Working Papers

La Cordata: Loyalty in Political Tournaments  

Wouter Dessein  and Luis Garicano (July 2025).  

Abstract:

We study the allocation of talent in tournaments between (political) teams. The winner-take-all nature of these contests implies that talented members may quit if the odds of winning diminish. A leader must choose between competent individuals who increase the chances of winning but may bolt at the first hint of bad news, and loyalists who have fewer outside options. The value of loyalty increases when outside options are more valuable, pre-election information (polls, primaries) is more predictive, or elections are more competitive. We discuss organizational responses, such as ideological platforms, and the role of leader loyalty in improving talent allocation.

Training in the Age of AI: A Theory of Apprenticeship Viability.  

Luis Garicano  and Luis Rayo (September 2025).  

Abstract:

Apprenticeships let juniors pay for training by doing menial work. AI now performs an increasing share of that work, putting the bargain at risk. We introduce AI into a dynamic apprenticeship model with an automation threshold and possible complementarity for experts. A single statistic—the expertise leverage ratio, measuring the AI-augmented value of a graduate relative to AI’s standalone output—governs the impact of AI. Our central result is that apprenticeships are guaranteed viable, in the sense that they are at least as profitable as they were before the arrival of AI, when this ratio is above a critical threshold, specifically Euler’s number e; in this case, training has a fixed duration and the apprenticeship is not at risk. Below the threshold, training compresses as the master’s saleable knowledge shrinks; in this case, advances in AI threaten wholesale apprenticeship collapse.

The Economics of Superabundant AI: Autonomy, Scarcity and the Future of Work

(October 2025)

Abstract

This paper is forthcoming as a chapter for an NBER volume a paper on Economics of Transformative AI, edited by Ajay K. Agrawal, Anton Korinek and Erik Brynjolfsson and published by University of Chicago Press. It analyzes how "superabundant" AI can simultaneously augment and displace workers. The outcome depends on what remains scarce. When compute is scarce, or the AI is non Autonomous, AI is a "co-pilot," and human time retains value. If compute is abundant and AI is autonomous, "opportunities" or "slots" become the bottleneck, displacing low-skill humans. If compute is abundant but AI is non-autonomous, human input is the bottleneck, and all humans work, but wages compress.  Hence the paper argues displacement is avoidable. If firms can create new "addressable opportunities" at a cost lower than the value AI provides, they will. This keeps compute scarce and sustains human employment.

Narrative Entanglement in Climate Policy. 

Adam Brzezinski and Luis Garicano (November 2025).  

Abstract:

Political narratives on climate policy have turned more skeptical despite evidence of climate urgency. We explain this shift with a theory of narrative entanglement: to appeal to voters, politicians intertwine economic and environmental narratives rather than treating them separately. Hence, shocks unrelated to climate change can impact environmental narratives. We test our theory in the context of Russia’s invasion of Ukraine, which affected the economic costs of the European Green Deal without changing its impact on emissions. We use large language models to identify climate narratives across all speeches in the 9th European Parliament (2019-2024).  Exploiting only variation within each parliamentarian, we show that after the invasion, narratives become both more negative in the cost assessments of climate policies and more skeptical about their environmental impact

Trust as a Scaling Strategy: How Internal Entrepreneurs Drive Corporate AI Adoption

with Elena Alfaro, Antonio Cabrales, José Elías Durán Roa, Luis Garicano, Isabel Pérez del Caño, Toni Roldán Monés, Guillermo Vieira de Santiago.  (November 2025)

(Note: This is not a traditional research paper, but a practitioner oriented case study-based analysis). 

Abstract

We argue most corporate GenAI programs disappoint. Since value is generated to a large extent from the bottom‑up it is a good idea to use your employees’ technical and entrepreneurial talent. The job is to achieve this in a safe, visible, and scalable manner—fast—then build the organization around it. BBVA’s human-centered, bottom-up strategy demonstrates how to do that effectively at scale, in a heavily regulated industry.