We develop a demand system for a dynamic auction market with directed search. In each period, heterogeneous goods are exogenously supplied and sold by second price auction, and incumbent bidders choose which good to bid on and how much to bid. Bidder valuations are multidimensional, private and...

We develop a model of consumer search with spatial learning in which sampling the payoff of one product causes consumers to update their beliefs about the payoffs of other products that are nearby in attribute space. Spatial learning gives rise to path dependence, as each new search decision...

We develop and estimate a model of consumer search with spatial learning. Consumers make inferences from previously searched objects to unsearched objects that are nearby in attribute space, generating path dependence in search sequences. The estimated model rationalizes patterns in data on...

We develop a flexible yet tractable model of consumer search and choice, and applyit to the problem of product rankings optimization by online retail platforms. In themodel, products are characterized by an observable search index, which governs whatconsumers search; and a utility index, which...