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Last updated May 2026
Basics
| Name | Minnie Cui |
| minnie.cui@wisc.edu | |
| Url | https://minnie-cui.github.io/ |
Education
-
2022 - Present Madison, WI
PhD
University of Wisconsin-Madison
Joint Economics & Finance
-
2022 - 2024 Madison, WI
MS
University of Wisconsin-Madison
Economics
-
2021 - 2022 Austin, TX
MS
University of Texas at Austin
Data Science
-
2014 - 2018 Toronto, ON
BA Hons.
University of Toronto
Economics
Work
-
2024 - Present Research Assistant to Prof. Jean-Francois Houde
University of Wisconsin-Madison
-
2022 - Present External Academic Consultant
Bank of Canada
-
2021 - 2022 Analyst
Bank of Canada
-
2018 - 2021 Research Assistant
Bank of Canada
Awards
- 2026
Young Scholars Best Paper Award
Georgia Tech–Atlanta Fed Household Finance Conference
- 2025
Best Third Year Finance Research Paper Scholarship
University of Wisconsin-Madison
- 2024, 2025
Juli Plant Grainger Summer Research Fellowship
University of Wisconsin-Madison
- 2022 - 2026
Doctoral Fellowship
Social Sciences and Humanities Research Council
- 2020
Women in Economics Scholarship
Bank of Canada
- 2018
Best Undergraduate Paper
Canadian Economics Association
- 2017
President's Scholar Program Scholarship
University of Toronto
Publications
-
2026 Adverse Selection and Learning in Consumer Credit Market
Working Paper
This paper highlights a trade-off in credit markets between regulatory safeguards for informed consent and the informational frictions they can amplify. In our empirical setting, we find that requiring lenders to garner explicit consent prior to raising clients' credit limits induces adverse selection. We find disproportionately higher take-up among riskier borrowers, as measured by increased utilization, delinquency, and charge-offs, which worsens the risk profile of accounts that receive a credit limit increase. In response to the policy, we find that lenders decreased the size of credit limit increases, yet simultaneously gave more frequent limit increases. We develop a model of lender credit limit provision to study the role of adverse selection and learning. We show that learning from acceptance decisions can rationalize lenders' increased frequency of credit limit increases, while adverse selection can rationalize the decline in the size of credit limit increases.
Skills
| Coding | |
| Python | |
| Julia | |
| Stata | |
| Matlab | |
| R | |
| HTML/CSS |
| Computing | |
| Azure | |
| AWS | |
| Slurm-based HPCs |
| Data | |
| Web-scraping | |
| Modeling | |
| Simulation |
Languages
| English | |
| Native |
| Mandarin | |
| Native |
| French | |
| Fluent |
| German | |
| Beginner |