Large language models---because of how they are trained and designed---are implicit computational models of humans---a homo silicus. Social scientists can use LLMs like economists use homo economicus: LLMs can be given endowments, information, preferences, and so on, and then their behavior can be explored in scenarios via simulation. We replicate four experiments using this approach and find qualitatively similar results to the original. Benefits of this approach include trying new variations for fresh insights, piloting studies via simulation, and searching for novel social science insights to test in the real world. The full version of the paper can be accessed at https://apostolos-filippas.com/papers/hs.pdf.

Buyers pursuing unavailable sellers is a common source of inefficiency in matching markets. We report the results of a field experiment in a large online marketplace where sellers could pay to signal higher capacity via a badge that simply said "available now." All sellers could rent this signal but only randomly treated buyers could see it. We find that sellers who rented this signal were positively selected, treated buyers sought them out more, and as a result matching efficiency increased. We discuss why costly signaling is necessary to facilitate this coordination, and show that mere statements about seller capacity had become uninformative in this marketplace. Two years after the experiment, we show that sellers renting this signal continue receiving substantially higher buyer attention. The full version of the paper can be accessed at https://apostolos-filippas.com/papers/costly-capacity-signalling.pdf.

We study the introduction of advertising in an online labor market where applicants could bid to "boost" their applications. Applicants with the highest bids received a prominent position at the top of the employer's application list. The platform randomly varied whether the employer was exposed to boosted applications, and within the exposure group, whether the employer was shown a disclosure that the application was boosted. We find that boosted applications are positively selected, and that boosting an application increases the likelihood of an applicant being hired by about 40%. The experimental design allows us to estimate that about 80% of this increase was due to the ranking effect---boosted applications ranking higher---and 20.2% was due to the signaling effect---the disclosure that the application is boosted. The full version of the paper can be accessed at https://apostolos-filippas.com/papers/boosted.pdf.

We model social media as collections of users producing and consuming content. Users value consuming content but due to scarce attention they may not value all content from other users. Users also value receiving attention, creating the incentive to attract an audience by producing valuable content but also through attention bartering—users mutually becoming each others’ audience. Attention bartering shapes substantially the patterns of production and consumption on social media, explains key features of social media behavior and platform decision-making, and yields sharp predictions that are consistent with data we collect from #EconTwitter. We conduct Twitter and Instagram user surveys that yield additional direct evidence in support of attention bartering, and we discuss the implications of attention bartering for the design of social media platforms.

A solution to marketplace information asymmetries is to have trading partners publicly rate each other post-transaction. Many have shown these ratings are effective; we show that their effectiveness deteriorates over time. The problem is that ratings are prone to inflation, with raters feeling pressure to leave "above average" ratings, which in turn pushes the average higher. This pressure stems from raters' desire to not harm the rated seller. As the potential to harm is what makes ratings effective, reputation systems, as currently designed, sow the seeds of their own irrelevance.

Peer-to-peer rental markets for short-term accommodation enable "hosts" to rent out properties to "guests." A common critique of such markets is that hosts benefit at the expense of their unwitting neighbors on whom they impose costs, potentially creating a market failure that justifies policy intervention. In this paper we examine four policy regimes that differ in the allocation of the decision right to become a host. We consider the market outcomes when hosting decisions are made by (1) individual tenants that maximize their revenue, (2) building owners that consider only rents from long-term rentals, (3) cities that consider the surplus of all city residents, and (4) a social planner that takes into account the surplus of both city residents and guests. We find that the equilibrium where tenants are allowed to individually decide has too much hosting, whereas city-specific policies result in too little hosting. The efficient social planner's solution is equivalent to the equilibrium where building owners decide. We conclude with a discussion of our results and lay out directions for future research.