The impact of human capital and bio-capacity on the environmental quality: evidence from G20 countries

Renewable energy and ecological footprint nexus: Evidence from dynamic panel threshold technique

The escalating phenomenon of environmental degradation is an urgent global concern, imperiling ecosystems and hindering the prospects for sustainable development on a planetary scale. Therefore, this study aims to explore the intricate interplay between renewable energy (RE) and ecological footprint (EF), considering the conditional impact of fiscal capacity (FIC), human development (HDI), institutional quality (IQI), and population density (PDN). Drawing on panel data encompassing 74 developing countries from 2000 to 2022, the study employs a dynamic panel threshold regression method, both with and without an instrumental variable approach. The findings unveil a non-linear nexus between RE and EF, revealing significant threshold values for FIC (1.870), HDI (0.736), and IQI (0.311), above which RE showcases its efficacy in mitigating EF. Conversely, when these predictors dip below the thresholds of FIC (1.391), HDI (0.655), and IQI (0.2545), the impact of RE on FE becomes insignificant. Moreover, the study introduces PDN as an additional threshold variable in the analysis, pinpointing that the effectiveness of RE in reducing EF hinges on PDN being below a threshold value of 263.144; however, above a threshold value of 276.98, the influence of PDN on the RE-FE nexus diminishes. The findings underscore the complexity of policy landscapes in developing countries. They suggest that while promoting renewable energy is pivotal for environmental sustainability, it is equally imperative to bolster existing environmentally friendly fiscal capacity, advance human capital, enhance institutional quality, and craft effective population distribution policies.

Trade openness, human capital, natural resource, and carbon emission nexus: a CS-ARDL assessment for Central Asian economies

There is a call for global efforts to preserve the ecological systems that can sustain economies and people's lives. However, carbon emission (CEM) threatens the sustainability of humanity and ecological systems. This analysis looked into the influence of energy use (ERU), human capital (HCI), trade openness (TOP), natural resource (NRR), population, and economic growth (ENG) on CEM. The paper gathered panel data from the Central Asia region from 1990 to 2020. The CS-ARDL was applied to establish the long-term interaction among the indicators. The paper's findings indicated the presence of the environmental Kuznets curve (EKC) in the Central Asia regions. Also, the empirical evidence highlighted that energy use, natural resources, and trade openness cause higher levels of CEM. However, the research verified that CEM can be improved through human capital and urban population growth. The study also found that HCI moderates the interaction between NRR and CEM. The causality assessment indicated a one-way interplay between ENG, ERU, NRR, and CEM. The study proposes that to support ecological stability in these regions, policy-makers should concentrate on developing human capital, investing in renewable energy sources, and utilizing contemporary technologies to harness natural resources in the economies of Central Asia.

Forecasting the ecological footprint of G20 countries in the next 30 years

The Ecological Footprint evaluates the difference between the availability of renewable resources and the extent of human consumption of these resources. Over the past few decades, historical records have shown an accelerated decline in the availability of resources. Based on national footprint and biocapacity accounts, this analysis aims to advance the forecasting of the G20 countries' ecological footprints over a 30-year time frame. We employed a time series forecasting approach implemented in Python, which included-modular regression (Prophet) and Autoregressive Integrated Moving Average (ARIMA & Auto-ARIMA) methods. We evaluated and combined the performance of these three methods. The results indicated that among the largest economies of the G20, only four countries are projected to have a positive ecological footprint balance by 2050. These countries share the common denominator of large land areas and a moderate population growth projection. However, the overall trend of the indicator suggests that it will continue to decline.

Determinants of ecological footprint in European countries: Fresh insight from Bayesian model averaging for panel data analysis

This study examines the determinants of the ecological footprint of production in European countries from 1992 to 2020. Using partial and semipartial correlation analyses and Bayesian Model Averaging (BMA) approach for the first time, the research identifies key variables affecting ecological footprint. Using Bayesian methods, posterior inclusion probabilities (PIPs) were calculated for each variable's coefficient estimates, revealing their relative importance. Biocapacity, energy consumption, industrialization, financial development, life expectancy, and globalization displayed notably high PIPs, indicating their strong influence on the ecological footprint. In addition, the study employs cointegration tests to examine the long-run relationship between ecological footprint and explanatory variables. The results indicate significant cointegration between these variables across panels, supported by various test statistics. In the Weighted Pooled DOLS estimation, biocapacity, energy consumption, and life expectancy significantly influence the ecological footprint, while industrialization, financial development, and globalization exert a comparatively smaller impact. Researchers and policymakers should consider these determinants for effective sustainable development planning. These findings underscore the intricate interplay of factors shaping the ecological footprint and offer insights for effective policy interventions towards sustainable development.

Effects of Human Capital on Energy Consumption: The Role of Income Inequality

High-quality human capital (HC) development has a strong influence on achieving a win-win target of economic growth and energy consumption mitigation based on the background of the contemporary "carbon neutrality" constraints in China. We here aim to empirically assess the effect of HC on energy consumption (EC) in 30 provinces of China from 2000 to 2019. Moreover, we broaden the literature by discussing the effect of HC in terms of impact mechanism and nonlinear relationship. Based on methods of the augmented mean group (AMG), the estimation of long-term impacts indicates that the improvement of HC significantly discourages the increase in EC. The intrinsic mechanism shows that the accumulation of HC significantly promotes the decline of EC through economic structure adjustment and technological innovation. Moreover, the threshold model indicates that income equality lifts the inhibitory impact of HC on EC. Accordingly, the development of HC should be involved in the policy preference of China's provincial and national development strategies considering its effectiveness in stimulating the reduction of energy consumption.

Renewable and Non-Renewable Energy Consumption and Trade Policy: Do They Matter for Environmental Sustainability?

In the extant literature, there are numerous discussions on China’s environmental sustainability. However, few scholars have considered renewable energy consumption and trade policy simultaneously to debate environmental sustainability. Therefore, this paper attempts to examine how renewable and non-renewable energy consumption, bio-capacity, economic growth, and trade policy dynamically affect the ecological footprint (a proxy for environmental sustainability). Using the data from 1971 to 2017 and employing the auto-regressive distributed lag model to perform an empirical analysis, the results demonstrate that renewable energy consumption and trade policy are conducive to environmental sustainability because of their negative impacts on the ecological footprint. However, the results also indicate that bio-capacity, non-renewable energy consumption, and economic growth are putting increasing pressure on environmental sustainability due to their positive impacts on the ecological footprint. Moreover, to determine the direction of causality between the highlighted variables, the Yoda-Yamamoto causality test was conducted. The results suggest a two-way causal relationship between renewable energy consumption and ecological footprint, non-renewable energy consumption and ecological footprint, and economic growth and ecological footprint. Conversely, the results also suggest a one-way causal relationship running from bio-capacity and trade policy to the ecological footprint.