Effects of formal credit on pastoral household expense: Evidence from the Qinghai-Xizang Plateau of China

Formal credit is critical in agricultural production,allowing more expenditure and productive input,thereby improving farmers'welfare.In pastoral China,formal financial institutions are gradually increasing.However,a limited understanding remains of how formal credit affects herders'household expenses.Based on a survey of 544 herders from the Qinghai-Xizang Plateau of China,this study adopted the propensity score matching approach to identify the effect of formal credit on herders'total household expenses,daily expenses,and productive expenses.The results found that average age,grassland mortgage,and other variables significantly affected herders'participation in formal credit.Formal credit could significantly improve household expenses,especially productive expenses.A heterogeneity analysis showed that formal credit had a greater impact on the household total expense for those at higher levels of wealth;however,it significantly affected the productive expense of herders at lower wealth levels.Moreover,the mediating effect indicated that formal credit could affect herders'household income,thus influencing their household expenses.Finally,this study suggests that policies should improve herders'accessibility to formal credit.

Pricing Catastrophe Options with Credit Risk in a Regime-Switching Model

In this paper,we consider the price of catastrophe options with credit risk in a regime-switching model.We assume that the macroeconomic states are described by a continuous-time Markov chain with a finite state space.By using the measure change technique,we derive the price expressions of catastrophe put options.Moreover,we conduct some numerical analysis to demonstrate how the parameters of the model affect the price of the catastrophe put option.

Evolutionary analysis of green credit and automobile enterprises under the mechanism of dynamic reward and punishment based on government regulation

To explore the green development of automobile enterprises and promote the achievement of the“dual carbon”target,based on the bounded rationality assumptions,this study constructed a tripartite evolutionary game model of gov-ernment,commercial banks,and automobile enterprises;introduced a dynamic reward and punishment mechanism;and analyzed the development process of the three parties’strategic behavior under the static and dynamic reward and punish-ment mechanism.Vensim PLE was used for numerical simulation analysis.Our results indicate that the system could not reach a stable state under the static reward and punishment mechanism.A dynamic reward and punishment mechanism can effectively improve the system stability and better fit real situations.Under the dynamic reward and punishment mechan-ism,an increase in the initial probabilities of the three parties can promote the system stability,and the government can im-plement effective supervision by adjusting the upper limit of the reward and punishment intensity.Finally,the implementa-tion of green credit by commercial banks plays a significant role in promoting the green development of automobile enter-prises.

Research on Early Warning of Banking Crises from the Perspective of Credit Structures

The relationship between credit expansion and banking crises is complex and cannot be fully explained by total credit alone.A systematic analysis of the relationship between the amount and structure of total credit and banking crises is important for an objective prediction of the influence of potential financial risks.This paper,drawing on data from 15 selected countries,delves into the power of credit indicators in the early warning of banking crises from the perspectives of industrial structure,sector structure,and term structure of credit.Various machine learning methods were used,including Logistic Regression,Random Forest,Decision Tree,Support Vector Machine(SVM),Bagging,and Boosting models.The empirical findings indicate that credit expansion plays a crucial role in triggering banking crises.However,total credit is better suited for the early warning of short-term banking crises,whereas credit structure is more useful for the early warning of long-term banking crises.Moreover,in an early warning system,identifying key early warning indicators is more meaningful than merely increasing the number of indicators.Machine learning can somewhat enhance the early warning power,but it may not always be robust.Therefore,more attention should be paid to potential systemic banking crises resulting from an imbalance in credit structure while regulating the total credit threshold.

A Self-Adapting and Efficient Dandelion Algorithm and Its Application to Feature Selection for Credit Card Fraud Detection

A dandelion algorithm(DA) is a recently developed intelligent optimization algorithm for function optimization problems. Many of its parameters need to be set by experience in DA,which might not be appropriate for all optimization problems. A self-adapting and efficient dandelion algorithm is proposed in this work to lower the number of DA's parameters and simplify DA's structure. Only the normal sowing operator is retained;while the other operators are discarded. An adaptive seeding radius strategy is designed for the core dandelion. The results show that the proposed algorithm achieves better performance on the standard test functions with less time consumption than its competitive peers. In addition, the proposed algorithm is applied to feature selection for credit card fraud detection(CCFD), and the results indicate that it can obtain higher classification and detection performance than the-state-of-the-art methods.

Properties and Characterization of Two Clays Raw Material from Mountain District (West of Côte d’Ivoire) for Use in Low-Carbon Cements

This work was devoted to the study of the physico-chemical properties of two clay minerals from the Mountain District (West Côte d'Ivoire) referenced ME1 and ME2. These samples were characterized by the experimental techniques, such as X-ray diffraction (XRD), Infrared spectroscopy (IR), Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES), Differential Thermal Analysis and Thermogravimetry (DTA-TG), Brunauer, Emett and Teller method (BET), laser particle size analysis and Scanning Electron Microscope (SEM). The main results of these analyses reveal that the two clay samples mainly contain quartz (52.91% for ME1 and 51.72% for ME2), kaolinite (36.60% for ME1 and 41.6% for ME2) and associated phases, namely goethite and hematite (13.47% for ME1 and 11.00% for ME2). The specific surface values obtained for samples ME1 and ME2 are 34.78 m2/g and 29.18 m2/g respectively. The results obtained show that the samples studied belong to the kaolinite family. After calcination, they could have good pozzolanic activity and therefore be used in the manufacture of low-carbon cements.

Construction of BDS Spatiotemporal Information Agricultural Product Digital Credit System

Spatiotemporal information,positioning and navigation services have become important elements of new type infrastructure.The rapid development of global digital trade provides a large-scale application scenario for the use of Beidou Navigation Satellite System(BDS)spatiotemporal information to support the certification of origin of agricultural products.The BDS spatiotemporal information agricultural product digital credit system uses such modules as BDS,spatiotemporal information collection,spatiotemporal coding,and spatiotemporal blockchain.It incorporates multi-level joint supervision mechanisms such as government,associations,and users.Starting from the initial production link of agricultural products,it realizes the correspondence and locking of online and offline products,effectively improves the integrity and credibility of information in the production process,finished product quality and circulation process of products,effectively manages the green production and anti-channel conflicts of producers,and provides credible information for consumers,thus realizing the digital credit certification of products.The successful practice of characteristic agricultural products in Yunnan Province has verified the application ability of the BDS spatiotemporal information agricultural product digital credit system.This system has played a significant role in promoting the online and offline locking,credible information,effective supervision and high quality and high price of characteristic agricultural products from the field.The BDS provides services for global digital trade and contributes to the further enhancement of the global application scale of GNSS.

Does China's digital economy contribute to low-carbon transition?

The digital economy,as a new emerging economic form,has become an important power for realizing Chinese-style modernization and promoting green development in China.This paper measures the digital economy and low-carbon transition index based on the data of 30 provinces in China from 2013 to 2020 and analyzes the mechanism and path of the digital economy affecting low-carbon transition using the fixed effect panel data model and the threshold effect model.It is found that,(1)The digital economy and low-carbon transition in China are various in different regions,with characteristics of being unbalanced and insufficient.(2)The digital economy significantly promotes low-carbon transition,with the greatest influence in the Central region,followed by the Eastern region and the Western region.Under different dimensions,the development of informatization and digital transactions promote low-carbon transition,but the development of the internet plays an inhibiting role.(3)The higher the degree of urbanization and environmental regulation,the greater the influence of the digital economy on low-carbon transition.

Effect of ZrC Modified Graphite on Structure and Properties of Low-carbon Al_(2)O_(3)-C Refractories

To address the issues of reduced performance and shortened lifespan during the low-carbonizating process of Al_(2)O_(3)-C refractories,nano-crystalline ZrC modified graphite was prepared using Zr powder and flake graphite as raw materials,with NaCl and NaF mixed salt serving as the medium.The flake graphite was gradually replaced by ZrC modified graphite in the preparation of Al_(2)O_(3)-C refractories,and its impact on the material’s structure and properties was investigated.The results indicate that,compared to samples with only flake graphite,the introduction of 1 mass%to 5 mass%nano-crystalline ZrC modified graphite can significantly enhance the mechanical performance of low-carbon Al_(2)O_(3)-C refractories.When 5 mass%ZrC modified graphite is added,the mechanical properties of the samples are optimal,with the cold modulus of rupture and elastic modulus reaching 22.5 MPa and 65.0 GPa,respectively.

International Comparison and Lessons for Developing the Personal Credit Market

The rapid development of the global personal credit market has been driven by diversification and technological innovation,both of which serve as key catalysts for industry transformation.This paper conducts a comparative analysis of international personal credit markets to examine successful practices and challenges in credit products,credit assessment,and risk management across various countries.In particular,advancements in financial technology,including big data and artificial intelligence,have created new opportunities for enhancing the accessibility and personalization of credit services.Nevertheless,China’s personal credit market continues to face significant challenges,such as an underdeveloped credit infrastructure,outdated financial regulations,and limited product innovation.Drawing insights from international experiences,China can enhance its credit evaluation systems,strengthen financial regulations,and foster innovation in financial technology to facilitate healthy market development and advance inclusive finance.

Performance Evaluation of Low-Carbon and Clean Transformation of China’s Coal Economy

In China,the oversupply of coal occurred in 2009,and from that year onwards,China’s coal economy began a low-carbon and clean transformation.Evaluating transformation performance is the research goal of this paper.The data collection for this paper includes data on deep processing of Chinese coal products from 2009 to 2020,as well as data on asset structure evolution and financial performance of 34 listed companies in the Chinese coal mining.Entropy value method is used to calculate the entropy value of low-carbon transformation,and the regression analysis is used to study the performance of cleaner transformation,the conclusion is as follows:(1)From 2009 to 2020,in China’s total energy consumption,coal consumption accounted for 71.6%in 2009 and 56.8%in 2020,the goals set by the state have been achieved.(2)The national goal of reducing the proportion of coal consumption and reducing carbon emissions has forced the transformation of deep processing of coal products.The transformation of coal enterprises towards low-carbon and clean production has achieved remarkable results.(3)From 2009 to 2020,the non coal industry income of 34 listed companies in China’s coal mining industry increased by 8.21%annually.At the same time,the asset structure was adjusted,and nearly 80%of the asset structure evolution showed an orderly development trend.(4)The regression analysis results show that the entropy value of coal deep processing products and the entropy value of asset structure adjustment are significantly related to transformation performance.The paper proposes to summarize the successful experience of China’s coal energy economic transformation,lay a foundation for achieving the carbon peak and carbon neutral goals in the future,further increase the intensity of coal deep processing,increase the proportion of clean energy in total energy consumption,and strive to control asset operation towards the goal of increasing the proportion of non coal industry income.

A Mechanism for Digital Finance to Drive Green and Low-Carbon Development

Given the global focus on green and low-carbon development and the increasing prominence of digital finance,it is particularly important to explore how to leverage digital finance to achieve these environmental goals.This study,through mechanism analysis,deeply examines how China’s digital finance promotes green and low-carbon development and elucidates the positive interaction between digital finance and the green industry.The study found that digital finance,through more flexible and efficient financial functions,alters the cost structure of carbon emissions,and reduces the risks and costs of green investments,thereby creating a cooperative green mechanism benefiting all parties,and guiding social groups toward a green and low-carbon transformation.Additionally,the rapid development of digital finance has strengthened the implementation of environmental protection policies,effectively promoted the expansion of the environmental protection industry,and established the green ethos as a mainstream concept in financial development.This study aims to provide reference perspectives and suggestions,assist policymakers in promoting the green and lowcarbon development of digital finance,and offer insights into the integrated development of digital finance and the green environmental protection industry.

区块链环境下基于商业信用融资模式的供应链运营决策研究

应用区块链可以解决现有商业信用融资模式中存在的交货期过长、产品真实性难以保证和零售商不按时还款等问题。本文构建了应用区块链与未应用区块链的两种商业信用融资模式,运用Stackelberg博弈求解两种模式下供应链的最优批发价和零售价决策,研究未应用区块链时产品为真的概率、零售商期末按时支付剩余款项的概率、零售商违约对供应商造成的损失比例、应用区块链的单位运营成本和应用区块链后的交货期等因素对供应链运营决策和成员期望利润的影响,分析应用区块链后商业信用融资的价值。研究表明:当引入区块链缩短交货期、确保产品为真等功能带来的益处大于一定程度时,零售价和批发价高于传统模式;若零售商违约的可能性非常低,或者即使零售商违约,供应商的损失也不大,则传统模式下的批发价和零售价更高。若区块链运营成本小于零售商愿意支付的阈值,选择应用区块链对供应链所有企业而言均有利;而若区块链运营成本大于供应商愿意支付的阈值,供应链中任何企业均不会因应用区块链而受益。

增值税留抵退税政策对企业韧性的影响

基于2012—2021年上市公司微观数据,以2018年增值税留抵退税试点政策作为外生冲击,构建双重差分模型进行准自然实验,分析增值税留抵退税政策对企业韧性的影响,并运用中介效应模型分析其影响机制。研究结果表明:增值税留抵退税政策的实施能有效提升企业韧性水平,且该政策对东部地区、民营及中小企业的促进效应更为明显。从影响机制来看,增值税留抵退税政策可通过促进企业现金流流转、缓解企业融资约束、提升企业创新能力三条路径增强企业韧性。发挥税收激励提升企业韧性的作用,应提高增值税留抵退税政策的精准性,充分发挥政策协同效应,重点关注中小微民营企业在面对突发事件冲击时韧性增强的路径和策略。

社区同群效应与居民网络消费扩容提质

在百年未有之大变局下,扩内需、促消费已成为推动经济高效循环、满足人民美好生活需要的关键途径。作为人际互动与社会关系构建的关键场所,社区居民所形成的关系网络,不仅能强化居民之间的相互依赖,也能使居民消费行为产生同群效应。社区同群效应的信息传递与知识溢出,在促进居民网络消费扩容提质的同时,可以通过增加网络消费信贷、提升消费等级和降低居民依赖心理,使得低于参考点的居民受到激励,实现网络消费的扩容提质,这一点在男性和银发群体以及处于中小城市和农村地区的居民中表现得更为明显。社区同群效应对居民网络消费所产生的这种积极作用,为建立社区交流机制、设计符合居民需求特点的网络消费信贷体系、树立理性消费观和构建能释放内需动力的消费机制提供了新的实证证据,也丰富了居民消费领域的研究。

课程超市视域下大学英语学分制模块课微认证教学评价模式改革研究

本文探讨了在高等职业教育深化改革背景下,大学英语教学通过课程超市、学分制和微认证等创新评价模式,结合MOODLE平台优化教学质量,促进学生个性化学习及教师专业化发展的实践。文章首先指出传统教学评价的局限性,并介绍了相关政策要求,随后详细阐述了这些创新模式的概念及其应用,特别强调了MOODLE平台在支持微认证评价中的作用。研究结果表明,基于MOODLE的微认证体系显著提升了学生的学习效果和动机,同时为教师提供了数据支持,促进了教学策略的调整。该模式构建了更科学、灵活的教学评价体系,对学生的未来职业发展具有积极影响。

基于学分银行视角的在线课程质量标准体系构建研究

在教育数字化技术的支持下,在线学习已成为常见的学习方式。借助学分银行优势,建立统一的在线课程质量标准体系,是提升在线学习质量的关键环节。采用案例分析法,对国内外权威标准的核心指标进行概括与归纳,经过多轮专家论证,对指标进行删改、增补,结合层次分析法,为不同指标维度赋上权重系数,最终形成学习内容、教师团队、教学条件、教学实施、质量保证和课程认可度6个维度、17个一级指标的在线课程质量标准体系,旨在为大规模在线课程的学分认证和转换提供科学的参考指标,完善数字化学习成果认证机制,满足不同学习者的学习需求,为建设全民终身学习的学习型社会、学习型大国赋能。

基于信誉的委员会共识机制

授权股权证明(DPoS)作为主流共识机制的一种,选举过程耗时长、节点投票不积极和恶意节点难处理的核心问题制约着它的快速发展。针对上述问题,提出一种基于信誉的委员会共识机制——幸运信誉证明(PoLaC)。首先,将信誉值作为节点历史行为的评估标准,并选择高信誉节点作为委员会成员,从而极大地简化选举流程;其次,引入幸运值概念来提高普通节点竞选成功的概率,从而激励普通节点参与网络共识;最后,采取延迟分叉的方式修正恶意节点的行为。实验结果表明,在共识通信量方面,投票意愿为50%时,PoLaC网络比DPoS网络的共识通信量少30%;在低权重节点收益方面,PoLaC网络的收益是DPoS的3倍;在委员会恶意节点占比方面,进入信誉稳定期的PoLaC网络的委员会恶意节点数约为DPoS的1/5;而相较于其他同类信誉共识机制,PoLaC在网络通信量、节点活跃度以及恶意节点处理方面均具有一定优势。

新型农村金融机构设立能否促进新型农业经营主体创立

新型农业经营主体作为农业现代化建设的微观基础,以金融力量促进其培育壮大是金融支持乡村振兴的应有之义。本文基于村镇银行、农村资金互助社和贷款公司三类新型农村金融机构设立的准实验,利用2000—2022年县域数据考察新型农村金融机构设立对新型农业经营主体创立的影响。研究发现,新型农村金融机构能够通过“比较优势”与“竞争效应”提升所在地区新型农业经营主体的成立数量,并提高其创立过程中的劳动力、生产技术与自有资金水平。这一正向影响在牧区、南方地区以及脱贫县、市场化程度较高地区表现得更为强烈。此外,金融监管强度在新型农村金融机构影响新型农业经营主体创立上存在“倒U”型的调节效应。本研究为如何优化农村金融服务体系、发挥金融机构的比较优势以更好地支持乡村振兴提供了微观证据。

西北汉简中的“贳卖”与“贳买”

西北汉简中有一类“戍卒贳卖名籍”,内容是记录内地戍卒将其携带衣财物在边地贳卖的名单。贳卖即赊卖,西北汉简中记载的贳卖是一种有特定含义的贸易活动。贳卖地点包括吏所和民所两类,分别对应“卒居署贳卖名籍”和“卒行道贳卖名籍”。贳卖民所标识信息详细,包括籍贯、人名,且有任者,并标注身份或居住地;贳卖吏所记录则相对简单,只标注隧长、隧名。偶有作为知情人、见证人的“旁人”,但并不涉及经济关系。其原因在于军政系统中的候官对军吏约束力强。贳卖对象相对集中,故而当为中介机构而非个人。官府禁止戍卒私贳卖衣财物。边地官府掌控着贳卖活动,军政系统由部—候官—都尉府层层控制,通过帮助收债、干预贳卖价格、调查交易中的不法行为来实现。贳卖方来源于内地戍卒,贳买方主要为边地的底层官吏和百姓。内地戍卒的贳卖活动有专门贸易的倾向,可以满足对现钱的需求,是丝路贸易的一种形式。边地军政机构也能通过贳卖名籍掌握士卒的衣物装备,从而保证戍卒基本屯戍衣装需要。国家对边地贳卖活动的管理显示出其为巩固边疆所做出的努力。