Benjamin Shiller

Emerging tracking data enable precise predictions of individuals' reservation values. However, firms may be reluctant to overtly adopt personalized pricing. This paper proposes a strategy that embeds personalization within a dynamic pricing framework, tailoring prices privately while committing to infrequent adjustments to obscure its use. Simulation analyses based on both theoretical and empirically estimated distributions of consumer valuations reveal that profits rise most when consumer arrivals are moderately frequent. Increasing the precision of individual‐level demand estimates broadens the range of products for which this strategy is profitable. These findings suggest the approach may be an auspicious strategy for online platforms.

Since its founding, Amazon has established a reputation for being consumer friendly by consistently offering lower prices than its market position would seem to allow. However, recent antitrust concerns about dominant online platforms have revived questions about whether Amazon’s growing market share threatens consumer welfare. Given its reputation, regulators have proposed a new focus on conduct unrelated to prices. We ask whether such a move is premature. Using the sudden and unanticipated US exit of Toys“R”Us as a natural experiment, we find that Amazon’s toy prices on its US site increased by almost 5 percent in the wake of the exit relative to similar products and to toys on its Canadian site. Thus, despite Amazon’s long-standing reputation, it may exploit increases in market power in traditional ways as competing retailers cease operating.

A consumer's web‐browsing history, now readily available, may be much more useful than demographics for both targeting advertisements and personalizing prices. Using a method that combines economic modeling and machine learning methods, I find a striking difference. Personalizing prices based on web‐browsing histories increases profits by 12.99%. Using demographics alone to personalize prices raises profits by only 0.25%, suggesting the percent profit gain from personalized pricing has increased 50‐fold. I then investigate whether regulations intended to prevent price gouging increase aggregate consumer surplus. Two feasible regulations considered offer at best modest improvements.

Recent technological innovations allow insurance providers to closely monitor and collect detailed data on their customers’ behaviors. Such innovations offer potential benefits by mitigating moral-hazard problems but may provide the incumbent with a lasting first-mover advantage, which may harm consumers. We investigate these outcomes in the context of pay-how-you-drive (PHYD) auto insurance, which offers tailored discounts to drivers monitored by telematics devices. We exploit the staggered entry of PHYD insurance across states and insurers in a difference-in-differences framework. While innovating firms experience initial profit increases, the profits are eroded by entry, which suggests that this innovation does not raise novel antitrust concerns. Furthermore, we find a meaningful impact of PHYD programs on fatal car accidents. Our findings are consistent with impacts implied by canonical theoretical models.

Ad blocking software allows Internet users to obtain information without generating ad revenue for site owners, potentially undermining investments in content. We explore the impact of site‐level ad blocker usage on website quality, as inferred from traffic. We find that each additional percentage point of site visitors blocking ads reduces its traffic by 0.67% over 35 months. Impacted sites provide less content over time, providing corroboration for the mechanism. Effects on revenue are compounded; ad blocking reduces visits, and remaining visitors blocking ads do not generate revenue. We conclude that ad blocking poses a threat to the ad‐supported web.

An existing theoretical literature finds that frictionless resale markets cannot reduce profits of monopolist producers of perfectly durable goods. This paper starts by presenting logical arguments suggesting this finding does not hold for goods consumers tire of with use, implying the impact of resale is an empirical question. The empirical impact is then estimated in the market for video games, one of many markets in which producers may soon legally prevent resale by distributing their products digitally as downloads or streamed rentals. Estimation proceeds in two steps. First, demand parameters are estimated using a dynamic discrete choice model in a market with allowed resale, using data on new sales and used trade-ins. Then, using these parameter estimates, prices, profits, and consumer welfare are simulated under counterfactual environments. When resale is allowed, firms are unable to prevent their goods from selling for low prices in later periods. The ability to do so by restricting resale outright yields significant profit increases. Renting, however, does not raise profits as much due to a revenue extraction problem.

With digital music as its context, this paper quantifies how much money would be made using alternatives to uniform pricing. Using survey-based data on nearly 1,000 students' valuations of 100 popular songs in early 2008 and early 2009, we find that various alternatives can raise both producer and consumer surplus. Digital music revenue could be raised by between a sixth and a third relative to profit-maximizing uniform pricing. While person-specific uniform pricing can raise revenue by over 50 per cent, none of the non-discriminatory schemes raise revenue's share of surplus above 40 per cent of total surplus.