Bargaining breakdown plagues bargaining in environments with incomplete information. Does communication help or harm? On May 23, 2016, eBay Germany's Best Offer platform introduced unstructured communication allowing desktop users, but not the mobile users, to accompany offers with a message. Using this natural experiment, our difference-in-differences approach documents a 14% decrease in the the rate of breakdown among compliers. Though adoption is immediate, the effect is not. We show, using text analysis, that the dynamics are consistent with repeat players learning how to use communication in bargaining, and that the messaging strategies of experienced sellers are correlated with successful bargaining.

A growing body of empirical literature finds that consumers are relatively limited in how much they search over product characteristics. We assemble a dataset of search and purchase behavior from eBay to quantify the returns, and thus implied costs, to consumer search on the internet. The extensive nature of the eBay data allows us to examine a rich and detailed set of questions related to search in a way that previous structural models cannot. In contrast to the literature, we find that consumers search a lot: on average 36 times per purchase over 3 (distinct) days, with most sessions ending in no purchase. We find that search costs are relatively low, in the region of 25 cents per search page. We pursue the analysis further by, i) examining how users refine their search, ii) how search behavior spans multiple search sessions, and iii) how the amount of search relates to finding lower prices.

A common complaint about online auctions for consumer goods is the presence of ``snipers,'' who place bids in the final seconds of sequential ascending auctions with predetermined ending times. The literature conjectures that snipers are best-responding to the existence of ``incremental" bidders that bid up to their valuation only as they are outbid. Snipers aim to catch these incremental bidders at a price below their reserve, with no time to respond. As a consequence, these incremental bidders may experience regret when they are outbid at the last moment at a price below their reservation value. We measure the effect of this experience on a new buyer's propensity to participate in future auctions. We show the effect to be causal using a carefully selected subset of auctions from eBay.com and instrumental variables estimation strategy. Bidders respond to sniping quite strongly and are between 4 and 18 percent less likely to return to the platform.

Classical statistical inference of experimental data assumes that the treatment affects the test group but not the control group. This assumption will typically be violated when experimenting in marketplaces because of general equilibrium effects: changing test demand affects the supply available to the control group. We illustrate this with an email marketing campaign performed by eBay. Ignoring test-control interference leads to estimates of the campaign's effectiveness which are too large by a factor of around two. We present the simple economics of this bias in a supply and demand framework, showing that the bias is larger in magnitude where there is more inelastic supply, and is positive if demand is elastic.