Working Papers
Working Papers
Generative AI tools have been widely integrated in online matching platforms. Although these tools could improve writing quality, they could also introduce issues of writing content convergence, which could result in increased screening difficulty and lower matching efficiency. In this paper, we study Job Post Generator, a generative AI tool launched by a freelance platform, Upwork. After its introduction, the average pairwise cosine similarity of job postings increased by 18.5% from 2023 March to 2024 September. We find that clients who use the Job Post Generator match with freelancers more quickly on average. However, those who rely heavily on AI-generated content with minimal modifications experience longer matching times. In contrast, clients who actively edit and customize AI-generated job postings experience significant improvements in matching efficiency, benefit from lower payment costs, and report higher satisfaction with freelancers' performance. Our paper provides evidence that homogeneity of job postings due to AI-driven writing can negatively impact online job matching efficiency. Our findings suggest that online platforms offering generative AI tools should encourage users to modify and personalize AI-generated content to achieve better outcomes.
Presentations:
NUS Applied Economics Student Workshop, NUS Behavioral & Experimental Econ Therapy, NUS Graduate Seminar, ISMS Marketing Science Conference (Washington D.C.), 2025 INFORMS International Conference (Singapore, scheduled)
This article examines endogenous consumer reviews and their impacts on seller pricing on Steam, an online video game platform. We find that discounts generate a positive post-promotion effect on sales through review accumulation. We build and estimate a structural model that incorporates endogenous consumer reviews and forward-looking game sellers. Counterfactual results demonstrate that without accounting for the effects of reviews, game prices would be 14% higher. We quantify that the reviews have great externalities. The whole system generates millions in surplus for both parties, particularly benefiting new and indie game sellers, while further fostering market diversity.
Presentations:
NUS Applied Economics Student Workshop, APIOC 2023 (Hong Kong), 22nd Annual Conference of IIOC (Rising star session, Boston), SMU Raising Star Conference*, AMES (Hangzhou), 2025 CES North American Conference (Rising star session, Michigan)
Online freelance platforms have expanded access to flexible work, but persistent inequalities remain. This paper examines whether generative AI can help reduce disparities faced by disadvantaged workers, using data from a major online labor marketplace. Among various worker characteristics, the most pronounced effects appear along the dimension of language proficiency. Since ChatGPT’s introduction, the gap in earnings and job count between native and non-native English speakers has narrowed. Non-native speakers have gained access to more complex, higher-paying jobs and experienced lower job displacement. These findings suggest that generative AI can expand opportunity and reduce barriers in digital labor markets.
Presentations:
NUS Applied Economics Student Workshop, NUS Real Estate brownbag*, NUS Marketing brownbag, NUS Applied Micro SIG brownbag*.
This article studies a major ride-hailing service provider in Singapore, which offers subsidies for both consumer side and driver side. We investigate the firm's optimal subsidy strategy in the presence of real-time externalities. By using a zone-time panel of 329,319 observations we estimate both the customer demand and driver labor supply. We also simulate the causal impact of demand and supply conditions on the surge multiplier, customers' waiting time as well as drivers' roaming time. The estimation results suggest that customers are price elastic and place a high value on time; while drivers are even more elastic to price and time than customers. Our counterfactual analysis indicates that considering real-time externalities, instead of subsidizing drivers and consumers at the same time, it will be more profitable for the platform to subsidize only the customer side. However, in contrast, the merely driver side subsidy is likely to generate the highest social welfare.
Presentations:
NUS Applied Economics Student Workshop, NUS Graduate Seminar, IAAE 2024 International Association for Applied Econometrics (Xiamen), 2024 CES China Conference (Hangzhou), NUS Applied Micro SIG brownbag, 51st conference of EARIE (Amsterdam).
Note: * presented by a co-author.