I am Assistant Professor in the Department of Economics at the University of Colorado, Boulder. Prior to this, I was a postdoctoral fellow at the Cowles Foundation at Yale University. I completed my PhD in Economics at the University of Arizona in 2023.
My primary research focuses on microeconomic theory.
*In Mexico, it is standard to use both paternal and maternal surnames. My first name is Ernesto, and my full last name is Rivera Mora.
When does more information robustly increase an agent's welfare -- when does Blackwell monotonicity hold? In the standard setup, Blackwell (1951, 1953) shows that all agents with a Bayesian updating rule weakly benefit from more information, regardless of the decision problem they face. This paper goes beyond the standard setup by studying Blackwell monotonicity in settings with motivated reasoning and psychological preferences.
We analyze the role of a central authority in mitigating collateral crises through public disclosure of information about borrowers' collateral value. Borrowers seek funding using collateral of unknown quality, and lenders can perform costly investigations. We find that information disclosure by a central authority can improve welfare and that the optimal policy is not full transparency.
This paper studies mechanism design in environments where a designer can only commit to deterministic mechanisms. If there is one agent, stochastic mechanisms may strictly dominate deterministic mechanisms. The main theorem shows an equivalence between stochastic and deterministic mechanisms, whenever there are two or more agents. The equivalence is achieved through an indirect deterministic mechanism.
This paper defines exchangeable-robust implementation. This concept requires interim incentive compatibility in environments where agents have arbitrary exchangeable first-order beliefs, i.e., in environments where the agents perceive the rest of the agents as ex-ante symmetric. Exchangeable-robust implementation requires weaker conditions than ex-post implementation; thus, it extends the set of social choice correspondences that can be implemented.
Markets for information are ubiquitous in modern society. Understanding how information providers choose to sell information is important for designing policies that improve efficiency. This paper studies markets for information when two uninformed agents play a quadratic game and characterizes the revenue maximizing information-selling schemes. The optimal way to sell information depends on the degree to which agents' actions are strategic substitutes or complements.
This paper studies information selling in environments in which (1) the seller has limited commitment power, and (2) the buyer and the seller hold different beliefs about the state of the world. We show that in environments with a common prior, there is no advantage to selling information sequentially; the seller cannot achieve higher revenue than by offering an experiment that fully reveals the state in one period.
We study mechanism design for a sophisticated agent with non-expected utility (EU) preferences. We show that the revelation principle holds if and only if all types are EU maximizers: if at least one type is a non-EU maximizer, randomizing over dynamic mechanisms generates a strictly larger set of implementable allocations than using static mechanisms.
This paper studies mechanism design when agents have belief-dependent preferences, in that utilities depend on the agents' ex-post beliefs about types. For instance, agents may be subject to curiosity, image concerns, or privacy concerns. In this setting, the textbook revelation principle does not hold, since mechanisms can provide agents with information that affects ex-post beliefs. This paper uses a psychological game framework suited for mechanism design and provides a novel version of the revelation principle for belief-dependent preferences.
The paper analyzes information sharing in neutral mechanisms when an informed party will face future interactions with an uninformed party. Neutral mechanisms are mechanisms that do not rely on the provision of evidence, conducting experiments, verifying the state, or changing the after-game. To address this question, the paper develops a reduced-form approach that characterizes the agents' payoffs in terms of belief-based utilities.
We study scaling auctions for procurement environments where sellers are risk-averse and have private fixed costs. We show that sellers' bidding behavior can be obtained as the solution to an auxiliary Hicksian demand problem, in which the weights of the scoring rule serve as prices. Consequently, changes in weights induce a pure substitution effect, rationalizing the skewed bidding behavior observed in the empirical literature.
We experimentally study procurement auctions for infrastructure projects under ex-post uncertainty. We compare fixed-price (cash) auctions, scaling (unit-price) auctions, and a novel equity auction in which bidders compete by requesting a fraction of variable costs to be covered. The experiment varies how bidder heterogeneity enters the environment: through input-quantity risk or through marginal costs.
Rivera Mora [2025] develops a reduced-form approach to analyze information sharing between an informed party and an uninformed party who will engage in future interactions. The reduced-form approach employs belief-dependent utilities to characterize payoffs of Bayesian equilibria through the agents' hierarchies of beliefs. This paper shows that -- by expanding the agents' domain of uncertainty -- reduced forms and reduced-form representations exist for a broad class of games, including all games with finite action spaces.