自认机制在金融反腐败中的应用研究

金融反腐败的机制设计应该从金融监管政策入手,因为在金融监管及执法过程中存在着监管腐败问题。在金融监管执法活动中,构建具有腐败倾向特征的监管执法者对金融机构或其从业人员的违法行为监督执法的这样一个模型:在实施具有恰当的惩罚激励措施的自认制度时,一个福利最大化的政府可以防范监管者和被监管者之间合谋腐败的发生,可以通过降低官僚作风、保持较少的监督执法官员、降低监管寻租以增加社会福利,为弱化或消除金融腐败带来良好的治理效应。     

The effect of natural and built environmental characteristics on pedestrian-vehicle crash severity in Ghana

Despite the benefits of walking as a means of travelling, walking can be quite hazardous. Pedestrian-vehicle crashes remain a major concern in Ghana as they account for the highest percentage of fatalities. The objective of this study is to determine the effect of both natural and built environmental features on pedestrian-vehicle crash severity in Ghana. The study is based on an extensive pedestrian-vehicle crash dataset extracted from the National Road Traffic Accident Database at the Building and Road Research Institute (BRRI) of the Council for Scientific and Industrial Research (CSIR), Ghana. Using a multinomial logit modelling framework, possible determinants of pedestrian-vehicle crash severity were identified. The study found that fatal crashes are likely to occur during unclear weather conditions, on weekends, at night time where there are no lights, on curved and inclined roads, on untarred roads, at mid-blocks and on wider roads. The developed model and its interpretations will make important contributions to road crash analysis and prevention in Ghana with the possibility of extension to other developing countries. These contributing factors could inform policy makers on road design and operational improvements.     

A hybrid clustering and classification approach for predicting crash injury severity on rural roads

As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011–2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.     

Accounting standards,regulatory enforcement,and innovation

We examine the effects of accounting standards and regulatory enforcement on entrepreneurial innovation and social welfare. When the entrepreneur issues a financial report that violates the accounting standards, a regulatory agency may detect the violation and bring charges. We find that when regulatory penalties are relatively insensitive to the magnitude of the violation, optimal standards are sufficiently low that they induce full compliance, and increase as the intensity of enforcement increases. In contrast, when regulatory penalties are sensitive to the magnitude of the violation, optimal standards induce non-compliance and decline as the intensity of enforcement increases.     

A fine-scale spatial analytics of the assessment and mapping of buildings and population at different risk levels of urban flood

Nowadays, urban flooding is becoming a severe issue in most of the developing and developed countries. The growth of the urbanization rate is also increasing, and the United Nations (UN) projected that 68 % of the world’s population would live in urban areas by 2050. People tend to migrate from rural to urban areas, which expose them more vulnerable to urban floods. The flood-related damages and deaths are increasing every year globally. Using the Birmingham city, Alabama (AL), USA as the study area, the objective of this research is to assess potential damage risks due to flood exposure of buildings and population in an urban area. Different social and environmental factors influence urban floods in an urban area. This paper considered elevation, slope, flow accumulation, land-use, soil types, and distance from the river as significant influential factors to urban flooding. The flood risk model hence can be developed by using an integrated GIS and cartrographic approach, in which we assessed and assigned weights to these factors and formed a GIS risk assessment model, which shows the level of flood risks in the floodplain areas of Birmingham and quantifies and maps both commercial buildings, home buildings, and populations’ exposed to flooding risks. This study found that the Valley Creek area is the highest flood risk zone in Birmingham, and about 48.85 percent of Valley Creek’s floodplain area will face very high flood risk. The findings further reveal that total number of 5602 people are living in high and very high flood risk zones in Birmingham that approximates 44.04 % of the total population in this floodplain area. The physical vulnerability is also assessed, and findings suggest that the Valley Creek zone has the highest percentage of residential (i.e., 56.14 %) and commercial (i.e., 75.34 %) buildings located in very high flood risk areas. Our study providing a GIS risk assessment approach to locating and mapping the areas, buildings, and populations from the most to the least at risks with a fine spatical scale for urban flood risk management. The numbers of vulnerable buildings and populations within each risk category are quantified and their distributions are mapped. Therefore, revealing population’s and buildings’ risks and their geographic information, this flood risk assessment can help local governments and communities prepare better to take actions against future urban flood events in Birmingham, and this integrated GIS and cartographic analysis for fine flooding assessments can be applied to other urban areas for flood mitigation and risk management.     

Information system and corporate income tax enforcement: Evidence from China

This paper adds the literature by investigating the effect of information system on corporate income tax (CIT) enforcement. We exploit the regional variations generated by the implementation in 2013 of the third stage of the China Tax Administration Information System (CTAIS-3) pilot. The CTAIS-3 is a nationally unified information system that significantly reduces information asymmetry between different tax authorities across regions. We find that the CTAIS-3 pilot significantly reduced firms’ conforming and non-conforming tax avoidance. The enhanced tax enforcement is particularly prominent if a firm is of a smaller size, or is administrated by the State Administration of Taxation, or is a non-state-owned enterprises, or locates in cities with a higher level of local fiscal pressure. Furthermore, we show that the CTAIS-3 improved the CIT enforcement by deterring firms from underreporting accounts receivable, as well as over-reporting accounts payable, inventory and the number of employees. In general, it would be more difficult for firms to hide profits from tax authorities under the CTAIS-3.     

I don't want to be a rule enforcer during the COVID-19 pandemic: Frontline employees' plight

This research explores the pandemic-related experiences of frontline employees (FLEs) relative to customer rule-enforcement interactions within retail and service industries. Using a survey, incorporating closed-ended and CIT questions, we investigated, from the FLEs' perspectives, the occupational stress of rule-enforcement, company expectations of FLEs regarding rule enforcement, and the emotional impact of customer interactions on FLEs. Results indicate that several customer misbehaviors, such as not following rules and being rude, produce significant occupational stress. Further, based on our CIT assessments, many of the FLEs’ recounted rule-enforcement incidents involved negative customer reactions, translating to heightened negativity for FLEs due to emotional contagion.     

Exploring online comments from a strategic marketing stance to reduce wildlife crime

Illegal wildlife trade (IWT) is an omnipresent global threat to ecological, social, and economic systems. Marketing expertise can aid in the mitigation and reduction of crime against wildlife using a variety of mechanisms. This paper focuses on how social media usage relates to the framing of conservation appeals. By studying the content of existing blogs, articles, white papers, and other online postings, we extract relevant themes and concepts. Conducting an unguided semantic analysis of our data, we analyzed messaging appeal strategies and the underlying social or informational frameworks they employ. Using literature on advertising appeal types and contrasting social/emotional with knowledge-based/informational messaging strategies, we identified how wildlife crime prevention content employs these rhetorical framing mechanisms. Through the lens of social learning theory, our study proposes messaging strategies as a framework for understanding online content. Crimes against wildlife are creating increasingly severe ecological, economic, and social damage within international political and social communities; individuals learn from and engage with online content, therefore appropriate framing mechanisms can aid marketers in designing effective prevention appeals.     

A re-examination of accruals quality following restatements

Empirical research from the first years following the Sarbanes-Oxley Act (SOX) in the US suggests that firms improve accruals quality following restatements, but the materiality of restatements has declined since then. This decline may affect firms' responses to restatements, and hence we re-examine whether restatements are associated with subsequent improvements in accruals quality in a more recent sample. We compare the changes in accruals quality of firms restating between 2000 and 2014 with that of a control group. We do not find that firms improve accruals quality more than the control group following a restatement, even when we isolate the types of restatements considered to be most material. However, we do find that restatements followed by the most negative stock market reactions are associated with a relative increase in accruals quality, indicating that only restatements deemed very severe by investors lead to subsequent improvements in accruals quality. Our results suggest that firms' responses to restatements have changed concurrently with the trend of fewer and less material restatements in recent years.     

Incomplete Enforcement of Pollution Regulation: Bargaining Power of Chinese Factories

Only a limited number of papers haveempirically examined the determinants of themonitoring and enforcement activities performedby the environmental regulator. Moreover, mostof these studies have taken place in thecontext of developed countries. In this paper,we empirically examine the determinants of theenforcement of pollution charges in China.More precisely, we seek to identify thecharacteristics which may give firms more orless bargaining power with local environmentalauthorities pertaining to the enforcement(collection) of pollution charges. Firms fromthe private sector appear to have lessbargaining power than state-owned enterprises.Firms facing an adverse financial situationalso appear to have more bargaining power.Finally, we also show that the higher thesocial impact of a firm's emissions (asmeasured by the presence of complaints), thesmaller the bargaining power of the firms withlocal environmental authorities.