The Interaction Between Suppliers and Fraudulent Customer Firms: Evidence from Trade Credit Financing of Chinese Listed Firms

Journal of Business Ethics - This study investigates the interaction between suppliers and fraudulent customer firms from the perspective of reputation damage and reputation recovery. Specifically,...     

我国城市住房保障水平评估——基于公租房准入门槛的量化分析

本文通过对全国153个地级及以上城市公租房准入政策和条件进行量化分析,运用主成分分析法构建起公租房准入指数,用以反映城市住房保障水平.以此为基础,本文利用中国家庭金融调查的微观数据,实证检验公租房准入指数对家庭居住公租房的影响.结果 显示,公租房准入指数越高,家庭获得公租房的可能性显著增加,从而验证该指数的合理性.文章发现,尽管在大力倡导新型城镇化的背景下,各地公租房仍然对外市户籍人口存在较高门槛.随着城镇化水平不断提高,人口流动持续增强,中央政府应建立对各城市科学合理的住房保障评估体系,重构地方政府激励机制,提高地方政府住房保障的积极性,同时应加大对外来居民的保障力度.     

刑事涉财产执行中的案外人权益救济——以案外人权益救济程序的当事人构造为视角

刑事涉财产执行程序因采取移送执行模式而被误认为不存在申请执行人，使得刑事涉财产执行程序及其衍生的案外人权益救济程序过分依赖执行法院的职权主义。在刑事附带民事诉讼裁判、追缴或责令退赔违法所得并返还被害人判项、责令被免予刑事处罚的被告人赔偿被害人损失判项的执行程序中，案外人权益救济程序原则上应以被害人为申请执行人，并参照适用民事强制执行程序中的案外人权益救济制度。其他刑事涉财产执行程序应以检察机关为申请执行人。除非出现被执行人逃避执行或者案外人对执行标的提出排除执行请求等特殊情形，作为申请执行人的检察机关通常无须现实参加执行程序。     

Do Cryptocurrencies Increase the Systemic Risk of the Global Financial Market?

The advance of cryptocurrencies has sparked wide concern over their interplay with the existing global financial market. This paper analyzes the risk spillover relation between cryptocurrencies and major financial assets, and unravels how cryptocurrencies could influence global financial systemic risk. We find that cryptocurrencies function as a separate risk source from traditional assets. Major legislative, financial and technological events in the cryptocurrency market may affect risk spillover dynamics. Although the overall penetration of cryptocurrencies is not yet deep, introducing cryptocurrency can significantly increase the systemic risk to traditional markets during low risk level episodes.     

Size of nested cities

Models of cities based on conventional spatial market theory are unable to replicate a realistic size distribution. The stochastic process approach to size distribution, which assumes proportionate growth, does not provide an economic foundation for spatial trades. There is an apparent irreconcilability. We propose that since there is a continuum of equilibria in models of spatial markets with endogenous location, proportionate growth can work as equilibrium selection. We present computations for an urban configuration that has not been presented in the literature before. A small city locates inside a larger city's agricultural supply zone. This generates a larger variation in city size that may include a realistic size distribution.     

The effects of anticipated goal‐inconsistent behavior on present goal choices

Prior work has examined how, in the pursuit of long‐term goals, past goal behavior influences present goal choices. Instead, the present work focuses on how anticipating future goal behavior, specifically future goal‐inconsistent behavior, influences present goal choices. For example, how anticipating overspending on an upcoming vacation influences current spending behavior. The authors propose that the effect of anticipated goal‐inconsistent behavior on present goal choice is moderated by the perceived changeability of the future behavior. When future goal‐inconsistent behavior is perceived as changeable, consumers tend to imagine it away, and it has no systematic effect on present goal choices. However, when future goal‐inconsistent behavior is perceived as unchangeable, consumers accept it as a matter of fact, and systematic effects occur. Specifically, some consumers not only fail to buffer against future goal‐inconsistent behavior's negative consequences, but tend to exacerbate those consequences by increasing their goal‐inconsistent behavior in the present. Four studies examine this surprising behavior, using an individual difference (the response‐to‐failure scale) to identify when and for whom it occurs. The studies demonstrate the role of perceived changeability using various manipulations across multiple critical goal domains such as spending, eating, and academics.     

面源污染视角下江西省耕地利用效率研究

[目的]在面源污染视角下考察耕地利用效率,可以为推动耕地可持续利用提供理论和参考依据。[方法]文章基于2000—2014年我国13个粮食主产省(区)耕地投入产出的面板数据,运用SBM方向性距离函数将耕地面源污染因素纳入到传统的效率分析框架,从省际比较的维度对江西省耕地利用效率进行了测度与分析。[结果]考虑面源污染因素对耕地利用效率测算产生了一定的影响;江西省耕地利用效率值呈现阶段性特征,耕地利用效率排名比较稳定,近年来排名有上升趋势;江西省耕地利用绩效一般,且与最佳实践者存在较大的差距。[结论]忽视面源污染因素的耕地利用效率评估是失真和不符合实际的,宜将面源污染因素纳入到耕地利用效率的测度框架,以此来更科学地量化评估耕地利用绩效;设计和完善相关政策,以有效控制耕地面源污染;加强与先进省(区)的交流与合作,学习其农业可持续耕作技术与管理经验,进一步推动江西省耕地产出与资源、环境协调发展。     

Is Oil Palm Expansion a Challenge to Agroecology? Smallholders Practising Industrial Farming in Mexico

Agroecology has become a powerful alternative paradigm for rural development. In contrast to conventional approaches, this paradigm shifts the emphasis from technology and markets to local knowledge, social justice and food sovereignty, to overcome rural poverty and environmental degradation. However, the spread of this approach faces several obstacles. This paper deals with one of these obstacles: the ‘preference’ of smallholders for industrial farming. We specifically analyse the widespread uptake up of oil palm by smallholders in Chiapas. Contrary to agro‐ecological assumptions, oil palm proved favourable to smallholders in Chiapas because of historical and contemporary state–peasant relations and the advantageous economic circumstances within the oil palm sector. Based on this research, we identify four challenges for agroecology: (i) the existence of contradictory interests within the peasantry as a result of social differentiation; (ii) the role of the state in making conventional development models relatively favourable to smallholders; (iii) the prevalence of modernization ideologies in many rural areas; and (iv) the need for this paradigm to acknowledge smallholders' agency also when engaged in industrial farming. These challenges need to be tackled for agroecology to offer viable alternatives in a context of agro‐industrialization.     

Predicting credit card delinquencies: An application of deep neural networks

The objective of this paper is twofold. First, it develops a prediction system to help the credit card issuer model the credit card delinquency risk. Second, it seeks to explore the potential of deep learning (also called a deep neural network), an emerging artificial intelligence technology, in the credit risk domain. With real-life credit card data linked to 711,397 credit card holders from a large bank in Brazil, this study develops a deep neural network to evaluate the risk of credit card delinquency based on the client's personal characteristics and the spending behaviours. Compared with machine-learning algorithms of logistic regression, naive Bayes, traditional artificial neural networks, and decision trees, deep neural networks have a better overall predictive performance with the highest F scores and area under the receiver operating characteristic curve. The successful application of deep learning implies that artificial intelligence has great potential to support and automate credit risk assessment for financial institutions and credit bureaus.