Chungsang Tom Lam
Assistant Professor
John E. Walker Department of Economics
Clemson University
Fields of interest:
• Labor Economics
• Economics of Network
• Ditgital Economy
• Industrial Organizations
Working Papers
Type of Peers Matters: A Study of Peer Effects of Friends, Studymates and Seatmates on Academic Performance (with Julian Tszkin Chan)
This paper studies the peer effects of friends, studymates, and seatmates on academic performance. We obtain the information of social networks, personality traits, and cognitive ability measures from a unique data set based on a survey we conducted in three schools in Hong Kong. We estimate a social interaction model which accounts for endogenous network formation and correlation between multiple networks. Our results show that the cognitive ability of studymates and the conscientiousness of friends positively affect a student’s mathematics exam score, while the conscientiousness of studymates and the cognitive ability of friends do not produce such an effect. We find that students with elder siblings are less affected by the cognitive ability of studymates, but the effect of conscientious friends is not related to that. By contrast, we find no such effect from seatmates. These results are consistent with the idea that studymates influence each other through discussing and teaching where cognitive ability is valued. On the other hand, friends influence each other by creating an atmosphere of studying, so being conscientious is more important. Our study hint at the way different types of peer work and which particular qualities are important for each peer type.
Incentive Contracts, Adverse Selection, and Risk Transfer: Evidence from Procurement (with Meng Liu)
Multi-attribute auctions, designed to address multi-dimensional preference, make a good case study where incentive provisions interact with competition. By studying Cost+Time'' highway procurement that aims to incentivize timely project delivery, we show the lack of complementarity between incentive contracts and bidding mechanisms that can yield sub-optimal outcomes. Our theory demonstrates that bidders, facing high-powered incentives and production uncertainty, optimally skew their time bids while transferring production risk to buying agencies. This gaming behavior leads to adverse selection and efficiency loss, in that a less-efficient bidder can outbid the efficient bidder due to the misalignment between bidder types and the auction rule that determines winners. We estimate our model using data from the California Department of Transportation and find that 18% of auctions are allocated to inefficient bidders. Counterfactual analyses suggest that procurement schemes with lower incentives can yield less mis-allocation with lower production costs and less buyer budget pressure.
Measuring Consumer Surplus in the On-Demand Economy: the Case of Ride Sharing (with Meng Liu)
Uber and Lyft, two pioneer ride-sharing platforms that serve as alternatives to traditional taxi cabs, have seen dramatic increase in adoptions from both consumers and driver-partners across the globe over the last few years. To understand their roles and impacts on the whole economy, we tackle the problem of consumer welfare of these ride sharing platforms by estimating a structural demand model for rides. In this model, consumers choose between Uber, Lyft, Taxi cabs, and the outside option'' based on price, convenience, brand effects, and unobserved characteristics. Our estimation and identification leverage on the unusually rich data set that combines taxi, Uber, and Lyft trip records from New York City, and Uber/Lyft surge pricing as well as wait time at granular location-time levels. Being among the first few, our work contributes to the understanding of the On-Demand Economy by providing evidence of consumer welfare increase due to vast satisfied instantaneous demand at minimal transaction costs.
Managing the release of consumable in-app purchases in competitive games (with Christopher Ryan and Michelle Wu)
A common practice for freemium games is to launch with a simple and intuitive design and release premium features over time in the form of in-app purchases (IAPs) to monetize players. We propose an optimal control model that yields insights into the optimality and economic justification of such an approach. Through analytically characterizing the game life cycle and optimal release pattern of IAP for certain structured instances, we characterize when games optimally launch with an initial period free of IAPs in order to maximize the growth of its player-base and later exploit this player-base for generating revenue by releasing IAPs. This strategy balances the tradeoff between the effects of IAP release on acquiring and retaining players with the revenue-generating potential of selling IAPs. Our model also admits comparative statics results on how exogenous factors, such as the social nature of the game, influence the optimal time of initial IAP release. In a numerical study, we show that a game can be permanently free if it generates revenues outside of player purchases, say through advertising revenue. We also consider the possibility of an operating loss during the free period due to per-player operating costs. We show the length of the loss period (while the game is totally free) and the magnitude of loss depends on exogenous factors, including the strength of word-of-mouth.
The Value of Free Players in a Freemium Game
Managing the size and growth of a social network: Habituation and exclusivity (with Chris Ryan)
Effects of the Duration and Benefit Level of Unemployment Insurance during the Great Recession: Evidence from Administrative Data (with Shan Jiang)