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...

A building block of many models in empirical industrial organization is a characteristic space, where products are modeled as a bundle of characteristics over which consumers have preferences. The ability of such models to predict counterfactual outcomes depends on how well this characteristic...

A concern central to the economics of privacy is that firms may use consumer data to price discriminate. A common response is that consumers should have control over their data and the ability to choose how firms access it. Since firms draw inferences based on both the data seen as well as the...

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...