税收违法黑名单制度是税务机关依照法律法规和政策规定，对特定重大涉税违法失信行为的纳税人，以黑名单的形式予以对外公布，并将相关信息推送多部门实施联合惩戒，以限制违法纳税人权益的一种制度。税收违法黑名单制度作为我国纳税信用体系建设的主要抓手之一，在震慑税收违法行为，引导依法诚信纳税，切实保护行政相对人合法权益，激发了市场活力、营造良好营商环境方面发挥了重要作用。从这项制度首次公布到现在已将近10年，制度的执行效果如何？是否有效抑制重大税收违法案件的发生？还存在哪些问题？虽然有不少研究从法律定位、制度建构、运行机制等进行了多方位探讨，但缺少实证数据的支持。此外，为完善失信约束制度，构建诚信建设长效机制，保障当事人合法权益，税收违法黑名单信用修复制度作为一项补充救济制度应运而生，在此背景下，对我国税收违法黑名单信用修复制度开展深入系统研究具有重要价值。

本文主要采用半结构式访谈法、参与式观察法和定量研究法，在梳理我国税收违法黑名单信用修复制度建设现状的同时，通过对2019-2023年北京市税收违法黑名单公布案件的实证分析，总结出北京市税收违法黑名单违法案件的主要特征。通过采用二元离散选择模型和典型案例分析得出影响失信主体信用修复的重要因素，针对性提出优化税收违法黑名单信用修复制度的建议。

研究发现，通过实施税收违法黑名单信用修复制度，不仅可以有效保障纳税人的合法权益，缓和征纳双方的对立关系，显著提升税收征管质效，还有助于规范市场秩序，促进税收法治的健康发展，为构建诚信社会奠定坚实基础。然而，制度标准不稳定、政策宣传不到位、违法成本相对较低、部门之间协作不顺畅等现实问题又在不同程度上影响了税收违法黑名单信用修复制度执行效果。

针对上述分析，为进一步优化税收违法黑名单信用修复制度，可以从以下四个方面入手：一是要保持制度和标准的稳定性，注重信用评价与修复制度的衔接性；二是要增加管理的人性化和便利性，差异化对待危害程度不同的失信主体；三是要深化信息优化与共享，搭建云平台，提供智能化、便捷化的信用修复渠道；四是要构建起多主体、全方位的纳税信用行为监督体系。

The tax violation blacklist system is a system in which tax authorities, in accordance with laws, regulations and policies, publish taxpayers with specific major tax violations and dishonest acts in the form of a blacklist, and push relevant information to multiple departments for joint punishment, in order to limit the rights and interests of taxpayers who violate the law. As one of the main starting points for the construction of China's tax credit system, the tax blacklist system has played an important role in deterring tax violations, guiding tax payment in good faith according to law, effectively protecting the legitimate rights and interests of administrative counterparts, stimulating market vitality and creating a good business environment. It has been nearly 10 years since the first announcement of this system. How has the system been implemented? Does it effectively inhibit the occurrence of major tax violations? What are the other problems? Although there are many studies from the legal positioning, institutional construction, operation mechanism and other aspects of the discussion, but the lack of empirical data support. In addition, in order to improve the credit breach restraint system, build a long-term mechanism for credit construction, and protect the legitimate rights and interests of the parties, the tax violation blacklist credit repair system came into being as a supplementary relief system, under this background, it is of great value to carry out in-depth and systematic research on the tax violation blacklist credit repair system in our country.

This paper mainly adopts semi-structured interview method,participatory observation method and quantitative research method.While combing the development and achievements of China's tax blacklist credit repair system,this paper summarizes the main characteristics of tax blacklist cases in Beijing through empirical analysis of the cases published in the tax blacklist of Beijing from 2019 to 2023.Through the use of binary discrete choice model and typical case analysis,this paper concludes the important factors affecting the credit repair of trust-breaking subjects,and puts forward targeted suggestions to optimize the tax blacklist credit repair system.

The research finds that the implementation of the credit repair system of the blacklist for tax violations can not only effectively protect the legitimate rights and interests of taxpayers, alleviate the antagonistic relationship between the two sides of the tax collection and significantly improve the quality and efficiency of tax collection and administration, but also help standardize the market order, promote the healthy development of the tax rule of law, and lay a solid foundation for the construction of a trustworthy society. However, the practical problems such as unstable system standards, inadequate policy publicity, relatively low illegal costs, and poor cooperation between departments have affected the implementation effect of the tax violation blacklist credit repair system to varying degrees.

In view of the above problems, in order to further optimize the credit repair system of tax violation blacklist, we can start from the following four aspects: First, to maintain the stability of the system and standards, pay attention to the cohesion of credit evaluation and repair system; Second, it is necessary to increase the humanization and convenience of management, and differentiated treatment of dishonest subjects with different degrees of harm; Third, it is necessary to deepen information optimization and sharing, build a cloud platform, and provide intelligent and convenient credit repair channels; The fourth is to build a multi-subject, all-round tax credit behavior supervision system.