I am an Assistant Professor of Economics at IESE Business School.

My research focuses on Microeconomic Theory, Industrial Organization, and Organizational Economics.

You can reach me at eide@iese.edu

I am an Assistant Professor of Economics at IESE Business School.

My research focuses on Microeconomic Theory, Industrial Organization, and Organizational Economics.

You can reach me at eide@iese.edu

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Research

Published work

Discounts as a Barrier to Entry

with Juan-Pablo Montero and Nicolás Figueroa
American Economic Review, Vol. 106, No. 7, July 2016, pp. 1849-1877

To what extent can an incumbent manufacturer use discount contracts to foreclose efficient entry? We show that off-list-price rebates that do not commit buyers to unconditional transfers--like the rebates in EU Commission v. Michelin II, for instance--cannot be anticompetitive. This is true even in the presence of cost uncertainty, scale economies, or intense downstream competition, all three market settings where exclusion has been shown to emerge with exclusive dealing contracts. The difference stems from the fact that, unlike exclusive dealing provisions, rebates do not contractually commit retailers to exclusivity when signing the contract.

Monopolization with Must-Haves

with Juan-Pablo Montero
American Economic Journal: Microeconomics, Vol. 16, No. 3, August 2024, pp. 284-320

An increasing number of monopolization cases have been constructed around the notion of “must-have” items: products that distributors must carry to “compete effectively.” Motivated by these cases, we consider a multiproduct setting where upstream suppliers sell their products through competing distributors offering one stop-shopping convenience to consumers. We show the emergence of products that distributors cannot afford not to carry if their rivals do. A supplier of such products can exploit this must-have property, along with tying and exclusivity provisions, to monopolize adjacent, otherwise competitive markets. Policy interventions that ban tying or exclusivity provisions may prove ineffective or even backfire.

Dual Moral Hazard and the Tyranny of Success

American Economic Journal: Microeconomics, Vol. 16, No. 4, November 2024, pp. 154-191

I explain why current success can undermine an organization's ability to innovate. I consider a standard bandit problem between a safe and a risky arm with two modifications. First, a principal allocates resources. Second, an agent must install the risky arm, which is not contractible. If the principal cannot commit to a resource policy, a dual moral hazard problem emerges: The agent's pay must be tied to the risky arm's success to encourage installation, inducing the principal to stop experimenting with the arm prematurely. This problem intensifies as the safe arm becomes more profitable, potentially leaving the organization worse off.

Working papers

Artificial Intelligence in the Knowledge Economy

with Eduard Talamàs. Updated: December 2024 - EC'24 - R&R Journal of Political Economy

The rise of Artificial Intelligence (AI) has the potential to reshape the knowledge economy by enabling problem solving at scale. This paper introduces a framework to analyze this transformation, incorporating AI into an economy where humans form hierarchical firms to use their time efficiently: Less knowledgeable individuals become “workers” solving routine problems, while more knowledgeable individuals become “solvers,” assisting workers with exceptional problems. We model AI as a technology that transforms computing power into “AI agents,” which can either operate autonomously (as co-workers or solvers/co-pilots) or non-autonomously (only as co-pilots). We show that basic autonomous AI displaces humans towards specialized problem solving, leading to smaller, less productive, and less decentralized firms. In contrast, advanced autonomous AI reallocates humans to routine work, resulting in larger, more productive, and more decentralized firms. While autonomous AI primarily benefits the most knowledgeable individuals, non-autonomous AI disproportionately benefits the least knowledgeable. However, autonomous AI achieves higher overall output. These findings reconcile seemingly contradictory empirical evidence and reveal key tradeoffs involved in regulating AI autonomy. 

Upcoming Presentations:  HEC Paris (Feb. 4), MIT Shaping the Future of Work Initiative (Feb. 19), USC (Feb. 24), SF Fed (Feb. 26), UW (Feb. 28), UBC (Mar. 6), C-BID NYUAD (Apr. 17), Lausanne (Apr. 29), Monash (Sept. 12).

The Turing Valley: How AI Capabilities Shape Labor Income

with Eduard Talamàs. Updated: August 2024

Do improvements in Artificial Intelligence (AI) benefit workers? We study how AI capabilities influence labor income in a competitive economy where production requires multidimensional knowledge, and firms organize production by matching humans and AI-powered machines in hierarchies designed to use knowledge efficiently. We show that advancements in AI in dimensions where machines underperform humans decrease total labor income, while advancements in dimensions where machines outperform humans increase it. Hence, if AI initially underperforms humans in all dimensions and improves gradually, total labor income initially declines before rising. We also characterize the AI that maximizes labor income. When humans are sufficiently weak in all knowledge dimensions, labor income is maximized when AI is as good as possible in all dimensions. Otherwise, labor income is maximized when AI simultaneously performs as poorly as possible in the dimensions where humans are relatively strong and as well as possible in the dimensions where humans are relatively weak. Our results suggest that choosing the direction of AI development can create significant divisions between the interests of labor and capital. 

Upcoming Presentations: SED 2025 invited session on AI and Labor Markets (June 26-28).

Revisiting the Impact of Upstream Mergers with Downstream Complements and Substitutes 

Updated: January 2025 - R&R The Economic Journal

I examine the impact of upstream mergers on negotiated prices when suppliers bargain with a monopoly intermediary selling products to final consumers. Conventional wisdom holds that such transactions reduce negotiated prices when the products are complements for consumers and increase prices when they are substitutes. This is because downstream complementarities or substitutabilities transfer to upstream negotiations, where a merger of complements (substitutes) weakens (strengthens) the suppliers’ bargaining leverage. I challenge this view, showing that this logic breaks down when the intermediary's portfolio includes products beyond those of the merging suppliers. In such cases, the merging suppliers' products may act as substitutes for the intermediary even if they are complements for consumers, or as complements for the intermediary even if they are substitutes for consumers. These findings reveal that upstream conglomerate mergers can increase prices without foreclosure or monopolization, and offer an explanation for buyer-specific price effects in upstream mergers. 

Work in Progress

The Impact of AI on the International Division of Knowledge Work

with Eduard Talamàs. In preparation for the Journal of Monetary Economics (Carnegie-Rochester-NYU Conference Series on Public Policy). 

Advancements in Artificial Intelligence (AI) are transforming the global division of knowledge work. To analyze this transformation, we introduce AI into a two-country model of a knowledge economy where individuals form hierarchical teams to use their time efficiently: those with less knowledge focus on routine work, while those with greater knowledge specialize in problem-solving. Pre-AI, the country with the more knowledgeable workforce—the North—is a net exporter of problem-solving services, while the other country—the South—is a net exporter of routine knowledge work. We model AI as a technology that transforms compute into “AI agents,” which can operate autonomously or non-autonomously, with all compute located in the North. We show that basic autonomous AI reduces the North’s net exports of problem-solving services, potentially reversing trade patterns. In contrast, advanced autonomous AI increases the North’s net exports of problem-solving services, further offshoring routine work to the South. Policies restricting AI autonomy solely in the South preserve pre-AI trade patterns irrespective of whether AI is basic or advanced, whereas similar restrictions solely in the North always undermine them. We discuss the importance of adopting a global perspective on AI regulation.

Upcoming Presentations: Carnegie-Rochester-NYU Conference on Public Policy (May 2-3), IESE (July 28).

Will AI Lead to the End of Experts?

with Eduard Talamàs.

Upcoming Presentations: IESE (July 28).

Teaching

IESE Business School

2020 -          

Economics (EMBA)

Global Economics (MBA)

Microeconomics (Master of Research in Management)

Stanford University

2016 - 2019

Graduate School of Business, Teaching Assistant

Managerial Economics Accelerated - Prof. Nicolas Lambert

Managerial Economics - Prof. Andrzej Skrzypacz

Managerial Economics - Prof. Paul Oyer

Pontificia Universidad Católica de Chile

2013 - 2014

Instituto de Economía, Lecturer

Introduction to Macroeconomics (Undergraduate)