emissions, particularly carbon dioxide. This study broadens the literature on environmental Kuznets curve (EKC) by assessing Pakistan's carbon dioxide emissions in the transport sector taking into account the impact of non-renewable energy, urbanization, and economic growth for the period of 1995-2018 using the novel QARDL model. Moreover, the outcomes of the study make a momentous benefaction to the literature by focusing a sector that contributes substantially to pollution in Pakistan. Specifically, the study finds that the EKC curve is confirmed for Pakistan's transportation sector in moderate to higher quantiles. Urbanization and non-renewable energy are also two other vital ingredients that dramatically aggravate the destruction of the environment. Except for the lowest (0.05th-10th) and highest (90th-95th) quantiles, urbanization affects transport-based carbon pollution positively. The study concludes by proposing some policy interventions for Pakistan.

Examining the nonlinear impact of human capital on environmental degradation in N-11 countries: an application of the PSTR approach.

The emergence of globalization and human capital has played a crucial role in the economic integration of countries, leading to the growth of the economies and a reduction in carbon dioxide (CO2) emissions. This study highlights the importance of investing in human capital development to control ecological degradation and promote sustainable economic growth. This paper employs the PSTR method to investigate the threshold impact of GDP, globalization, information communication technology, and energy consumption on CO2 emissions. The study examines two regimes, with a single threshold to analyze the transition of human capital on these variables. The results reveal that human capital developments play a central role in controlling ecological degradation due to reduced CO2 emissions. Based on the empirical findings, this research study offers corresponding policy suggestions.

The spatial impact of digital economy on energy intensity in China in the context of double carbon to achieve the sustainable development goals.

Using the provincial panel data of China during 2012-2019, the present study employed spatial Durbin error model to explore the spatial effect of the digital economy on energy intensity. The results show that both digital economy and energy intensity have spatial autocorrelation, showing the distribution characteristics of spatial aggregation. The digital economy has a significant negative influence on energy intensity. The result shows a significant spatial spillover effect of digital economy on energy intensity, and the development of the digital economy in neighboring regions reduces energy intensity in the central region. Additionally, industrial structure, urbanization, energy price, and foreign direct investment have a heterogenous impact on energy intensity. Thus, it is crucial to give importance to the development of the energy intensity, plan the spatial layout of the digital industry as a whole, drive the coordinated growth of the regional digital economy, quicken the upgrading of industrial structure, promote urbanization, perfect the energy price formation mechanism, raise the entry threshold for foreign direct investment, to effectively reduce the energy intensity, and facilitate the smooth realization of the "double carbon" goal.

Hydropower, human capital, urbanization and ecological footprints nexus in China and Brazil: evidence from quantile ARDL.

The relations among ecological footprints, biocapacity per capita, gross domestic product per capita, natural resources, urbanization, human capital, and hydroelectric consumption are analyzed from 1971Q1 to 2017Q4 for Brazil and China. The novel quantile autoregressive distributive lag method was employed to analyze the long-run and short-run dynamics of environmental degradation. The findings revealed that economic growth has a positive role in the environmental degradation of both countries. However, human capital, natural resources, and hydropower have heterogeneous effects across quantile distribution and between the two countries. Based on the quantile dynamics of environmental degradation, the present study mentions policy implications for sustainable development.

Revisiting global energy efficiency and CO2 emission nexus: fresh evidence from the panel quantile regression model.

Given the importance of energy efficiency in environmental degradation, the effects of energy efficiency and renewable and nonrenewable energy consumption on global environmental pollution were investigated. For this purpose, panel data from 107 countries from 1996 to 2014 were examined. In addition, the present study also tested the well-known environmental Kuznets curve (EKC). The long-run relations were estimated by applying a panel quantile regression (PQR) approach, which is useful for finding heterogeneous effects at lower- and upper-level quantiles of CO2 emissions. The empirical results indicated that energy efficiency had a significantly negative impact on CO2 emissions with low intensity at higher-level quantiles.Furthermore, the impact of renewable and nonrenewable energy consumption on environmental degradation was significantly negative and positive across all quantiles, respectively. The empirical results provide evidence supporting an inverted U-shaped nexus between GDP and CO2, whereby the EKC is found valid. Hence, energy efficiency improvement and renewable energy consumption policies must align with strategies to curb environmental degradation.

The nonlinear links between urbanization and CO2 in 15 emerging countries: Evidence from unconditional quantile and threshold regression.

The extant literature has provided empirical evidence about the relationship between urbanization and the environment; however, little attention has been paid to the non-linear relationship among them. This study aims to measure the effects of urbanization on carbon dioxide emission using quantile and threshold regression methods. To this end, the study employed threshold analysis and quantile regression methods in a sample of 15 emerging economies from 1995 to 2015 and analyzed the variation of such non-linearity at different levels of carbon dioxide. The results illustrate that a single threshold and two regimes exist and the threshold for urbanization is 29.56%. Among the two regimes, the elasticity estimates form an inverted U-shape impact of urbanization on carbon dioxide emission. The increase in the marginal effect of urbanization on carbon dioxide emissions up to the median level and a declining trend after this level implies that environmental quality is likely to improve in the emerging countries.

Does financial development reinforce ecological footprint in Singapore? Evidence from ARDL and Bayesian analysis.

Singapore has been ranked in the most dynamic financial market and the highest ecological deficit country, indicating that the trade-off hypothesis may exist. The main goal of the present study is to probe the impact of financial development, economic growth, and human capital on ecological footprint in Singapore from 1980 to 2016. The outcomes obtained from the Autoregressive Distributed Lag (ARDL) method have failed to provide a clear impact of financial sector development on ecological footprint. However, the Bayesian analysis reveals that both financial development and economic growth have a harmful influence on EF, while the impact of human capital is beneficial. A theoretical conclusion derived is that monetary expansion policies should be associated with improving human capital to achieve the United Nations SDGs in the context of Singapore. The findings of the study are of particular interest to policymakers for developing sound policy decisions for sustainable economic progress which is not at the cost of environment.

The roles of economic growth and health expenditure on CO2 emissions in selected Asian countries: a quantile regression model approach.

Continuous economic growth and the rise in energy consumption are linked with environmental pollution. Demand for health care expenditure increased after the COVID-19 pandemic. This study is interesting in modeling the nexus between public and private health expenditure, carbon dioxide emissions, and economic growth. To this end, the present study analyzed the nexus between public and private health care expenditure, economic growth, and environmental pollution for 36 Asian countries for the period 1991-2017. FMOLS, GMM, and quantile regression analysis confirm the EKC hypothesis in Asia. Besides, FMOLS and quantile regressions reached the reducing effects of government and private health expenditures on CO2 emissions. While quantile regression results show that public and private health expenditures can mitigate CO2 emissions; however, these results differ for various levels of CO2. Findings of quantile regression show a significant impact of both public and private health expenditures in reducing CO2 at the 50th and 75th quantiles but results are insignificant for the 25th quantile. Overall, the paper concludes that both government and private health sectors' expenditures caused CO2 emissions to decrease in Asia and that the negative impact of the private health sector on CO2 emissions is greater than that of the government health sector. The concluding remark is that the higher the health spending, the higher the environmental quality will be in Asia. Hence, the health administrators need to increase public and private health expenditures with an effective cost-service and energy-efficient management approach to reach sustainable health services and a sustainable environment in Asia.