Luis Menéndez
I am a Ph.D. candidate in Economics at Universitat Autònoma de Barcelona, the Barcelona School of Economics, and the IDEA Graduate Program.
My main research interests are Political Economics and Media Economics. I apply machine learning and text processing techniques combined with structural econometric methods to understand topics such as online coordination for offline protest participation, linguistic echo-chambers, and polarization in the demand for political content. I am on the 2025-26 Job Market.
You can check out my CV here.
Email: luisigmenendez@gmail.com
RESEARCH
Job Market Paper
"The Impact of Political Campaigns on Demand for Partisan News"
Abstract
I explore how electoral campaigns affect the market for partisan news. I use machine learning and large language models (LLMs) to build a novel slant index that I match to high-frequency audience-meter data on television consumption. This allows me to compare how the same story has been framed across different outlets with the number of viewers. I integrate these measures into a structural model of news demand and supply. Viewers choose their preferred information source based on how coverage is framed, which is chosen by the outlets in equilibrium. To identify viewers’ preferences for political content, I exploit exogenous variation in the composition of political events that constrains what outlets can cover. Demand for news becomes significantly more polarized during the election campaign period, with viewers exhibiting stronger negative responses to coverage favorable to the party they oppose. On the supply side, outlets face lower costs of producing slanted coverage that aligns with their political stance. I then evaluate rules requiring newscasts to allocate airtime to parties in proportion to their previous election results. Outlets comply by becoming more partisan, resulting in a more polarized media environment.
Other Works
"Breaking the Echo Chamber: Nonviolent Protest and Police Violence on Twitter"
--(submitted)--with Hannes Mueller, Daniel Montolio, and Francesco Slataper.
Abstract
This article exploits data from a political conflict between language groups to show how political events can rapidly redefine how these groups interact on social media. Leveraging on a unique dataset of 26 million retweets by 120 000 Catalan- and Spanish-speaking Twitter users, we estimate individual exposure to tweets with a network-based model. We then compare two shocks in the same region and year: the Barcelona terror attack and the Catalan independence referendum. The referendum — and the circulated images of police violence — triggered a sharp, symmetric jump in cross-language retweeting. The terror attack, by contrast, did not lead to a similar realignment.
"Online and Offline protest participation: An Empirical Analysis for the 2020 Black Lives Matter Movement"
Abstract
The recent wave of world-wide protests that took place after George Floyd’s killing has sparked attention in the Black Lives Matter movement, specially in terms of online activism. How does offline protesting behavior interact with the underlying online social networks? In this work, I build a classification algorithm to identify individuals who physically participated in the BLM demonstrations across the US. Thanks to this unique dataset, I explore at an individual level their full Twitter activity to better understand the role of influential users, coordination patterns and speech evolution. Through this analysis, I aim to examine assumptions regarding slacktivism, which involves engaging in online activism with minimal effort, in comparison to more traditional forms of protesting. By exploring how social media contributes to the development of traditional activism, we can gain a deeper understanding of the role of social media in protesting behavior.
"Media Entry and Political Slant"
with Manuel Lleonart.
Abstract
This paper investigates how competition shapes ideological slant in television news. While theoretical models suggest that increased media competition can either intensify or mitigate bias—depending on whether audiences seek confirmation or accuracy—empirical evidence remains limited. We address this gap by analyzing the entry of a new Spanish TV news outlet and measuring how it alters the political slant of existing providers. Our approach combines a formal model of political media markets with a novel empirical strategy that leverages large-language-model and text-analysis techniques. We disentangle media bias into topic selection, ideological tone, and airtime allocation—capturing the three primary channels through which slant manifests. Our findings offer the first direct evidence of how heightened rivalry influences not just audience composition, but the strategic editorial decisions that shape political coverage.
"The End of the Iberian Exception: Populists and
the Economy"
with Agustina Martínez and Henry Redondo.
PROJECTS
Spanish Media Monitor
Spanish Media Monitor is the first effort to monitor TV media using large language models (LLMs). I built this project to provide real-time analysis of Spanish television news content, leveraging LLMs for story identification, classification, and visualization. You can visit the webpage here.
TEACHING
Instructor:
Teaching Assistant:
Course evaluations available upon request.
