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Job Market Paper

Cashless Payment and Financial Inclusion [SSRN Link] [pdf]

JFI/FIRS Best Doctoral Paper Award (2022)

AsianFA Best Doctoral Paper Award (2022)

EEA/UniCredit Econ Job Market Best Paper Runner-Up Award (2022)

PIIRS Graduate Student Research Award (2022)

Selected Presentations: NBER Chinese Economy Meeting 2022, MIT GCFP Conference 2022, EFA 2022, FIRS 2022, NFA 2022, MFA 2022, UConn Finance Conference 2022, Economics of Payments XI 2022, CB&DC JMC Workshop 2022

Abstract: Can in-person cashless payment improve credit provision to the underprivileged? I study Alipay, a BigTech platform that acts as a one-stop-shop for financial services for more than 1 billion users. Using a representative sample of Alipay users with detailed information on their consumption, credit, and investment activities, I exploit a natural experiment to estimate the effects of cashless payment adoption. The use of cashless payment in a month increases the likelihood of gaining access to credit in the same month by 56.3%. Conditional on having credit access, a 1% increase in the cashless payment flow leads to a 0.41% increase in the credit line. These effects are mainly present for the less educated and the older. To quantify the value of cashless payment data to the lender and consumers, I build and estimate a simple model and run a counterfactual in which the lender does not observe these data. I find that credit lines rise by 57.7% on average, consumer surplus rises by 0.5% of median disposable income, and the increase in lender profit is about 41.3% of the increase in consumer surplus.

Working Papers

Data Privacy and Digital Demand [NBER Link] [pdf]

with Long Chen,  Yadong Huang and  Wei Xiong

Selected Presentations: NBER Economics of Privacy Conference 2022, AFA 2022, CB&DC Virtual Seminar 2021

Media Coverage: VoxEU, VoxChina

 

Abstract: We combine survey and behavioral data to analyze consumers’ data-sharing choices in a realistic setting in which they exchange personal data for digital services. We find that respondents with stronger privacy concerns authorize more, rather than less, data sharing, confirming the data privacy paradox. Instead of attributing this paradox to the respondents’ unreliable survey responses, resignation from privacy, or behavioral biases, we uncover that privacy-concerned respondents have greater demands for digital services, which offset their privacy concerns. Our findings highlight a key tension for the data economy—privacy concerns and digital demands both grow with the deepening of digital services. 

Return to Venture Capital in the Aggregate [NBER Link] [pdf]

with Ravi Jagannathan and Jiaheng Yu

 

Selected Presentations: AFA 2020, ERFIN Workshop 2020

Abstract: We measure the aggregate return to all equity investors in various funding rounds of a venture company with the founders’ investments valued at their first-round pre-money valuations. We examine 17,242 ventures that had their first funding rounds during 1980 and 2006 and follow them till their exits or 2018 whichever is earlier. Our measure, unlike round-to-round and round-to-exit return measures, does not require valuation information for interim funding rounds, which are mostly missing. The potentially large bias in reported post-money valuations pointed out by Gornall and Strebulaev (2020) does not affect our return measure.

Consumer Demand for Digital Money [preliminary draft available upon request]

with Cameron Peng

 

Selected Presentations: WEFIDEV 2022

Abstract: The functioning of money increasingly relies on its digital forms rather than physical cash. Using comprehensive portfolio and consumption data of a representative sample of Alipay users, we study the drivers of consumer demand for digital money. In our setting, individuals allocate wealth between cash, digital money, and an illiquid asset. Digital money can be used immediately for consumption and bears time-varying interest. With an inventory framework, we quantify the welfare implications of the digital money adoption.

Investor’s Responses to Market Fluctuations [preliminary draft available upon request]

with Lina Han and Xuan Luo

 

Selected Presentations: Whitebox Advisors Ph.D. Conference 2020

Abstract: This paper examines how individual investors respond to the market price fluctuations, using unique individual-level transaction data from a trading experiment and the same individuals’ real trading history on the Alipay app. We find that, in response to exogenous price movements in the experiment, investors tend to be contrarian traders. The magnitude of investors’ response is asymmetric in downturn and upturn markets. Sophisticated investors tend to be more contrarian than the less sophisticated ones. We further document that investors’ contrarian styles are persistent in the experiment and real transactions. The results imply that investors use simple heuristics from the price movement when they make investment decisions in the real world.

Work in Progress

Cashless Payment Adoption

with Daixi Chen and Long Chen

Informed Consent and Data Sharing

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