中国农村信用的演化路径研究

中国农村信用是通过自发的、松散的非正式组织形式实现的,在基于血缘、地缘关系的特殊信任主义系统里,农村信用的实施机制和信用保护机制事实上是在一个关联博弈中进行的。当农村非正式社会结构向正式社会结构转轨时,由于契约的法律执行机制的不完善以及交易范围的扩展诱致的信息不完备和非对称,使得关联博弈和信息完备性的基础逐渐丧失,仅靠声誉和关系交易的维系成本急剧上升,人格化交易面临规模不经济和信用风险的双重约束。     

Eco‐efficiency of high‐yielding variety rice cultivation after accounting for on‐farm environmental damage as an undesirable output: an empirical analysis from Bangladesh

This study computes the eco‐efficiency of high‐yielding variety (HYV) rice production by including an on‐farm environmental damage index (OFEDI) as an undesirable output using data envelopment analysis. It then identifies its determinants by applying an interval regression procedure on a sample of 317 farmers from north‐western Bangladesh. Results reveal that the mean level of the OFEDI‐adjusted production efficiency (i.e. eco‐efficiency) is 89 per cent, whereas ignoring OFEDI adjustment (i.e. with OFEDI = 0) reduces the mean level of efficiency to 69 per cent, implying that the production of undesirable output or on‐farm environmental damage induces an efficiency loss of 20 per cent with significant differences across regions. The proportion of farmers’ income from HYV rice agriculture, land ownership, extension services and socio‐environmental living standard are the significant determinants of improving eco‐efficiency. Policy implications include investments in extension services and land reform measures to increase land ownership, which will synergistically improve eco‐efficiency of HYV rice production in Bangladesh.     

Diffusion of Kyoto's clean development mechanism

To date, developed countries can only tap mitigation opportunities in developing countries by investing in projects under the Clean Development Mechanism (CDM). Yet CDM investments have so far failed to reach all of the high-potential sectors identified in IPCC reports. This raises doubts about whether the CDM will be able to generate an adequate supply of credits from the limited areas where it has proved successful. Our paper examines the current trajectory of potential mitigation entering the CDM pipeline and projects it forward under the assumption that the diffusion of the CDM will follow a path similar to other kinds of innovations. Projections are then compared to pre-CDM predictions of the mechanism's potential market size used to assess Kyoto's cost, in order to discern whether limits on the types of project entering the pipeline will also limit the eventual supply of certified emission reductions (CERs). The main finding of the paper is that the mechanism is on track to deliver an average annual flow of roughly 700 million CERs by the close of 2012 and nearly to 1100 million tons by 2020. Parameter tests suggest that currently identified CDM investments will exceed early model predictions of the potential market for CDM projects.     

R&D and regional competitiveness: a study of global entrepreneurial firms

We quantify, using data from the World Bank’s Enterprise Surveys and the World Economic Forum’s Global Competitiveness Index, the empirical relationship between global competitiveness and R&D investment activity as well as the independent relationship between global competitiveness and R&D investments across geographic regions of economic development. We also explore alternative measures of the effectiveness of R&D investments. Our findings suggest that R&D investments are a possible policy target variable in high-income regions for policy makers to consider for increasing firms’ global competitiveness.

     

Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China

The current research aims to launch effective accounting fraud detection models using imbalanced ensemble learning algorithms for China A-Share listed firms. Based on a sample of 33,544 Chinese firm-year instances from 1998 to 2017, this research respectively established one logistic regression and four ensemble learning classifiers (AdaBoost, XGBoost, CUSBoost, and RUSBoost) by 12 financial ratios and 28 raw financial data. Additionally, we divided the sample into the train and test observations to evaluate the classifiers' out-of-sample performance. In detail, we applied two metrics, namely, Area under the ROC (receiver operating characteristic) curve (AUC) and Area under the Precision-Recall curve (AUPR), to evaluate classifiers' discriminability. In the supplement test, this study put forward an algebraic fused model on the basis of the four ensemble learning classifiers and introduced the sliding window technique. The empirical results showed that the ensemble learning classifiers can detect accounting fraud for the imbalanced China A-listed firms far more effectively than the logistic regression model. Moreover, imbalanced ensemble learning classifiers (CUSBoost and RUSBoost) effectively performed better than the common ensemble learning models (AdaBoost and XGBoost) in average. The algebraic fused model in the supplement test also obtained the highest average AUC and AUPR among all the employed algorithms. Our results offer firm support for the potential role of Machine Learning (ML)-based Artificial Intelligence (AI) approaches in reliably predicting accounting fraud with high accuracy. Similarly, for the Chinese settings, our ML-based AI offers utmost advantage in forecasting accounting fraud. Finally, this paper fills the research gap on the applications of imbalanced ensemble learning in accounting fraud detection for Chinese listed firms.     

Consumer ethics: A review and research agenda

Consumer ethics continues to draw the attention of academicians and practitioners as a significant economic and social issue globally. Consumer ethics refers to moral principles that govern a consumer's behaviour. This literature review seeks to enrich the discourse on consumer ethics through a comprehensive and detailed review of 106 articles, covering 21 journals from 2010 to 2020. Through an examination of theories, contexts, characteristics, and methodologies used in consumer ethics research, our review (1) presents a comprehensive and up-to-date overview of the research in this field and (2) sets a future research agenda to spur scholarly research. We found studies have primarily relied on a single theoretical lens such as the theory of marketing ethics, planned behaviour, and neutralization theory. Further consumer ethics research focuses on advanced countries, with a narrow focus on developing countries. We have diagnosed the need to examine boundary conditions impacting consumer ethics. Finally, we provide actionable inputs to combat unethical consumer actions as well as promote ethical consumption.     

IRS Private Letter Rulings: Initial Evidence on Determinants and Consequences

This study examines the determinants of firms' requests for Private Letter Rulings (PLRs) from the US Internal Revenue Service (IRS) and their impact on firms' cash holdings. Our results show that PLR requests tend to be made by firms with more active tax planning, more acquisitions, higher analyst following, higher leverage, and less in-house tax expertise. We also show that firms with IRS audit red flags are less likely to request a PLR. We use a difference-in-difference approach to assess changes in cash holdings following PLR requests and report a decrease in cash holdings for PLR firms, consistent with the notion that PLRs act to reduce tax uncertainty. Our study provides the first empirical evidence about the determinants of PLR requests and complements prior work on tax uncertainty and cash holdings (Hanlon, Maydew and Saavedra, 2017).