How do land supply admittance regulations affect urban carbon emissions?

The rationalization of land resource utilization, affected by increasing stringent guidance of urban land supply regulations, is a vital path for countries to achieve their sustainable development goals. However, evidence on environmental effects of land supply regulations is scarce. Thus, adopting China's land supply policy, we investigate the impact of land supply admittance regulations (LSARs) on urban carbon emissions (UCEs) by using the land market transaction data and carbon emission data of China's 285 cities from 2007 to 2019. The result shows that LSARs notably curb UCEs, with UCEs decreasing by 0.051 standard units (approximately 1.052 g CO2 per RMB) for each 1 standard unit increase in LSARs. After introducing the instrumental variable to deal with endogenous issues, this conclusion remains robust. Mechanism analysis indicates that the carbon abatement effect of LSARs is through structural and efficiency two main channels: the industrial structure advancement from quantity and quality; the green production efficiency from scale and technology. Furthermore, heterogeneity results demonstrate that the reduction effect varies in admittance regulations setting, government intervention, land supply marketization, and environmental regulations. Our findings provide valuable insights for other economies seeking to adopt land-based policy instruments for carbon governance and urban sustainability.

How does new urbanization affect urban green total factor productivity? A perspective based on coordinated development.

China's new urbanization strategy serves as a key instrument for achieving sustainable development goals in urban areas. However, a consensus on how and whether new urbanization affects urban green total factor productivity (GTFP) has yet to be reached. This analysis targets 276 prefecture-level and above cities, using panel data from 2011 to 2019 to assess the impact of the new urbanization pilot policy (NUPP) on GTFP. The research findings demonstrate that implementing China's NUPP has significantly enhanced urban GTFP. Furthermore, the population-land-industry coupling coordination degree (PLICCD), as well as the industry-environment-economy coupling coordination degree (IEECCD), play crucial facilitating roles in the aforementioned enhancement effects. The results remain robust even after employing PSM-staggered difference-in-differences (DID) estimation and excluding other policy interferences. Furthermore, heterogeneity analysis, based on urban characteristics, reveals that the NUPP significantly enhances GTFP in resource-based, non-resource-based, industrial, non-intensive compactness, and non-expansionary urbanization cities. Finally, the paper offers three policy recommendations. First, new urbanization initiatives should be more actively promoted in China and other developing countries. Second, the construction of new urbanization plans should focus on the coordinated development of "population-land-industry" and "industry-environment-economy." Third, the government should implement new urbanization initiatives tailored to the specific characteristics of different cities. This study provides valuable insights for the general public, policymakers, and scholars to better understand the potential of coordinating the development of population, land, industry, the environment, and the economy to improve GTFP. Moreover, it offers a broad perspective for evaluating sustainable urban development.

An Application of Analytic Hierarchy Process and Entropy Weight Method in Food Cold Chain Risk Evaluation Model.

The food cold chain is a special type of cold chain that refers to a system in which refrigerated and frozen food is always kept in the specified low-temperature environment in all links from production, storage, transportation, sales, distribution to consumption, so as to ensure food quality and to prevent food deterioration caused by temperature fluctuation. In recent years, the coronavirus disease 2019 (COVID-19) has brought a great impact on people's life and the social economy and also threatened the large-scale food cold chain. Through the effective identification and evaluation of high-risk factors in the food cold chain, this article has found the major risks that have a great impact on the entire food cold chain and proposes the specific measures of risk management and control to solve the problems of food cold chain and reduce risks quickly and efficiently to ensure the stability and safety of food cold chain and avoid the serious food safety accidents. The contribution of this article is reflected in three aspects, namely, (1) applies the expert system based on professional knowledge and rich experience and constructs a classification and identification system structure of food cold chain risk indexes, which lay a foundation for further identifying and evaluating the major risks of the food cold chain; (2) designs a comprehensive index weighting method combining the AHP method and entropy weight method to quantitatively evaluate the major risks. This comprehensive method combines a hierarchical structure system, evaluation algorithm, subjective factor correction algorithm, and so on. The evaluation results are more accurate, have a high matching degree with reality, and have good theoretical and practical significance; (3) analyzes and explains the major risks of the food cold chain in the non-epidemic situations and COVID-19 situations. Proposals and measures for risk management and control are put forward, which have wide practical significance.

Analysis of regional differences and dynamic mechanisms of agricultural carbon emission efficiency in China's seven agricultural regions.

A profound understanding of the present status and regional characteristics of China's agricultural carbon emissions (ACE) is the basic prerequisite for exploring a pathway to ACE reduction that is compatible with China's national conditions. This study uses the inter-provincial agricultural industry panel data from 2001 to 2017 and selects the three-stage slack-based measure data envelope analysis (SBM-DEA) model and Malmquist-Luenberger(ML) index model to measure the dynamic efficiency of agricultural carbon emissions (ACE). Additionally, this study uses the Dagum Gini coefficient and the panel vector auto-regression(PVAR) model to analyze the sources of regional differences in dynamic efficiency and the internal structure, respectively. The empirical results reveal the following: (i) The dynamic efficiency of China's ACE is in a state of "efficiency optimization." Although both technological change and technological efficiency change are in an "efficient" state, they also show a decline in technological efficiency change and a regression in technological change, respectively. (ii) The overall Dagum Gini coefficient of China's ACE dynamic efficiency, technological change, and technological efficiency change all demonstrate upward trends. The gap between regions is the main reason for the long-term gap between the dynamic efficiency of China's ACE, technological change, and technological efficiency change. (iii) Regardless of the time horizon, technological change has always been the main driving force for the continuous growth of dynamic efficiency; the contribution of technological change to dynamic efficiency is far greater than that of technological efficiency change. This conclusion has been verified in samples from different regions of China.

A Comparative Analysis of the Effects of Objective and Self-Assessed Financial Literacy on Stock Investment Return.

Till now, comprehensive and quantitatively meaningful analyses of stock market participation outcomes of retail investors have been limited by data sources in developing countries. This article devised a special questionnaire related to stock investment to measure the financial literacy (FL) and stock investment return (SIR) for the subjects with stockownership in China and to theoretically and empirically study the effects of objective FL, self-assessed FL, and their composite FL on SIR. The results of the comparative analysis showed that self-assessed FL has a greater effect on SIR than objective FL, and the effect is mediated by risk preference. In addition, we found that competent and overconfident respondents have higher SIR, while under confident respondents cannot gain from the stock market. We also found that risk preference has a positive mediating effect in the relationship between competence and overconfidence and SIR, and a negative mediating effect in the relationship between under confidence and SIR. We thus concluded that confident investors can gain more stockholding returns via taking more risks regardless of the level of their actual financial knowledge. Our findings would be a meaningful complement to the studies of stock market participation.

Regional Differential Decomposition and Formation Mechanism of Dynamic Carbon Emission Efficiency of China's Logistics Industry.

Among China's five major industries, the logistics industry is the only one in which carbon emission intensity is continuing to increase, so it is of great importance in developing a low-carbon economy for China. Thus, some scholars have learned about carbon emission efficiency (CEE) in logistic industry recently; however, few of them have considered the inner structure, regional differentiation, or dynamic items of CEE. To fill this gap, we first calculate the dynamic carbon emission efficiency of China's logistics industry (CEELI) (2001-2017) using the three-stage DEA-Malmquist model, and then using the Dagum Gini coefficient method, the Kernel Density Estimation (KDE), and the panel vector auto-regression (PVAR) model to analyze regional differential decomposition and their formation mechanism. The results indicate that the dynamic CEELI is 'inefficient' overall; it shows a decreasing trend, and the decline of dynamic efficiency mainly comes from technical backwardness rather than efficiency decline. Moreover, the domestic differences are gradually narrowing; the Gini inequality between regions and the density of trans-variation between regions are the main reasons for the gap between different regions and different periods.

Spatial distribution and regional difference of carbon emissions efficiency of industrial energy in China.

The three-stage super-efficiency slack-based measure and data envelopment analysis (SBM-DEA) model with undesirable outputs is used to calculate carbon emissions efficiency of industrial energy (CEEIE) of 30 provinces in China from 2000 to 2017. Then ArcGIS software is used to illustrate the spatial distribution of CEEIE, and Dagum Gini ratio is calculated to decompose the regional difference. The results show that the spatial distribution of CEEIE changes from disorder to order and provinces characterized with high or low CEEIE cluster in space over time. The total Dagum Gini coefficient indicates that the interprovincial difference in CEEIE across China is gradually expanding, which is mainly induced by the difference between regions. Our findings attach more importance to interregional integration policies for carbon emissions reduction in China.