TARC ESRC Legacy Status

TARC ESRC 旧状态

• 批准号: ES/X003973/1
• 负责人: Christos Kotsogiannis
• 金额: $ 12.49万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FX003973%2F1
• 关键词: TARC; ESRC; Legacy; Status

During the Legacy Status period, the Research Centre will communicate its research findings and impact-led work to the widest possible audience of international tax researchers. Dissemination takes various forms, including through the organisation of workshops, conferences and specialised capacity building seminars and builds on the significant track record of international events organised by TARC which demonstrates that the Research Centre has developed the expertise required to continue to do so successfully. The Research Centre will also build additional capacity through engagement with researchers and policymakers from Revenue Authorities and Government bodies in developing countries, and particularly Africa. Assisting developing countries in their efforts to improve revenue mobilization and achieve sustainable development has been a key research and impact priority of the Centre. Through TARC's continuing programme of specialised seminars given the Revenue Authorities in developing countries, knowledge transfer is achieved and much-needed capacity building is enhanced. The Research Centre will also broaden its extensive research and policy network of International Fellows, and its successful active visitors programme. This proposed activity will contribute to maximising the international visibility of the Centre and to boosting global knowledge transfer, thereby enhancing TARC's reputation as an international hub where ideas are articulated and developed. TARC has already built up an excellent network of stakeholders - including but not restricted to: the Tax Administration Diagnostic Assessment Tool (TADAT), International Monetary Fund; World Bank: OECD; Independent Authority of Public Revenue of the Hellenic Republic; Rwanda Revenue Authority; Bulgarian National Revenue Authority (BNRA): Welsh Government: African Tax Administration Forum (ATAF); Her Majesty's Revenue and Customs; the Directorate General of Taxation of Cameroon; Namibia Revenue Authority: the Digital Economy Taxation Foundation and the Vienna University of Economics and Business - and will be developing this engagement further in order to disseminate TARC's research and further policy engagement and impact. These collaborations have had research and policy impact. The collaboration with BNRA has contributed to significant revenue gain for Bulgaria and more efficient targeting of tax audits, to the extent that it generated an impact statement from the BNRA to the OECD which emphasise the impact: 'To combat VAT fraudulent transactions the Bulgarian National Revenue Agency (BNRA) for over ten years has been using a two-step process. This two-stage process discretely combines data analytics with operational knowledge. As such it is highly labour-intensive as requires input from the most experienced BNRA tax professionals In 2019 a co-operation was established between the BNRA and the Tax Administration Research Centre (University of Exeter Business School), and University College London. The main objective of this co-operation was to develop a scalable predictive model, which automatically identifies missing traders. A key aspect of the methodological approach developed is that the network structure of all VAT transactions (through sales/purchases invoices) provides important information which can (and should) be used to identify abnormal VAT transactions through the production chain. In early 2021, BNRA started implementing the predictive model, partially utilising the information structure emerging from the rich VAT transactions data collected. The first results have shown that such an approach can achieve both faster identification of fraudulent VAT transactions, but also a significantly higher proportion of identified real missing traders. This means the time a missing trader begins its fraudulent activities and the time it is identified by BNRA is on average reduced by 15%. Importantly, the predictive model can now identify fraudulent transactions

在遗产地位期间，研究中心将向尽可能广泛的国际税务研究人员宣传其研究成果和影响导向的工作。传播采取各种形式，包括通过组织讲习班，会议和专门的能力建设研讨会，并建立在TARC组织的国际活动的重要记录的基础上，这表明研究中心已经发展了继续成功开展工作所需的专业知识。研究中心还将通过与发展中国家，特别是非洲国家税务当局和政府机构的研究人员和决策者接触，建设更多的能力。协助发展中国家努力改善收入调动和实现可持续发展一直是国贸中心的一个关键研究和影响优先事项。通过TARC为发展中国家税务当局举办的持续专业研讨会方案，实现了知识转让，加强了急需的能力建设。研究中心还将扩大其广泛的国际研究员研究和政策网络，以及其成功的积极访问者方案。这一拟议活动将有助于最大限度地提高该中心的国际知名度，促进全球知识转让，从而提高TARC作为阐述和发展思想的国际中心的声誉。TARC已经建立了一个优秀的利益攸关方网络，包括但不限于：税务管理诊断评估工具、国际货币基金组织、世界银行、经合组织、希腊共和国独立公共收入管理局、卢旺达税务局、保加利亚国家税务局、威尔士政府、非洲税务管理论坛、英国税务和海关总署;与喀麦隆税务总局、纳米比亚税务局、数字经济税务基金会和维也纳经济和商业大学的合作--并将进一步发展这种合作，以传播TARC的研究和进一步的政策参与和影响。这些合作产生了研究和政策影响。与BNRA的合作为保加利亚带来了可观的收入收益，并提高了税务审计的针对性，以至于BNRA向经合组织提交了一份影响声明，其中强调了这一影响：“为了打击增值税欺诈交易，保加利亚国家税务局（BNRA）十多年来一直采用两步流程。这个两阶段过程将数据分析与运营知识相结合。2019年，BNRA与税务管理研究中心（埃克塞特大学商学院）和伦敦大学学院建立了合作关系。此次合作的主要目标是开发一个可扩展的预测模型，该模型可以自动识别缺失的交易者。所开发的方法的一个关键方面是，所有增值税交易（通过销售/采购发票）的网络结构提供了重要信息，可以（并且应该）用于识别整个生产链中的异常增值税交易。2021年初，BNRA开始实施预测模型，部分利用从收集的丰富增值税交易数据中产生的信息结构。第一个结果表明，这种方法可以实现更快地识别欺诈性增值税交易，而且识别出的真实的失踪交易者的比例也明显更高。这意味着失踪交易者开始欺诈活动的时间以及BNRA识别的时间平均减少了15%。重要的是，预测模型现在可以识别欺诈交易