We study the estimation of preference heterogeneity in markets where consumers engage in costly search to learn product characteristics. Costly search amplifies the way consumer preferences translate into purchase probabilities, generating a seemingly large degree of preference heterogeneity. We...

Traditional methods for estimating demand are not always well-suited to online markets, where individual products are sold infrequently, unobserved factors such as webpage layout drive substitution, and often only a limited set of product characteristics is observed. We propose a demand model...

We analyze the impact of a tax on sweetened beverages using a unique dataset of prices, quantities sold, and nutritional information across several thousand taxed and untaxed beverages for a large set of stores in Philadelphia and its surrounding area. We find the tax is passed through at an...

We assemble a unique data set that combines information on supermarket feature advertising with path-tracking data on consumers' movement within the store as well as purchase information. Using these novel data, we trace out how advertising affects consumer behavior along the path-to-purchase....

In many competitive settings consumers buy multiple product categories, and some prefer to use a single firm, generating complementary cross-category price effects. To study pricing in supermarkets, an organizational form where these effects are internalized, we develop a multi-category...

We leverage a temporary block of the Chinese microblogging platform Sina Weibo due to political events, to estimate the causal effect of online word-of-mouth content on product demand in the context of TV show viewership. Based on this source of exogenous variation, we estimate an elasticity of...