Search

This paper introduces a new green decomposition model of carbon productivity that aims to further analyze the regional differences in carbon productivity and its interaction with regional industrial performance. We combine desired outputs and undesired outputs orientation, and multiple factor inputs to derive a new green decomposition theorem, establish a new green decomposition model of carbon productivity, and obtain nine effects of regional carbon productivity differences. Empirical analysis is conducted using input-output data from 29 provinces and 15 industries in China, comparing the differences in carbon productivity from both the provincial and industry perspectives and exploring the mechanism of action. This paper provides theoretical basis and empirical evidence for regional carbon productivity enhancement and economic and industrial optimization from the perspective of multi-factor inputs, as well as policy insights for regional low-carbon transition development. [ABSTRACT FROM AUTHOR]

The advancement of Financial Technology (FinTech) is crucial for government entities, the National Grid, and various energy corporations to facilitate the transition towards sustainable and green production methods. This study investigates the relationship between FinTech and Total Factor Energy Efficiency (TFEE) using data from a selected sample of 254 city groups in China. We examine how the development of FinTech impacts TFEE from both non-spatial and spatial perspectives. The results from the non-spatial panel model indicate that FinTech development has a significant positive impact on TFEE. Comparative studies were conducted using fixed effects (FE), feasible generalized least squares (FGLS) models, and system generalized method of moments (GMM) models, and the main findings remained consistent, confirming the robustness of our conclusions. Spatial autocorrelation results reveal a significant positive spatial spillover effect on TFEE. Both the spatial Durbin model and the dynamic spatial Durbin model demonstrate that FinTech also has a significant positive impact on TFEE, and this effect increases over time. These conclusions remain robust even after considering various spatial weight matrices and alternative methods for calculating TFEE. Additionally, we discovered that the digital economy plays a vital role in strengthening the relationship between FinTech and TFEE. Heterogeneity analysis indicates that, compared to cities without resource-based economies, FinTech development in growing resource-based cities has a more substantial impact on TFEE. [ABSTRACT FROM AUTHOR]

Under the fiscal decentralization of government environmental management, this paper investigates the relationship between local environmental protection expenditure (LEPE) and CO2 ecological footprint (CEF). Unlike conventional emissions-based greenhouse gas metrics, this research calculates per capita CEF for 253 Chinese cities, considering both carbon emissions and absorption. The dynamic spatial Durbin model demonstrates that LEPE not only reduces a city's own CEF but also exerts a long-term influence on neighboring cities, signifying competitive dynamics among local governments in LEPE. This decentraliztion of environmental budget authority may yield adverse outcomes. Further analysis reveals an inverted U-shaped relationship between CEF and LEPE intensity, partly mirroring the environmental Kuznets curve. Different developmental stages should consider economic levels when allocating resources to environmental budgets. The low-carbon pilot policy strengthens LEPE, with varying effects across Chinese urban agglomerations, remaining consistent post-environmental protection tax introduction. These findings hold critical reference value for local policymakers aiming to collaboratively adjust market-oriented environmental policies. [ABSTRACT FROM AUTHOR]

Abstract Carbon emission rights allocation affects the effective operation of carbon trading system, and then the achievement of energy saving and emissions reduction objectives. Reasonable allocation scheme should meet the principle of justice. Carbon emission rights allocation based on energy justice is a novel and worth discussing subject. This paper explores the optimization of carbon emission rights allocation based on energy justice. The justice-based model is built with the aid of Gini coefficient. The way to optimize allocation scheme with constraints of population, ecological productive land, fossil energy resources and GDP is discussed. Results show that fossil energy resources and ecological productive land play more important role in the allocation. The prime example is Inner Mongolia, its quota percentage change reaches up to 150.01%. As the GDP and population growth rate are fixed in a given interval, the quota allocation in eastern China shows some interesting results. When the GDP growth rate is 6.25%, the quotas of eastern China will not change with varying population growth rate. The allocation will enter a relative stable stage as the population growth rate is greater than or equal to 6.4‰. These results can provide China with experience to deal with the new problem appeared in carbon trading system like two-children policy and the new normal of economic growth. Highlights • Energy justice-based carbon emission allocation with multiple constraints is explored. • Provincial allocation results in China are related to location-related factors. • Two-children policy has effect on optimal allocation results in eastern China. • The critical values of population and economic growth rate in this model are found. [ABSTRACT FROM AUTHOR]