We examine the profitability of personalized pricing policies that are derived using different specifications of demand in a typical retail setting with consumer-level panel data. We generate pricing policies from a variety of models, including Bayesian hierarchical choice models, regularized...

Rapid growth in e-commerce has altered the ability of jurisdictions to enforce commodity taxes on a destination basis. This results in different effective tax rates depending on the way in which goods and services are purchased and the characteristics of both the products and the sellers. We...

If online transactions are tax-free, increased online shopping may lower tax rates as jurisdictions seek to reduce tax avoidance; but, if online firms remit taxes, online sales may put upward pressure on tax rates because internet sales help enforce destination-based taxes. I find that higher...

We develop a model of strategic geoblocking, where two competing multi-channel retailers, located in different countries, can decide to block access to their online store from foreign consumers. We characterize the equilibrium when firms decide unilaterally whether to introduce geoblocking...

Technological innovations facilitating e-commerce have well-documented effects on consumer behavior and firm organization in the retail sector, but the effects of these new transaction technologies on fiscal systems remain unknown. By extending models of commodity tax competition to include...

What is the effect of e-commerce on the geographic distribution of local sales tax revenues? Using COVID-19 as a shock to online shopping and hand-collected high-frequency data on local sales tax revenue, we document an important shift in the state and local public finance landscape. As...

Requiring firms, rather than individuals, to remit sales taxes improves tax compliance. In the U.S., this shift toward firm-based remittance rules for remote purchases occurred gradually after South Dakota v. Wayfair. Using comprehensive and high-frequency local sales tax revenue data, we show...

We study competition among a score of firms participating in an online market for a commodity computer component. Firms were able to adjust prices continuously; prices determined how the firms were ranked and listed (lowest price listed first), with better ranks contributing to firms' sales....

Online ratings play an important role in many markets. We study the often disputed information content of these ratings, by proposing a reduced-form Bayesian model of the typical buyer's rating decision. Our empirical evidence based on eBay raw data is in line with even intricate predictions...

Online ratings play an important role in many markets. However, how fast they can reveal seller types remains unclear. To study this question, we propose a new model in which a buyer learns about the seller’s type from previous ratings and her own experience and rates the seller if she learns...