Zhentong Lu is a Principal Researcher in the Financial Stability Department (FSD). His main research areas are applied econometrics, empirical economics and finance.
We propose a novel approach to estimating consumer demand for differentiated products. We eliminate the need for instrumental variables by assuming demand shocks are sparse. Our empirical applications reveal strong evidence of sparsity in real-world datasets.
Canada transitioned to a new wholesale payment system, Lynx, in August 2021. Lynx is based on a real-time settlement model that eliminates credit risk in the system. This model can require more liquidity; however, Lynx’s design allows Canada’s wholesale payments to settle efficiently.
In this paper, we empirically study how flagship entry in an online marketplace affects consumers, the platform, and various sellers on the platform. We find flagship entry may benefit consumers by expanding the choice set, by intensifying price competition within the entry brand, and by improving consumer perception for parts of the platform.
We show how participants in Canada’s new high-value payment system save liquidity by exploiting the new gridlock resolution arrangement. The findings have important implications for the design of these systems and shed light on financial institutions’ liquidity preference.
We quantitatively assess the changes in participants’ payment behaviour from modernizing Canada's high-value payments system to Lynx. Our analysis suggests that Lynx's liquidity-saving mechanism encourages liquidity pooling and early payments submission, resulting in improved efficiency for participants but with slightly increased payment delays.
This paper studies how the impact of a cyber attack that paralyzes one or multiple banks' ability to send payments would transmit to other banks through the Canadian wholesale payment system. Based on historical payment data, we simulate a wide range of scenarios and evaluate the total payment disruption in the system.
“Flagship Entry in Online Marketplaces” (with Ginger Zhe Jin, Xiaolu Zhou, Lu Fang), Journal of Industrial Economics, November 2025.
“From LVTS to Lynx: Quantitative Assessment of Payment System Transition” (with Ajit Desai, Hiru Rodrigo, Jacob Sharples, Phoebe Tian and Nellie Zhang), Journal of Payments Strategy & Systems, April 2023.
“Quantifying the economic benefits of payment modernization: the case of the large-value payment system” (with Neville Arjani and Fuchun Li), Journal of Financial Market Infrastructures, March 2023.
“Semi-Nonparametric Estimation of Random Coefficient Logit Model for Aggregate Demand” (with Xiaoxia Shi and Jing Tao), Journal of Econometrics, August 2023.
“Estimating Demand for Differentiated Products with Zeroes in Market Share Data” (with Amit Gandhi and Xiaoxia Shi), Quantitative Economics, May 2023.
“Estimating Multinomial Choice Models with Unobserved Choice Sets,” Journal of Econometrics, February 2022.
“The Effects of Government Licensing on E-Commerce: Evidence from Alibaba” (with Ginger Zhe Jin, Xiaolu Zhou, Chunxiao Li), Journal of Law and Economics, February 2022.
“Not too much nor too little: Salience bias in mobile plan choices” (with Haofeng Jin, Liqiang Huang and Junsheng Dou), Telecommunications Policy, May 2021.
“Examining the Impact of Home Purchase Restrictions on China’s Housing Market”, (with Jian Hong and Sisi Zhang), China Economic Review, June 2021.
