A Theory Model of Digital Currency with Asymmetric Privacy

• 成果类型: Article; Early Access
• 署名作者: Tinn, Katrin
• 署名单位: McGill University; Centre for Economic Policy Research - UK
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2024.06830
• 发表日期: 2025
• 页码: 1225-1244
• 关键词: Bayesian learning; Central bank digital currency; costly verification; Data Privacy; digital currency design

摘要

This paper considers introducing asymmetric privacy in the design of central bank digital currencies (CBDC) and digital currencies more generally to preserve the privacy of money spent while keeping the benefits of digital records for money received. It is shown that this feature would help minimize real distortions between consumers, firms, and financiers while enabling tax optimization and better access to external financing. Protecting the privacy of consumers is desirable from a welfare and efficiency standpoint as long as there exist noticeable privacy concerns. Implementing asymmetric privacy is technologically feasible, using, for instance, zero-knowledge proofs or other privacy tools.