  We perform a simulation-based analysis of keyword auctions modeled as
one-shot games of incomplete information to study a series of mechanism design
questions. Our first question addresses the degree to which incentive
compatibility fails in generalized second-price (GSP) auctions. Our results
suggest that sincere bidding in GSP auctions is a strikingly poor strategy and
a poor predictor of equilibrium outcomes. We next show that the rank-by-revenue
mechanism is welfare optimal, corroborating past results. Finally, we analyze
profit as a function of auction mechanism under a series of alternative
settings. Our conclusions coincide with those of Lahaie and Pennock [2007] when
values and quality scores are strongly positively correlated: in such a case,
rank-by-bid rules are clearly superior. We diverge, however, in showing that
auctions that put little weight on quality scores almost universally dominate
the pure rank-by-revenue scheme.
