Research

This article evaluates caps on the commissions that food delivery platforms charge to restaurants. Caps may lead platforms to raise their consumer fees, thereby reducing ordering and consequently platforms’ value to restaurants. Equilibrium restaurant responses to caps, though, may counteract fee hikes—commission caps may boost restaurant uptake of platforms and reduce restaurant prices on platforms, thereby benefitting consumers. The net welfare effects of caps are thus uncertain. To quantify theseeffects, I estimate a model of pricing and platform adoption in a multi-sided market using data on consumer restaurant orders, restaurants’ platform adoption, and platform fees. Counterfactual simulations imply that commission caps reduce overall welfare, bolstering restaurant profits at the expense of platforms and especially consumers.

This article develops techniques for the empirical analysis of repeated sequential search over unordered alternatives using data on consumer search processes. I use these techniques to assess why consumers conduct little search in e-commerce and often pay significantly above the minimum available price for a product. Search costs could explain these facts, as could pre-search seller differentiation: consumers with low search costs may not visit stores they dislike based on information known before search. I find that seller differentiation is primarily responsible for limited consideration and market power.

We estimate the effects of offline stores on online spending using data on US store locations and on internet browsing and transactions. The direct effect of a multi-channel retailer’s offline stores on its online sales depends on two opposing forces: (i) a negative cannibalization effect and (ii) a positive cross-channel complementarity, which may reflect offline customer service for items purchased online or brand awareness effects of offline stores. The direct effects of an offline store on rival retailers’ online sales similarly depend on (i) a negative business-stealing effect and (ii) a positive showrooming effect, which arises when offline stores bolster consumer interest in a product category. Our empirical approach captures consumer heterogeneity through variables characterizing the categories of websites that consumers visit, which proxy for unobserved tastes, as well as the demographic profiles of consumers' neighbourhoods. Our estimates for 2007–2008 imply that a multichannel retailer's online sales fall by 1.1–3.8% on average when a rival adds an offline store. These sales increase by 7.1–32.3% when the retailer adds an offline store of its own, suggesting that cross-channel complementarities exceed cannibalization effects. Additionally, our estimated effects of offline stores on rivals' online sales vary across retailers and categories. Notably, offline stores often boost Amazon's sales, suggesting the relevance of showrooming effects.

This paper characterizes the identifiability of demand models with network externalities. Guided by my identification analysis, I empirically evaluate how network externalities shape the welfare effects of consolidation in the US dating websites industry. Network externalities often arise in differentiated products markets, and especially in platform markets. I show that demand models with network externalities are generally not identified with market-level data alone. This result reflects the impossibility of independently varying product characteristics and market shares at the market level. However, an extension of results in Berry and Haile (2022) establishes that demand models with network externalities are identified under reasonable conditions with microdata linking consumers' decisions and characteristics. I estimate demand for dating websites using online browsing microdata. Under my preferred estimates, a user of a site values a 10% increase in the site's usership at $6.34/month. I find that welfare losses from increased prices outweigh the gains from network externalities associated with monopolization. Additionally, I find that—due to platform differentiation—a firm earns higher profits from joint ownership of the two largest dating websites when it does not integrate these sites.