Research
A Dynamic Structural Model for Pay-Per-Bid Auctions: Explaining the Excess Revenue Puzzle in Online Auctions
This paper studies pay-per-bid auctions, a type of auction where bidders incur a cost each time they place a bid. There is strong empirical evidence that these auctions can generate higher expected revenues than second price auctions. In particular, the data shows that pay-per-bid auctions generate revenue that is on average 50 percent higher than what can be achieved in second price auctions. In order to explain this excess revenue puzzle, I develop a general theoretical framework for pay-per-bid auctions where bidders are strategic and forward-looking. In this model, bidders have private valuations and can enter and exit throughout the duration of the auction. Bidders have uncertainty about how many other bidders are active in each round and I allow the bidders to have non-equilibrium beliefs about this number. I then propose a simulated method of moments estimator that can be used to recover the structural parameters even when bidders have biased beliefs. In the empirical application, I use data from an online auction website called Swoopo and I show that the excess revenues we observe cannot be generated by a model where bidders have rational expectations but is consistent with a model where bidders have biased beliefs. Finally, I quantify the effect of biased beliefs using counterfactual analysis. I find that the excess revenues we observe are not sustainable and without biased beliefs, the bidders may choose not to participate in these auctions.
Identification of Dynamic Models of Market Entry and Exit with Buy/Lease Decisions
This paper studies the identification of dynamic models of market entry and exit where firms can choose to buy or lease fixed inputs. We are particularly interested in the identification of counterfactual experiments that change the stochastic process of the state variables that relate to the selling price and/or leasing price of the fixed input. First, we show that without additional restrictions, the structural functions that represent entry cost, fixed cost and scrap value are not point identified. Second, for applications where the researcher has data on both leasing price and selling price of the fixed input, we propose plausible exclusion restrictions that provide point identification of our counterfactual experiments, despite the structural functions being nonidentified. Third, we propose a simple simulation based method to construct a confidence region for counterfactual choice probabilities in applications where counterfactual experiments are not point identified. We illustrate our results and methods using numerical experiments.
Transforming Rural Trade: The Impact of a Government-initiated E-commerce Platform on Local Specialty Sales (joint with Xintong Han, Shaojia Wang anmd Kefan Chen)
This paper empirically examines the impact of the launch of a Government-initiated E-commerce Platform (GEP) on the sales of local specialties, with a particular focus on China’s Pu’er tea market. Employing two-way fixed effects (TWFE) regressions on a panel dataset on 983 local households over 5 years, covering over 90% of the local tea farmers, we find that the introduction of the GEP leads to an average decline of 11.22% in offline household sales, while online sales experience an increase of 16.88%. This channel shift was observed at all levels of production and quality, yet the total volume of tea sales remained constant, suggesting that the GEP facilitated a more efficient allocation of sales between online and offline channels and increased profits. Further evidence shows that the platform was particularly beneficial to farmers who faced significant barriers to entry on traditional platforms, providing them with a more cost-effective alternative. Mechanism analysis suggests that the increase in online sales is primarily due to an increase in product variety rather than an increase in the number of online sellers. Overall, our study underscores the transformative potential of such E-commerce initiatives in specific markets and provides actionable insights for policymakers and practitioners.
Fit Classmates: The Effect of Peers on Exercise Habits in Students (joint with Zheng Pan, Xintong Han and Xuxian Zhang)
The influence of social networks on exercise habits and health capital accumulation is an area that is gaining significant attention. Using a nationally representative sample, this study investigates the role of peer groups in shaping the exercise behavior of junior high school students in China. By exploiting the random assignment of students to classrooms, we evaluate the effect of peers’ exercise habits on the likelihood of forming persistent exercise habits. Our empirical study affirms that having peers who exercise regularly has a robust and positive impact on the student’s own exercise habits. Further analysis shows that this effect is more pronounced for male students, while family income and geographic factors appear to have minimal influence. To explain this result, we identify challenges that female students face in forming intra-class friendships in junior high school, which subsequently reduces their potential to fully benefit from their peers. Finally, we highlight an important policy dilemma: while peer influence does promote exercise, it also has the unintended consequence of negatively affecting academic performance. The dual-faceted nature of the effect of peers complicates the design of effective policies, as initiatives aimed at increasing physical activity may come at the expense of the student’s academic achievement. Our study offers policymakers evidence-based guidelines to help them navigate the complexities of encouraging physical activity while also mitigating the potential consequences on academics.
Work in Progress
Evaluating the Efficiency of Canadian Spectrum License Auctions
Explaining Markup Heterogeneity in Pay-per-bid Auctions
Testing Informational Assumptions in Empirical Entry Games