We study how job-seekers share information about jobs within their social network, and its implications for firms. We randomly increase the amount of competition for a job and find that job-seekers are: (i) less likely to share information about the job with their peers; and (ii) choose to...

As technology platforms have created new markets and new ways of acquiring information, economists have come to play an increasingly central role in tech companies - tackling problems such as platform design, strategy, pricing, and policy. Over the past five years, hundreds of PhD economists...

Trust is vital for market development, but how can trust be enhanced in a marketplace? A common view is that more trusting may help to build trust, especially in less developed economies. In this paper, we argue that more trusting may lead to less trust. We set up a rational expectation model in...

Data on sales of memory modules are used to explore several aspects of e-retail demand. There is a strong relationship between e-retail sales to a given state and sales tax rates that apply to purchases from online retailers. This suggests that there is substantial substitution between online...

Search frictions can explain why the "law of one price" fails in retail markets and why even firms selling commodity products have pricing power. In online commerce, physical search costs are low, yet price dispersion is common. We use browsing data from eBay to estimate a model of consumer...

Despite substantial efforts to help consumers search in more intuitive ways, text search remains the predominant tool for product discovery online. In this paper, we explore the effects of visual and textual cues for search refinement on consumer search and purchasing behavior. We collaborate...

We build a model of online behavioral manipulation driven by AI advances. A platform dynamically offers one of n products to a user who slowly learns product quality. User learning depends on a product's "glossiness,' which captures attributes that make products appear more attractive than they...

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...