跨境电商对华商网络贸易的效应分析

在就跨境电商对华商网络贸易所具有的替代效应与互补效应进行理论分析的基础上，利用古诺模型分析市场均衡的结果及贸易效应，采用面板数据实证检验跨境电商对华商网络贸易的影响，结果表明跨境电商对华商网络贸易的互补效应大于替代效应：一方面，由于华商网络对出口贸易的影响尤为显著，而跨境电商平台又以出口贸易为主，从而跨境电商对华商网络出口贸易的影响较大；另一方面，跨境电商平台偏向于差异化产品贸易，因而跨境电商对差异化产品的华商网络贸易有着较大影响。也就是说，跨境电商对华商网络贸易的互补效应在出口贸易与差异化产品贸易上表现得尤为显著。     

Accounting practice,fiscal decentralization and corruption

In prior studies, accounting and decentralization corruption solutions have so far been analysed in isolation. In this article, we connect these two strands of literature on corruption. Understanding this connection is important because weak financial accounting and reporting systems can inhibit monitoring incentives and thus reduce decentralization benefits in countering corruption. We argue that the effectiveness of decentralization as an anti-corruption barrier is complemented by the quality of the accounting practice in a country. Using multiple sources of data, we find that decentralization has a positive and increasing effect on reducing corruption among countries with a high-quality accounting practice. In contrast, decentralization has a negative and decreasing effect on reducing corruption among countries with weak-quality accounting practices. These findings are robust to alternative measures of accounting, decentralization and corruption and to endogeneity tests. Our findings demonstrate the crucial information role of accounting in enhancing decentralization monitoring mechanisms and in thereby reducing corruption.     

审计师地理距离对客户公司股价信息含量的影响

从地理经济学视角分析审计师的地理区位特征对上市公司股价信息含量的可能影响，利用2004—2013年中国A股上市公司的数据，实证检验了审计师与客户间的地理距离对客户公司股价信息含量的经验影响关系，并进一步考察了证券分析师与审计监督两种中介组织间的交互效应。研究发现：（1）审计师与客户公司间的地理距离越小，客户公司的股价信息含量越低，因为在中国当前经济社会背景下，地理邻近对审计师独立性的消极影响要强于其对审计师专业胜任能力的积极影响，这导致审计师审计质量降低，影响客户公司股价信息含量；（2）证券分析师对客户公司的关注程度越高，审计师的地理邻近性对客户公司股价信息含量的负面影响越弱，表明证券分析师与外部审计之间主要呈现一种相互替代的关系，证券分析师可以作为一种有效的补充监督机制。     

Contracting and Reporting Conservatism around a Change in Fiduciary Duties*

We exploit an influential 1991 Delaware court ruling to examine simultaneously two types of conservatism that play important roles in resolving creditor–owner agency conflicts: contracting conservatism and reporting conservatism. The ruling expanded managerial fiduciary duties in favor of creditors for Delaware-incorporated firms in the vicinity of insolvency. In those firms, following the ruling, debt contracts are less likely to include conservative adjustments to accounting numbers used for covenant compliance (i.e., contracting conservatism decreases), while public financial reporting becomes more conservative (i.e., reporting conservatism increases). The decrease in contracting conservatism is concentrated in firms that exhibit a greater increase in reporting conservatism, suggesting that reporting conservatism is more cost-effective in resolving agency conflicts. In addition, the substitution effect is more pronounced in firms facing greater business uncertainty and firms with greater board independence.     

Asymmetric information consolidation and price discovery: Inferring bad news from insider sales

Due to the paucity of sources of negative firm‐specific information, US capital markets have more difficulty identifying and incorporating bad news into stock prices than they do good news. Even though insider selling is a potentially important proxy for undisclosed bad news, researchers have difficulty ex ante identifying information‐based sales due to an inability to separate liquidity‐motivated from information‐based insider trades. We hypothesize that when insiders in multiple firms sell shares of one firm in which they are insiders and at the same time buy shares of other insider portfolio firms, the sale is more likely to be information‐based, since the proceeds are reinvested. Conversely, when an insider sells one firm without purchasing others or sells multiple insider firms the sale is likely liquidity‐motivated. We find that insider sales identified as information‐based using this algorithm are followed by significant negative abnormal returns. Information‐based sales are also more likely to be associated with delistings, earnings declines and earnings restatements. Analysts are also more likely to revise their earnings forecasts downwards for these firms. It is thus possible to ex ante identify insider sales with information content. Our results will be of interest to investors and also to regulators designing insider trading rules.     

Muddling through cybersecurity: Insights from the U.S. healthcare industry

The U.S. healthcare sector is inadequately prepared to deal with the reality of cyber threats. The increasing use of smart medical equipment and mobile devices is making healthcare organizations more susceptible to ransomware and other types of malware. The size and complexity of operations, coupled with the presence of numerous legacy and incompatible systems, make it difficult to implement effective cybersecurity measures. The daunting nature of the problem often results in an if-it-ain’t-broke-don’t-fix-it stance among senior healthcare leaders. The preponderance of healthcare-related laws, compliance regulations, and security guidance frameworks serve to complicate the cybersecurity challenge further and too often results in senior leadership assuming a state of blissful ignorance. This study sheds light on the key factors contributing to the chaotic state of affairs and presents a roadmap to a more deliberate and proactive approach to cybersecurity risk management.     

Commemorating the 50‐Year Anniversary of Ball and Brown (1968): The Evolution of Capital Market Research over the Past 50 Years

We commemorate the 50th anniversary of Ball and Brown [1968] by chronicling its impact on capital market research in accounting. We trace the evolution of various research paths that post–Ball and Brown [1968] researchers took as they sought to build on the foundation laid by Ball and Brown [1968] to create a body of research on the usefulness, timeliness, and other properties of accounting numbers. We discuss how those paths often link back to the groundwork laid and questions originally posed in Ball and Brown [1968].     

Perceptions of the benefits of the A3 planner in facilitating project-based learning in accounting education

This paper evaluates ways of instilling project management skills into accounting-based learning by the use of an iterative A3 planner to plan, monitor and review assignment progress. The application of an A3 planner to facilitate a project-based learning (PBL) group assignment in undergraduate accounting education has been critically evaluated in terms of both the student and tutor experience. The study uses a mix of qualitative and quantitative data. Quantitative data assisting exploration of perceptions were collected through 100 undergraduate students. A series of focus group discussions were carried out to investigate students’ engagement and tutors’ teaching experiences regarding the adoption of the A3 planner. The results suggest that the A3 planner promotes active planning and effective management of a PBL group assignment. It makes students’ thought processes more visible thereby facilitating and enhancing the tutoring/mentoring process. Moreover a more interactive and transparent approach by doing assignment via the use of an iterative A3 planner has ensured more feedback points and action based efficiency in the doing approach for learners.     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.