@techreport{a808b376b6ae4b5f8a3557fe320619eb,
title = "Labor Market Signals: The Role of Large Language Models",
abstract = "Large Language Models (LLMs) have the potential to transform the labor market, including hiring. This paper assesses their impact on signals that job-seekers send to potential employers and how this affects labor market matching. Through two field experiments, focusing on cover letters and involving job-seekers and recruiters, we document that LLMs enhance the quality of signals, particularly benefiting lower-quality applicants. However, these improvements do not translate into increased interview invitations because the improvements are concentrated in standardized, less influential sections of the cover letters. When recruiters are explicitly informed of candidates{\textquoteright} use of LLMs, they place greater value on high-quality cover letters crafted without AI assistance. Our findings indicate that LLMs reduce the informativeness of signals, potentially leading to increased inefficiencies in labor market matching.",
keywords = "large language models, cover letters, labor market, matching, signaling",
author = "{Abbas Nejad}, Kian and Giuseppe Musillo and Till Wicker and Niccol{\`o} Zaccaria",
note = "CentER Discussion Paper Nr. 2025-003",
year = "2025",
month = mar,
day = "18",
language = "English",
volume = "2025-003",
series = "CentER Discussion Paper",
publisher = "CentER, Center for Economic Research",
pages = "1--89",
type = "WorkingPaper",
institution = "CentER, Center for Economic Research",
}