Charles Pébereau

Research

(Mis)Perceptions of the Labor Market (pdf) - with Pierre Deschamps, Morgane Hoffmann, Morgane Laouénan, and Louis-Pierre Lepage
Presented at the NBER Conference, 2026

Abstract: Workers and firms make costly decisions based on what they think is valued in the labor market. We study whether employers and workers hold accurate perceptions about the preferences of others through a series of incentivized field experiments on one of Europe’s largest freelance platform. First, we elicit employer and worker preferences over a rich set of worker, employer, and job characteristics using randomized worker profile and job offer evaluations. Second, we elicit beliefs about these preferences, from the other side of the market as well as from competitors, and we test their accuracy. We document substantial perception gaps about labor market preferences on both sides of the market, including about the value of posted wages, human capital, market reputation, job amenities like remote work, and demographic characteristics. Third, we implement a personalized information treatment to correct these gaps and show that it changes participants’ market behavior. To help interpret our results, we develop a theoretical framework showing how the perception gaps we document can distort both pricing and investment decisions. Consistent with the model, we find that workers and firms with larger perception gaps have worse market outcomes. Our findings highlight an important source of information frictions in labor markets and their economic consequences.

None of your business! Efficient disclosure policies with heterogeneous audiences (pdf)

Abstract: This paper studies the efficient disclosure of performance information about an agent with career concerns to heterogeneous future employers. A principal trades off effort incentives against the agent’s welfare. Although employers’ profits are not internalized, efficient disclosure uses employer-specific cutoffs on past performance. Raising a cutoff strengthens incentives but reduces welfare. Cutoffs differ because employers for whom past performance is less relevant are harder to persuade, narrowing the set satisfying their obedience. The model informs debates on regulating access to personal records: uniform public disclosure is generally inefficient, and reputational incentives should be targeted where information is most relevant.

Evaluating LLM Behavior in Hiring: Implicit Weights, Fairness Across Groups, and Alignment with Human Preferences (pdf) - with Morgane Hoffmann, Emma Jouffroy, Warren Jouanneau, Marc Palyart
Published in RecSys (2025)

Abstract: General-purpose Large Language Models (LLMs) show significant potential in recruitment applications, where decisions require reasoning over unstructured text, balancing multiple criteria, and inferring fit and competence from indirect productivity signals. Yet, it is still uncertain how LLMs assign importance to each attribute and whether such assignments are in line with economic principles, recruiter preferences or broader societal norms. We propose a framework to evaluate an LLM’s decision logic in recruitment, by drawing on established economic methodologies for analyzing human hiring behavior. We build synthetic datasets from real freelancer profiles and project descriptions from a major European online freelance marketplace and apply a full factorial design to estimate how a LLM weighs different match-relevant criteria when evaluating freelancer-project fit. We identify which attributes the LLM prioritizes and analyze how these weights vary across project contexts and demographic subgroups. Finally, we explain how a comparable experimental setup could be implemented with human recruiters to assess alignment between model and human decisions. Our findings reveal that the LLM weighs core productivity signals, such as skills and experience, but interprets certain features beyond their explicit matching value. While showing minimal average discrimination against minority groups, intersectional effects reveal that productivity signals carry different weights between demographic groups.

Barriers to real-time electricity pricing: Evidence from New Zealand  (pdf) - with  Kevin Remmy 

International Journal of Industrial Organization 2023, 89, 102979

Abstract: This paper studies the introduction of real-time electricity pricing in the New Zealand residential retail market to understand why its market share remained below 1.25%. We use rich panel data of all retail switches between 2014 and 2018 and an unexpected wholesale price spike to study adoption and attrition. Exploiting the staggered roll-out of real-time pricing in different locations we find that attrition decreases with experience. We also find that prospective adopters are present biased. The combination of these findings explains why adoption stalled and shows that wholesale price spikes pose a serious threat to widespread adoption of real-time pricing.