Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China

It is difficult to predict the financial distress of unlisted public firms due to their longer disclosure cycle of accounting information and more inadequate continuity of market trading information compared to listed firms. In this paper, we propose a framework to predict the financial distress of unlisted public firms using current reports. Specifically, to better represent the meaning of current report texts, we propose a semantic feature extraction method based on a word embedding technology. Empirical results show that current reports contain more effective information for predicting the financial distress of unlisted public firms compared with periodic reports. In addition, semantic features extracted using our proposed method significantly improve the predictive performance, and their enhancing effect is superior to that of topic features and sentiment features. Our study also provides implications for stakeholders such as investors and creditors.     

新基建发展对产业升级的影响机制研究

新基建作为现代化基础设施体系的重要组成部分，已经成为中国经济高质量发展的重要支撑。基于2015—2021年中国71个城市的面板数据，构建双向固定效应、中介效应和调节效应三种回归模型，实证检验新基建发展对城市产业结构水平的影响及内在机制。研究发现：新基建发展能促进产业高级化水平，改善不合理的产业结构状态，提升产业合理化水平；新基建通过发展物联网和激励城市研发创新两种间接路径对产业结构转型升级产生积极影响；新基建对产业结构水平的影响受到地方政府干预行为的调节作用，在地方政府合理的行政管理下，新基建对产业转型升级的积极作用更为明显；新基建发展对产业结构水平的提升作用具有区域异质性和城市规模异质性，在中西部地区和大城市地区的作用效果更为明显。     

Delegation and the regulation of U.S. financial markets

We analyze the institutional determinants of U.S. financial market regulation with a general model of the policy-making process in which legislators delegate authority to regulate financial risk at both the firm and systemic levels. The model explains changes in U.S. financial regulation leading up to the financial crisis. We test the predictions of the general model with a novel, comprehensive data set of financial regulatory laws enacted specifically between 1950 and 2009. The theoretical and empirical analysis finds that economic and political factors impact Congress’ decision to delegate regulatory authority to executive agencies, which in turn impacts the stringency of financial market regulation, and our estimation results indicate that political factors may have been stronger and resulted in inefficiencies.     

土地市场扭曲如何影响制造业出口产品质量升级*——基于土地市场交易数据和制造业企业数据的实证分析

地方政府“以地谋发展”的策略在促进各地区制造业大规模集聚和出口贸易快速增长的同时，也势必会给企业出口产品质量带来深刻影响。本文综合利用中国土地市场网城市土地交易数据、中国工业企业数据、中国海关进出口产品数据和中国城市面板数据，实证检验了土地市场扭曲对企业出口产品质量升级的影响，并对其内在机制进行了探讨。研究发现：中国城市建设用地配置存在明显的工业偏向性，进而导致工业用地价格被低估，产生工业用地应得收益大于实际价格的反向扭曲问题。这种反向扭曲可通过抑制技术进步、阻碍产业结构高级化、弱化集聚经济效应等机制显著降低制造业企业出口产品质量。土地市场扭曲对企业出口产品质量升级的影响具有明显的异质性特征。具体而言，土地市场扭曲不利于一般贸易企业与混合贸易企业出口产品质量提升，但对加工贸易企业出口产品质量提升具有促进作用。土地市场扭曲对企业出口产品质量升级的抑制作用由东到西依次递增。土地市场扭曲不利于外资企业和国有企业出口产品质量提升，对集体企业及民营企业的影响不显著。     

“绿色矿业”的逻辑机理、实践探索与推进策略

发展“绿色矿业”是人类进入生态文明社会的必然选择，绿色发展理念指导下的“绿色矿业”发展具有主旨统一性和实践多样性、国家主导性和企业渐进性，需要完善的理论指导、体系构建和政策支持。“绿色矿业”的运行体系是由相关主体（绿色政府、绿色企业、绿色社会、绿色市场）及其功能共同形成的网络结构，各主体多元化、多维度的相互作用共同促进“绿色矿业”的有序发展，最终实现“矿业经济发展、生态环境良好、发展成果共享”的目标。我国发展“绿色矿业”的实践取得了显著成效，各地不同的发展模式既有目标的同一性，又有方式的差异性。当前，我国“绿色矿业”发展还存在标准体系不健全、政策法规不完善、发展格局不协调、协同监管不到位等问题，需要进一步发挥政府的主导作用、企业的主体作用、行业协会及社会的协调支撑作用，并构建和优化“绿色矿业链”和“绿色矿业区域板块网络”，推动“绿色矿业”健康有序发展。     

金融周期、行业技术周期与经济结构优化

本文首先采用马尔科夫区制转移模型测算金融周期和12类行业的技术投入周期,进而采用交叉谱分析法和OLS法分析金融周期对行业技术周期的影响,结果发现:不同金融变量的周期具有异步性,各行业的技术投入周期具有明显差别;不同金融变量周期与行业技术投入周期之间存在不同的数量关联性,对不同的行业技术投入具有不同的影响作用;在繁荣阶段,金融市场和银行对各行业的技术投入都具有正向推动作用,但金融市场对高密度创新行业技术投入的推动作用更为显著,银行对低密度稳定行业技术投入的推动作用更为显著;在紧缩阶段,金融市场对高密度创新行业技术投入的紧缩效应更为剧烈,银行却对低密度稳定行业的技术投资下行起到缓解作用。根据这些事实和规律,可以引导利用各金融变量对具有发展前景的行业强化技术投资助推作用,提升经济结构优化效率。     

Business marketing in France: can the case be made for “French exceptionalism” or is it just a slight variation?

Purpose: The aim of this article is to elucidate the state of B-to-B marketing research in France by conducting a review of theoretical and empirical studies in this field that have been published over the last three decades.

Methodology/approach: Authors identified relevant literature sources, and proceeded with classifying the publications according to their main theme of study (as determined by reviewing the topic, the abstract, and/or keywords). To extract the main articles, authors explored multiple electronic databases, including Source Premier (EBSCO), Elsevier Science Direct, Google Scholar, and Cairn.info. This methodology has allowed comparisons both in time and in relation to similar works done in other countries. The analysis focuses on the main contributions of French literature in the B-to-B domain and establishes that progress has been made in understanding the issues of B-to-B marketing in France, as well as in the development of the theory in this field.

Findings: The review shows that B-to-B marketing research in France, although under-represented in relation to its B-to-C counterparts, is gradually emerging from the shadows and covers important topics that are increasingly diverse and varied. By identifying the main topics studied by French B-to-B marketing researchers, this work advances this academic discipline while also providing valuable information.

Originality/value: This study is the first attempt to conduct an in-depth examination of the state of B-to-B marketing research in France. Findings yielded by this literature review would be beneficial to both B-to-B marketing researchers and practitioners and promotes this research field.     

Improving forecasting performance using covariate-dependent copula models

Copulas provide an attractive approach to the construction of multivariate distributions with flexible marginal distributions and different forms of dependences. Of particular importance in many areas is the possibility of forecasting the tail-dependences explicitly. Most of the available approaches are only able to estimate tail-dependences and correlations via nuisance parameters, and cannot be used for either interpretation or forecasting. We propose a general Bayesian approach for modeling and forecasting tail-dependences and correlations as explicit functions of covariates, with the aim of improving the copula forecasting performance. The proposed covariate-dependent copula model also allows for Bayesian variable selection from among the covariates of the marginal models, as well as the copula density. The copulas that we study include the Joe-Clayton copula, the Clayton copula, the Gumbel copula and the Student’s $t$-copula. Posterior inference is carried out using an efficient MCMC simulation method. Our approach is applied to both simulated data and the S&P 100 and S&P 600 stock indices. The forecasting performance of the proposed approach is compared with those of other modeling strategies based on log predictive scores. A value-at-risk evaluation is also performed for the model comparisons.     

数据交易市场双边匹配模型与决策方法研究

针对平台视角下的数据交易供需双边匹配问题，基于双边匹配理论，提出了考虑模糊语言评价信息、区间数评价信息和0-1评价信息的混合型多属性匹配决策方法并定义了属性匹配满意度函数。以供需主体最大匹配满意度为目标，构建了数据交易供需双边匹配的多目标优化模型，并设计模型求解算法，将多目标化模型转化为单目标线性规划模型进行求解，以获取匹配结果。结果表明，通过对供需双方需求信息的详细分析，双边匹配结果能在最大程度上满足双方需求，同时，优化模型具有合理性及有效性。     

Changing International Financial Architecture: Growing Chinese Influence?

It is often said that the 21st century will be the Asian century. Based on population and gross domestic product projections, it certainly looks as if this will be so. Will the existing international financial institutions give more voices, votes, and top positions to Asia? Or will Asia create its own institutions that would rival the old architecture? This present paper argues, first, that China, and possibly India, will be in a position to be so influential that the international financial architecture may have to go through significant changes. Second, the three large crises in the last 20 years have made Asian countries more confident that they can manage capital flows by accumulating large foreign reserves and by adopting sound macrofinancial policies. After 2009, China started to push various initiatives that will amount to creating its own sphere of influence with new regional institutions in the future.