Welcome!
I'm a Postdoctoral Associate at the Center for Algorithms, Data, and Market Design at Yale (CADMY). I work on economic theory and market design. My CV is here.
I earned my PhD in Economics from Penn State.
You can contact me at salvador.candelas@yale.edu.
Subsidizing Sequential Search (Job Market Paper) joint with Nicole Immorlica & Brendan Lucier [PDF]
Abstract: We study markets where firms compete for consumer attention by subsidizing costly product inspection. Such subsidies do not alter product quality, but they reshape the consumer's search order by lowering inspection costs. We establish a subsidy–sorting principle: in any equilibrium, higher–quality firms offer weakly larger subsidies, inducing consumers to search in descending subsidy order. Under the Intuitive Criterion, a unique equilibrium survives: low–quality firms do not subsidize, intermediate types separate with strictly increasing subsidies, and high–quality firms pool by offering full subsidy. This outcome minimizes consumer's search costs among all equilibria and implements efficient inspection. We then extend the analysis to AI–mediated platforms that can mint and price ``inspection tokens”. The platform’s optimal linear pricing induces excessive inspection relative to the social optimum. While this distortion does not reduce consumer welfare, it reallocates sellers' surplus toward the platform.
When Colleges Compete: Signals, Noise, & Equilibrium Outcomes joint with S. Nageeb Ali & Ran I. Shorrer [slides]
Abstract: This paper proposes a framework of college admissions in which colleges choose who to admit based on noisy signals, leading to a winner's curse. We find conditions for a unique equilibrium in threshold strategies. Our main results evaluate how correlation in colleges' signals affects matching and welfare. Although each applicant may favor a more independent draw, greater correlation benefits applicants overall: in equilibrium, a larger fraction then obtains a higher ranked choice. Weaker applicants gain unambiguously whereas stronger ones risk going unmatched. Greater correlation reduces assortative matching and makes colleges worse off. These findings speak to the debate on standardized testing by highlighting how public signals benefit applicants. We use this framework to also study early decision policies, offering an informational rationale for why colleges favor those applying early.
Revealing Compatible Choice, Mathematical Social Sciences, December 2025 [PDF]
Abstract: This paper presents a framework for multi-agent settings where each agent must select an action compatible with the choices of others. Agents face a technological constraint that dictates which alternative profiles are feasible, and each agent chooses her preferred option from those available, given the others' choices. I distinguish between two cases: rival and non-rival alternatives. For a generic problem, I introduce a key axiom, Acyclicity, that characterizes the decision-making process. In the non-rivalrous case, Acyclicity can be further decomposed into two properties: WARP-CC and Joint Acyclicity. Additionally, I propose revealed preference relations to conservatively identify players’ preferences and assess compatibility based on observable, potentially limited choice data. Importantly, the construction and the results presented on this paper do not rely on access to the complete choice observations.
How Intermediaries Shape Labor Market Outcomes
Abstract: Labor markets today use digital platforms for workers to learn about positions and for firms to fill their vacancies. These platforms routinely charge fees to one or both sides of the market and choose a recommendation policy that makes some workers more visible than others. This paper develops a model for how a profit-maximizing intermediary would make these choices and their effects on the labor market. In this model, the intermediary observes workers' abilities and chooses between selling firms perfect information or promoting lower ability workers to firms but at a fee. We characterize conditions under which each regime is optimal.
Formal modeling in economics joint with Agustín Deambrosi. Reference Module in Social Sciences, December 2025 [link]
Abstract: This chapter provides a critical introduction to formal economic models. It explains how economists use simplified, abstract representations to isolate causal mechanisms, generate testable predictions, and guide policy decisions. While the mathematical formalism and assumptions can seem opaque to outsiders, the logic behind these models is accessible and powerful. We aim to demystify formal models, showing how their transparency, internal consistency, and disciplined abstraction can clarify complex social phenomena. Readers will learn to interpret models thoughtfully, evaluate their assumptions, and engage with them as analytical tools.