arXiv subjects

John Horton

Publications and source records attributed to John Horton.

5 recordsLinked to original sources

arXiv2025

Strategic Tradeoffs Between Humans and AI in Multi-Agent Bargaining

Markets increasingly accommodate large language models (LLMs) as autonomous decision-making agents. As this transition occurs, it becomes critical to evaluate how these agents behave relative to their human and task-specific statistical predecessors. In this work, we present results from an empirical study comparing humans (N=216), multiple frontier LLMs, and customized Bayesian agents in dynamic multi-player bargaining games under identical conditions. Bayesian agents extract the highest surplus with aggressive trade proposals that are frequently rejected. Humans and LLMs achieve comparable aggregate surplus within their groups, but exhibit different trading strategies. LLMs favor conservative, concessionary proposals that are usually accepted by other LLMs, while humans propose trades that are consistent with fairness norms but are more likely to be rejected. These findings highlight that performance parity -- a common benchmark in agent evaluation -- can mask substantive procedural differences in how LLMs behave in complex multi-agent interactions.

cs.AI↗

arXiv2021

The Ruble Collapse in an Online Marketplace: Some Lessons for Market Designers

The sharp devaluation of the ruble in 2014 increased the real returns to Russians from working in a global online labor marketplace, as con- tracts in this market are dollar-denominated. Russians clearly noticed the opportunity, with Russian hours-worked increasing substantially, primarily on the extensive margin -- incumbent Russians already active were fairly inelastic. Contrary to the predictions of bargaining models, there was little to no pass-through of the ruble price changes in to wages. There was also no evidence of a demand-side response, with buyers not posting more "Russian friendly" jobs, suggesting limited cross-side externalities. The key findings -- a high extensive margin elasticity but low intensive margin elasticity; little pass-through into wages; and little evidence of a cross-side externality -- have implications for market designers with respect to pricing and supply acquisition.

econ.GN↗

arXiv2021

The Production and Consumption of Social Media

We model social media as collections of users producing and consuming content. Users value consuming content, but doing so uses up their scarce attention, and hence they prefer content produced by more able users. Users also value receiving attention, creating the incentive to attract an audience by producing valuable content, but also through attention bartering -- users agree to become each others' audience. Attention bartering can profoundly affect 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.

econ.GN↗

arXiv2010

The Condition of the Turking Class: Are Online Employers Fair and Honest?

Online labor markets give people in poor countries direct access to buyers in rich countries. Economic theory and empirical evidence strongly suggest that this kind of access improves human welfare. However, critics claim that abuses are endemic in these markets and that employers exploit unprotected, vulnerable workers. I investigate part of this claim using a randomized, paired survey in which I ask workers in an online labor market (Amazon Mechanical Turk) how they perceive online employers and employers in their host country in terms of honesty and fairness. I find that, on average, workers perceive the collection of online employers as slightly fairer and more honest than offline employers, though the effect is not significant. Views are more polarized in the online employer case, with more respondents having very positive views of the online collection of employers.

cs.CY↗

arXiv2010

The Labor Economics of Paid Crowdsourcing

Crowdsourcing is a form of "peer production" in which work traditionally performed by an employee is outsourced to an "undefined, generally large group of people in the form of an open call." We present a model of workers supplying labor to paid crowdsourcing projects. We also introduce a novel method for estimating a worker's reservation wage--the smallest wage a worker is willing to accept for a task and the key parameter in our labor supply model. It shows that the reservation wages of a sample of workers from Amazon's Mechanical Turk (AMT) are approximately log normally distributed, with a median wage of $1.38/hour. At the median wage, the point elasticity of extensive labor supply is 0.43. We discuss how to use our calibrated model to make predictions in applied work. Two experimental tests of the model show that many workers respond rationally to offered incentives. However, a non-trivial fraction of subjects appear to set earnings targets. These "target earners" consider not just the offered wage--which is what the rational model predicts--but also their proximity to earnings goals. Interestingly, a number of workers clearly prefer earning total amounts evenly divisible by 5, presumably because these amounts make good targets.

cs.HC↗