Optimal environmental investment strategies for enterprise green technology innovation: An empirical study based on multiple drive models.

Enterprise green technology innovation (GTI) is vital for global sustainable development. However, the optimal strategies are needed to understand how environmental investments (EIs) impact enterprise GTI. This study adopts multiple drive models to explore the impact of EIs on the GTI of A-share listed enterprises in China from 2008 to 2022.

Digital finance and sustainable development: Evidence from developing nations.

Objectives: This paper investigates the role of digital finance in promoting environmental sustainability within a group of 52 developing economies from 2010 to 2019. Specifically, it examines whether digital finance effectively contributes reducing CO emissions in these nations.

Methods: This paper is a quantitative study which employs the IV-GMM (instrumental variable generalized methods of moment) approach that tackles any potential endogeneity.

Regional policy options for carbon peaking in the Yangtze River Delta under uncertainty.

The Yangtze River Delta (YRD) region plays a crucial role in achieving China's carbon peaking goal. However, due to uncertainties surrounding future economic growth, energy consumption, energy structure, and population, the attainment of carbon peaking in this region remains uncertain. To address this issue, this study utilized the generalized Divisia index method to analyze the driving factors of carbon emissions, including economy, energy, investment, and population.

Towards energy conservation by constructing more transportation infrastructure?: An endogenous stochastic frontier analysis framework.

Whether constructing more transportation infrastructure can be helpful for the achievement of energy conservation is a long-running and debatable issue. To answer this question, the relationship between transportation infrastructure and energy efficiency must first be clarified. Nonetheless, the existence of the endogeneity problem poses a challenge to defining the relationship.

Forecasting carbon emissions future prices using the machine learning methods.

Due to the uncertainty surrounding the coupling and decoupling of natural gas, oil, and energy commodity futures prices, the current study seeks to investigate the interactions between energy commodity futures, oil price futures, and carbon emission futures from a forecasting perspective with implications for environmental sustainability. We employed daily data on natural gas futures prices, crude oil futures prices, carbon futures prices, and Dow Jones energy commodity futures prices from January 2018 to October 2021. For empirical analysis, we applied machine learning tools including traditional multiple linear regression (MLR), artificial neural network (ANN), support vector regression (SVR), and long short-term memory (LSTM).

Financial inclusion, renewable energy consumption, and inclusive growth: cross-country evidence.

The COVID-19 pandemic has affected the global economy to varying degrees. Coupled with the widening gap caused by the unbalanced distribution of resources, the sustainability and inclusiveness of economic growth have been challenged. To explore the influencing factors of the level of economic inclusive growth among different countries, we used the spatial Durbin model to analyze the relationship between financial inclusion, renewable energy consumption, and inclusive growth based on panel data of 40 countries from 2010 to 2020.

Can environmental regulations break down domestic market segmentation? Evidence from China.

While local protectionism and market segmentation owing to fiscal decentralization are not conducive to broad economic development, they may be rational choices on a local scale. Based on a spatial Durbin model, we analyzed the relationship between environmental regulations and market segmentation in China using interprovincial panel data for 2004-2018. The results indicated that the "beggar-thy-neighbor" phenomenon persists in China; environmental regulations have a U-shaped impact on market segmentation, i.

Exploring the role of green innovation and investment in energy for environmental quality: An empirical appraisal from provincial data of China.

To better analyze China's carbon neutrality target, this study investigates the effect of green innovation and investment in the energy industry on China's provincial and regional data from 1995 to 2017. Using Westerlund and Edgerton's panel cointegration test, the authors found a stable long-run relationship between CO emissions and its determinants. We found that under major structural breaks at the local, regional, and global levels, such as the East Asian crises of 1997, the financial crises of 2007-2008, China's RMB exchange rate reform announced on August 11, 2015, and mild recession in 2001, CO emissions, income, green innovation, renewable energy use, and energy industry investment are cointegrated.