In the dissertation, we study the value of reputation in a market prone to adverse selection
and also the incentives of the individuals in that market to participate in the reputation
mechanism. Ever since [Akerlof, 1970], it is known that adverse selection can hinder trade.
Reputation can be used as a possible mechanism in mitigating adverse selection problems,
resolving the inefficiencies caused by asymmetric information and help the marketplace to
thrive. There are a number of examples of such online markets which have been conceived,
have survived and have thrived during the internet age. These markets have been kept
alive by their built-in reputation systems. In this dissertation, I focus on the effects of
reputation on eBay online market.
In chapter 1, I study how actors in a marketplace can introduce mechanisms to overcome
adverse selection, and I focus on one mechanism employed by eBay: sellers’ reputation.
Using a unique data set that follows sellers on eBay over time, I show that reputation,
according to various measures, is a major determinant of variations in the prices of homogeneous
goods sold on eBay, in particular, for iPods. Inspired by this observation, I develop
a model of firm dynamics where firms have heterogeneous qualities that are unobservable
by consumers. Reputation is used as a signal of private information to buyers in order
to improve allocations. I structurally estimate this model to uncover deep parameters of
buyers’ utility and sellers’ costs as well as sellers’ unobservable qualities. The estimated
model suggests that reputation has a positive effect on the expected profits of high quality
sellers and their market shares. I perform a counterfactual to establish the value of reputation.
Removing reputation mechanisms put in place by eBay will increase the profits of low quality sellers and will decrease the profits of high quality sellers. Moreover, removing
reputation mechanisms significantly increases the market share of low quality sellers and
decreases the market share of high quality sellers. Finally, buyers’ welfare is significantly
improved as a result of the reputation mechanism.
In chapter 2, we focus on incentives of buyers and sellers in leaving feedback and their
effect on emergence of reputation systems in online markets. To do so, we analyze how
such systems work and we turn our focus on eBay. We start by analyzing the feedback behavior of buyers and sellers over time. We use a key policy change, that sellers cannot
leave negative feedback for buyers, as an identifier. Our data analysis points to the existence
of retaliation between buyers and sellers before the policy change. Furthermore, we
develop a model of feedback behavior as a dynamic game between buyers and sellers and
structurally estimate the model. The structural estimation further establishes the existence
of retaliation incentives between buyers and sellers. Finally, we perform various welfare
and counterfactual analysis.