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.     

Does educational diversity of managers matter for the performance of team‐managed funds?

We study the effect of the educational diversity of managers on the performance of team‐managed mutual funds using a large sample of U.S. equity funds from 1994 to 2013. We consider diversity in terms of both final educational degree and field of educational specialisation. We find that, in general, both types of diversity have a positive impact on fund performance, and our results are robust over a wide range of performance metrics and changes in market conditions.     

隐性杠杆约束、流动性风险和投资者情绪

本文以2003—2019年间开放式主动管理型的股票型和偏股型基金为样本,以持仓占比为权重估算基金投组中A股的总市场风险暴露,检验结果表明,该序列上升反映了基金面临的隐性杠杆约束收紧,刻画了市场的弱流动性。内在逻辑在于,流动性收紧时,投资者难以通过融资直接增加杠杆,更倾向于重仓持有高市场风险头寸的股票而间接实现杠杆。本文发现隐性杠杆约束所刻画的风险在股票或基金收益截面上的无条件定价基本失效,而条件定价则依赖于低市场情绪与弱流动性。分解基金持股的敞口,进一步发现,因中小盘基金在流动性收紧时具有更强的流动性偏好,其持股的市场风险头寸能够更敏锐地捕捉到弱流动性风险。     

产业共性技术政府支持性研发外包合同影响因素研究

建立产业共性技术研发外包博弈模型，从政府视角研究以共性技术产出最大化为目标的最优政府支持性研发外包合同，并对最优外包合同影响因素进行分析。研究表明：足够多的政府预算是共性技术政府支持性最优研发外包合同存在的前提，最优合同条款随政府预算的增大而增多，企业保留收益增大倒逼政府预算增加；企业最优知识技术投入与共性技术价值系数以及从研发中分享的收益份额正相关，与政府支付的固定研发费用负相关；政府最优知识技术投入与固定研发费用及单位投入成本系数负相关；企业最优投入与政府投入成本系数负相关，与政府投入对研发成功的贡献系数正相关，且企业最优投入随其研发能力的增强而加大。最后，根据研究结论，从政府预算、项目前景及支持性资源分配3个方面提出共性技术研发外包合同实施的政策建议。     

异质机构持股、政府补贴与企业技术创新

机构投资者与政府补贴等优惠政策作为企业经营的重要资本来源和制度保障，势必对企业技术创新产生重要影响。以我国沪深两市战略性新兴上市企业2010-2015年面板数据为研究样本，对异质机构持股、政府补贴与企业技术创新的关系进行实证分析。结果发现：机构持股对企业技术创新没有显著影响，政府补贴可以促进机构持股对企业技术创新尤其是实质性技术创新产生显著正向影响；基金持股对企业技术创新存在显著负向影响，券商持股与QFII持股对企业技术创新分别存在不显著和显著正向影响；政府补贴能够降低基金持股对企业技术创新的负向影响，有效促进基金持股对企业技术创新的正向影响，并通过调节作用促进券商持股和QFII持股对企业技术创新产生更加显著的正向效应；政府补贴对基金持股与企业非实质性技术创新关系的正向调节作用更加显著，对券商持股和QFII持股与企业实质性技术创新关系的正向调节作用更加显著。     

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.     

Financial scandals: a historical overview

I examine the incidence of fraud from c.1720 to 2009 and relate it to the occurrence of significant financial scandals. Focusing on the UK, and US prior to Enron, and using a detailed dataset of significant events and news content, underpinned by examination of specific watershed scandals, the paper highlights the regulatory response to scandals and the implications for accounting and financial reporting. The evidence reveals the incidence of fraud and financial scandal to be historically contingent and skewed towards certain sectors, particularly banking and finance, facilitated by complex group structures and international capital mobility, and mediated by managerial incentives and ownership concentration. Financial reporting and auditing can mitigate fraud opportunities in all sectors and businesses without complex group structures, and the accounting profession achieved some success in this respect up to the mid-1970s. Since then, the profession has been increasingly challenged by, and to some degree implicated in, the development of interconnected and international business networks, which, combined with wider financial deregulation, has led to a resurgence of fraud and financial scandal not previously experienced since the mid-nineteenth century.     

Managing leverage of infrastructure projects: Aggregate and sectoral risk effect

Funding for infrastructure projects recently shows that debt has a portion more than equity, triggering public debates. Therefore, leverage as an instrument to measure the ability and willingness of project sponsors to fund becomes the utmost importance to discuss. Relating to leverage, risk and government participation are two main factors that can explain the choice of funding decisions by the project sponsors. For this reason, this study would analyze the effect of risk and government participation on leverage through the two main sectors of infrastructure projects, namely the transportation sector and the energy sector, and derivating risk to political risk and financial risk. The objects of research were 976 infrastructure projects listed in the Asian Development Bank during 2007−2016. We use censored regression to examine the model by infrastructure sectors, both as individual and through interaction effects. The analysis showed that overall, leverage of infrastructure projects was rather influenced by financial risk than by political risk. However, the leverage of infrastructure projects in the transportation sector was more vulnerable to risk than that in other sectors.