Essays on Online Marketplaces
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Abstract
This dissertation is three chapters on online marketplaces. The first marketplace that I investigate is online auction platforms, where I
investigate the impact that default penalties have on bidding in
common-value contexts. Due to the existence of the winners curse and the
fact that bidders can observe all the bids after the auction closes, winning
bidders have an incentive to decline to pay their bids when their signal
about the item's value is not representative of the average bid. I build a
structural model of bidding, and estiamte the parameters using data scraped
from the internet, and calculate counterfactual default policies. The second
marketplace that I analyze is Amazon's, where third-party sellers sometimes
compete with Amazon itself in the market for a given product. The impact of
Amazon participating as a seller in one of the markets that it hosts has
received a lot of theoretical attention, but limited applied analysis. Using
a large sample of Amazon products, we leverage differences-in-differences
designs to isolate the impact of Amazon participating in such a market and
find that Amazon entry drives prices down and increases sales, while not
driving third-party sellers out of the market. These results suggest that
entry by Amazon is beneficial for customers on its platform, potentially at
the expense of third-party sellers. I conclude by formulating a dynamic
model to answer the question of how third-party sellers should set prices
and invest in their products given the presence of Amazon. This model builds
off of the conclusions of the empirical work in Chapter 2, which motivates
expanding the static analysis presented there to a dynamic setting to answer
important questions about how third-party sellers operate in hybrid
marketplaces, how the platforms enforce price discipline, and the welfare
consequences thereof.
Description
Thesis (Ph.D.)--University of Washington, 2025
