Hi!
I am a theorist studying how firms and other organizations respond to environments where behavioral biases, non-standard preferences, or informational frictions are prevalent.
I am currently an Adjunct Professor in the Managerial Economics and Decision Sciences department at the Kellogg School of Management.
My email is andres.espitia@kellogg.northwestern.edu.
I am on the job market.
When to Request Evidence? (with E. Muñoz-Rodríguez) New version! (December 2025)
Appropriate decisions depend on information gathered beforehand, yet such information is often obtained through intermediaries with biased preferences. We study the problem faced by a decision-maker who can only access information through an agent with misaligned preferences. In a dynamic framework with exogenous decision timing, we ask how requests for verifiable information (evidence) should be scheduled and their implications for the quality of implemented choices. When the agent's incentives are ignored, evidence requests do not condition on previously reported information. However, such policies are susceptible to strategic manipulation by the agent. We show that, in these cases, optimal requests should be biased: additional evidence is more likely to be sought when previous reports favor the agent’s preferred outcome. The primary application is the design of optimal testing schedules for patients awaiting transplants.
Confidence and Organizations [Video]
Miscalibrated beliefs generally compromise the quality of workers' decisions. Why might a firm prefer to hire an individual known to be overconfident? In this paper, I explore the role of such biases when members of the organization disagree about the right course of action. I present a model in which an agent uses his private information to make a choice on behalf of a principal. In this setting, I consider what I call the belief design problem: how would the principal like the agent to interpret his observations? I provide conditions under which the solution indicates a preference for a well-calibrated, an underconfident, or an overconfident agent. A well-calibrated agent is preferred if and only if his information does not affect the expected difference in the players' preferred actions. Overconfidence is optimal when the principal seeks to adjust actions beyond what a well-calibrated agent would do.
Robust Contracts under Social Preferences
A principal faces several moral hazard problems under multitasking, one with each of several agents. While these problems are independent, the principal is concerned that agents may also intrinsically care about their peers' payoffs. For example, agents may have status concerns and evaluate wages according to their ranking in the group. Alternatively, agents may be averse to ex-post inequality. The exact shape of the agents' preferences, however, is not fully known by the principal; she only knows that they belong to some specific class. This project explores the type of contracts that perform robustly well from the principal's perspective. Contracts that combine individual and group incentives can perform well by leveraging agents' choices across tasks to gather information about their true preferences.
The (Early) Winner Takes It All: The Matthew Effect in Creative Careers
The highly skewed distribution of output is a pervasive regularity across creative environments, including science, art, journalism, and entertainment. Moreover, output inequality within these domains tends to intensify over the course of creators’ careers. For instance, within a given cohort of scientists, inequality in publication output increases over the life cycle. This paper studies whether the consumption process of creative content can, by itself, generate such dynamic patterns of inequality. I show that when audiences instrumentally rely on authors’ reputations (endogenously determined by past output) to guide their consumption choices, dynamic competition among creators collapses into a winner-takes-all outcome. This mechanism gives rise to a Matthew effect, even in the absence of ex ante heterogeneity.
Business Analytics II (MBA) - Lecturer
Topics in Microeconomic Theory (M.Sc.) - Lecturer
Behavioral Economics (M.Sc.) - Lecturer
Business Analytics I, II (MBA) - Teaching Assistant
Public Economics (MBA) - Teaching Assistant
Ethics and Leadership (MBA/Executive MBA) - Teaching Assistant
Microeconomics I (B.Sc.) - Lecturer
Mathematical Economics (B.Sc.) - Lecturer
Mathematical Economics (M.Sc./Ph.D.) - Teaching Assistant
Ph.D., Managerial Economics & Strategy - Kellogg School of Management - Northwestern University (Evanston - USA, 2022)
Chairs: David Besanko and Luis Rayo
M.Sc., Managerial Economics & Strategy - Kellogg School of Management - Northwestern University (Evanston - USA, 2017)
M.Sc., Economics (with distinction) - London School of Economics (London - UK, 2015)
B.Sc., Finance - Universidad del Rosario (Bogota - Colombia, 2012)