Ph.D. candidate in Computer Science. Theory, AGT, CS+Law.

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Posts

Future Blog Post

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Blog Post number 1

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portfolio

publications

The People’s Republic of China’s Digital Yuan: Its Environment, Design, and Implications

Published in ADBI Discussion Paper Series, 2022

The People’s Republic of China (PRC) has rapidly achieved a relatively high degree of financial inclusion (access of individuals to financial products and services) as a result of the development of various large-scale financial platforms using financial technology (fintech) to reduce the cost of providing financial services. Most notable are the two companies Ant Group and Tencent, which started in digital payments but have branched out into other bank-like services, such as investment products and loans. At the same time, the People’s Bank of China (PBC) has been developing a central bank digital currency (CBDC), specifically the digital yuan. The digital yuan has a link to the legacy yuan in value terms but could act for retail digital transactions in a centralized payment system. This paper examines the likely contributions of the digital yuan to financial inclusion and financial stability in the PRC and includes the following: A description of the current state of digital payments in the PRC, including the role of non-banking platforms, such as Ant Group’s Alipay and Tencent’s WeChat Pay, as well as that of commercial banks. A description of the current state of digital finance in the PRC. A description of the current state of financial inclusion in the PRC. A description of the PBC’s digital yuan project, including the modalities available to retail users (individuals and firms), the mechanisms (such as bank intermediaries) that can make the digital yuan available to such users, and the settlement processes. An analysis of the expected contribution of the PBC’s digital yuan to financial stability, taking into account the possible effects of the introduction of the digital yuan on the assets and liabilities of commercial banks and on private borrowing behavior as well as the possible impacts on non-bank firms, such as Ant Group and Tencent. An analysis of the expected contribution of the PBC’s digital yuan to financial inclusion, taking into account the expected value contributions of the digital yuan to retail users beyond what they obtain from the current system.

Recommended citation: Fullerton, E.J., & Morgan, P.J. (2022) The People’s Republic of China’s Digital Yuan: Its Environment, Design, and Implications. ADBI Discussion Paper 1306. Tokyo: Asian Development Bank Institute. https://dx.doi.org/10.2139/ssrn.4204153
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Constant-Approximate and Constant-Strategyproof Two-Facility Location

Published in The International Symposium on Algorithmic Game Theory (SAGT), 2025

We study deterministic mechanisms for the two-facility location problem. Given the reported locations of n agents on the real line, such a mechanism specifies where to build the two facilities. The single-facility variant of this problem admits a simple strategyproof mechanism that minimizes social cost. For two facilities, however, it is known that any strategyproof mechanism is Omega(n)-approximate. We seek to circumvent this strong lower bound by relaxing the problem requirements. Following other work in the facility location literature, we consider a relaxed form of strategyproofness in which no agent can lie and improve their outcome by more than a constant factor. Because the aforementioned lower bound generalizes easily to constant-strategyproof mechanisms, we introduce a second relaxation: Allowing the facilities (but not the agents) to be located in the plane. Our first main result is a natural mechanism for this relaxation that is constant-approximate and constant-strategyproof. A characteristic of this mechanism is that a small change in the input profile can produce a large change in the solution. Motivated by this observation, and also by results in the facility reallocation literature, our second main result is a constant-approximate, constant-strategyproof, and Lipschitz continuous mechanism.

Recommended citation: Fullerton, E.J., Hu, Z., Plaxton, C.G.: Constant-Approximate and Constant-Strategyproof Two-Facility Location (2025). In: Proceedings of the 18th International Symposium on Algorithmic Game Theory. (Sep 2025)
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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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