In many markets, advance contracts allow one party to renege against a penalty, granting them the option to keep searching for alternatives and reducing their opportunity cost of contracting early. This paper studies the optimal design and welfare implications of such arrangements in the trucking industry, leveraging novel data from a brokerage firm. Through a digital auction platform, the firm lets freight carriers bid their asking price on shipments directly and penalizes cancellations lightly through a reputational mechanism. To evaluate alternative penalty designs, this paper develops and estimates a dynamic structural model of the carriers' job-finding problem, linking their search and bidding behavior to the firm's cancellation policy. Counterfactual simulations of the model suggest that increasing the cancellation penalty reduces both firm profits and overall welfare, as the burden of reduced flexibility is shifted to the brokerage through increased bids and fewer total matches. The paper also explores a switch to pecuniary penalties—common in the travel industry—which provide the brokerage with an additional revenue stream. Results show that while these can boost firm profits, they do so at the cost of lower overall welfare.

Sophisticated pricing algorithms used by digital transportation platforms have renewed interest in price control policies, but little evidence exists on their redistributive effects. This paper studies a uniform price mandate in the market for shared electric vehicle platforms in Washington, D.C., which prohibits origin- and destination-based pricing. To compute price equilibria encompassing hundreds of prices for specific origin-destination pairs, I develop a new simulation-based pricing algorithm, adapted from the reinforcement learning literature. I apply the algorithm to a demand system estimated using geolocation data from all firms in the market. In the counterfactual exercise, I find that the redistributive effects of the price controls are mild, and mainly serve riders in the periphery of the city. Furthermore, I find that relaxing the price controls increases rides taken by consumers by 41%, firm profits by 34%, and increases consumer welfare by more than double the profit increase (80% of firm profits).

As the gig economy grows, an increasing number of individuals are relying on content creation for their livelihood. The design of platform recommendation algorithms plays a critical role in the discovery and success of new creators. This study presents novel evidence from a natural experiment on the Twitch livestreaming platform to quantify this entry barrier. We analyze eight weeks of high-frequency viewership panel data for all World of Warcraft streams, focusing on the period surrounding the launch of a new game expansion that substantially increased both viewership and the number of streamers. Our findings highlight the significant role of viewer favorites, with the median viewer dedicating 60% of their time to a single streamer pre-launch and 48% post-launch. We also observe considerable stickiness in these preferences; fresh viewers in the post-launch period are twice as likely to watch fresh streamers compared to those active pre-launch. These patterns have important implications for the entry of new streamers and inform the design of recommendation algorithms. Future work aims to develop a theoretical model to understand the impact of these dynamics on the equilibrium distribution of viewership across streamers.

We utilize data from 5,010 soccer games in the top two Swiss divisions between the 2005/06 and 2018/19 seasons. In these games, a referee can share the same linguistic area with one of the teams. Using referee-per-season fixed effects, we find that referees issue significantly more penalties, in the form of yellow cards, to teams that are not from the referee's linguistic area. We also find some evidence, in the highest level league only, that referees issue more red cards to teams that are not from their linguistic area and that away teams achieve fewer points when home teams share the same linguistic area with the referee. Our analyses suggest that referees' bias is likely to be subconscious and reflexive rather than being a deliberate act of discrimination.