ALT We study stationary equilibrium and comparative statics in an incomplete market economy with risk-sensitive preferences. We prove that a stationary equilibrium exists for every nonnegative degree of risk sensitivity. With independent income, greater risk sensitivity weakly raises aggregate saving at fixed prices and weakly lowers the smallest and the largest equilibrium interest rates. With stochastically monotone Markov income, these comparisons hold when the lower risk-sensitivity parameter is sufficiently small or the upper parameter sufficiently large. For pairs of intermediate values, however, greater risk sensitivity can lower saving, contrary to an existing result in the literature, and can raise the smallest and largest equilibrium rates. An exact decomposition identifies the forces driving these reversals.

ALT We study the sale of an asset to competitive buyers. Before the sale, the seller can buy hard information about the asset from an intermediary who designs and prices a test to maximize his revenue guarantee across equilibria. The test consists of one or more signals, and the seller privately chooses which subset of signals to buy and selectively discloses their realization to the buyers. We show that the intermediary benefits from splitting information into multiple signals and characterize his maximal revenue guarantee as the cumulative entropy of the asset value distribution. This guarantee is achieved by a sequence of “skim from the top” tests with binary, i.i.d. signals and additive pricing. Furthermore, any sequence of tests that achieves the maximal guarantee reveals the asset's value in the limit. For binary values, we also characterize the revenue guarantee for any given number of signals, and show that it is achieved by a test that corresponds to a “Swiss cheese" model of fail

ALT Bergemann, Brooks, and Morris (2015) characterize the consumer and producer surplus pairs that segmentation can produce when the distribution of values is known. I fix only the set of possible values and characterize the pairs that some market and some segmentation can produce. They form a convex polygon. Its outer edge is the largest efficient surplus a market can have when its uniform-price profit is capped, net of that profit, and truncated equal-revenue markets attain it. At the values no segmentation is needed; strictly between two values, reaching the frontier requires splitting a market into two extremal markets. With a continuum of values up to v̄, consumer surplus is at most πln(v̄/π) when producer surplus (the seller's profit) is π, this bound is reached without segmentation, and no market gives consumers more than v̄/e.

ALT We propose a publisher content marketplace that allocates payments for information used in AI-generated answers. The unit of attribution is a “lego block:” a distinct fact or piece of commentary that may appear in articles from multiple publishers. A simple news-reading model connects three payment rules: equal sharing among all publishers reporting on a block, rewarding the publisher who reported a block first, and rewarding indispensable contributions. Each can be represented within a Shapley-value framework. We evaluate the framework using answers to 1,974 search-engine queries about a heavily covered news episode. When attribution considers only the articles retrieved for an individual query, most cited blocks appear unique, and the rules produce nearly identical allocations. A global index covering the full news corpus reveals overlap across publishers, making the choice of payment rule consequential. Premium publishers, defined as established outlets with substantial newsgatherin

ALT We study persuasion that works through memory: a manipulator alters the probabilities with which a Bayesian decision-maker recalls the signals he has received. The decision-maker corrects for the elevated or reduced probabilities of recalling different signals, and this correction disciplines what manipulation can achieve. Manipulation cannot move the average posterior. It backfires on decision-makers with few memories, whose sparse recall is evidence against the favored state, yet it is effective on those with many, who can be led to arbitrarily confident beliefs in the wrong state. It thickens the right tail of the belief distribution and, under Poisson memory, lowers its hazard rate. In a monopoly pricing application, the seller manipulates memory retrieval at high prices, and manipulation in turn raises the optimal price. In a narrative persuasion application, memory manipulation reduces information provision and creates echo chambers.

ALT In auction design with limited information about bidders' value distributions, we provide an optimality foundation for dominant-strategy mechanisms. We show that simple dominant-strategy incentive compatible (DIC) mechanisms–either a second-price auction with a random reserve or the standard second-price auction without a reserve–achieve a revenue guarantee equal to the worst-case optimal revenue attainable by Bayesian incentive compatible (BIC) mechanisms, thereby establishing a robust form of DIC-BIC equivalence.

ALT Organizations rely on languages that imperfectly represent underlying states. We study the interaction of a lying cost, increasing in the distance from the message prescribed by the language, and a deception cost, increasing in the distortion induced in beliefs. Higher lying costs reduce bias and informativeness; higher deception costs do the opposite. Full revelation is sustained as lying costs become small, but with unbounded bias and communication costs. The most efficient policies sustaining nearly full revelation feature high deception costs with some tolerance for lying. With complementarities, targeting messages both untruthful and deceptive sustains full revelation without communication costs.

ALT We study whether a planner can favor students at schools they rank more highly while preserving truthful reporting. The standard implementation of the deferred acceptance (DA) algorithm is typically not the solution. With interior cutoffs, DA with multiple tie-breaking (DA-MTB) solves the planner's optimization problem if and only if the planner's payoff from a school assignment is independent of the students' preferences. This is typically not the case, and strict incentive compatibility under DA-MTB leaves room for improvement via preference-dependent priority adjustments. We characterize optimal rank-dependent cutoff adjustments in a two-school model and show that, in a many-school environment, near-optimal approximately incentive-compatible assignments can be chosen with small support (so each type of student may only attend a small number of schools).

ALT We study matching markets with overlapping reserves governed by heterogeneous priorities. When applicants qualify for multiple reserves, how they are routed can affect reserve utilization and which applicants are admitted. We introduce classify-and-rank choice rules that yield strategy-proof deferred acceptance mechanisms satisfying maximum reserve utilization and priority-respect. We axiomatically characterize our mechanism's admission outcomes for any given classification and reserve order. With two reserve categories, we provide a foundation for the reserve order and establish its distributional implications for access across eligibility groups. Using nine cycles of Chilean school admissions, which feature such reserves, we document reserve-utilization failures under the deployed mechanism and show that their frequency depends sharply on the reserve order. We show how our mechanism can be adapted to Chile's institutional setting to prevent such failures. Under this alternative mecha

ALT This paper establishes the existence and essential uniqueness of an intuitively refined Markov-perfect equilibrium in a duopoly game with sunk costs, barriers to entry, firm-specific technological progress, and irreversible exit. We develop an algorithm that quickly computes the equilibrium by solving for fixed points of a finite sequence of auxiliary contraction mappings, which we label Fake Backward Induction. We illustrate the game's practical value with a quantitative analysis of competition policy in a stochastically growing market with firms idiosyncratically learning by aging. Computing one equilibrium of this example takes 10.2 seconds on one Apple M5 Pro core.

ALT Multiplicative Kantian equilibrium requires agents to evaluate whether they would prefer all players to change their actions by a common proportional factor. This note argues that such a counterfactual is not fully specified by the material payoff environment alone: one must also specify the scale in which proportional universalization is performed. Building on the Sher-Roemer discussion of strategic non-invariance, we characterize how a smooth monotone reparametrization of actions changes the multiplicative Kantian first-order condition. We then illustrate the issue in a simple two-country abatement problem. Universalizing physical abatement and universalizing abatement expenditures are both natural interpretations of "doing one's part," but they lead to different Kantian outcomes, even though they describe the same material environment. The note also identifies special cases in which the interior first-order condition is representation-invariant, including common-exponent power trans

ALT CEO compensation has often been examined from the top down, i.e., as the outcome of a negotiation between the CEO, the board of directors, and the shareholders. While these approaches have provided valuable insights into the nature of CEO compensation and its relations with firm performance and intra-firm inequality, we believe they leave aside the internal decision-making dynamics of CEOs and employees. To fill this research gap, we develop an agent-based model built on the NK framework in which a CEO compensated for long-term firm performance interacts with several employees rewarded for short-term departmental performance. This temporal dichotomy in their respective compensation functions creates a potential temporal misalignment of incentives. By varying the horizon considered by the CEO to make their decisions, we examine how this temporal (mis)alignment of incentives shapes firm performance and pay inequality between the CEO and the employees. Our findings suggest that aligning t

ALT We propose a unified framework for a class of evidence games in which a sender, seeking to increase posterior expectations (e.g., a market price), chooses whether to reveal or withhold her information. Our model nests several classic models, including type-dependent disclosure costs or benefits, uncertain information endowment, and the market for lemons. Frictions are captured as random disclosure costs that are privately known to the sender and noisily inferred by the receiver. We derive a simple characterization of the equilibrium and show that it features increasing disclosure for lower frictions or greater fundamental uncertainty. Further, with high uncertainty or low frictions, greater uncertainty about disclosure costs decreases the likelihood of disclosure. Positive costs do not necessarily rule out unraveling to full disclosure, especially when outcomes have heavy tails or when disclosure costs are not constant. Finally, we demonstrate that the model can be estimated with a sim

ALT Many economic problems have several controls per period, whose joint choice is subject to the curse of dimensionality. Solving them in stages is computationally cheaper, but no general result says when staging is exact. I develop a separability theory, discrete choices and non-concave objectives included: staging is exact if utility, transitions, and constraints depend on earlier decisions only through a state passed forward. For each ordering the smallest such state exists and is unique up to relabeling. Any state that keeps staging exact for all preferences over later decisions and the future must carry everything the smallest one carries for the transition. For affine primitives, the smallest state consists of the linear combinations, such as cash-on-hand, on which later outcomes depend. Its dimensions pick the order whose largest stage is smallest. In a six-choice household model, each stage chooses one variable on a three-dimensional state, the joint problem all six.

ALT Starting with Waldman (1984), it has become widely understood that an important role of promotions in labor markets is that promotions serve as signals of high worker ability. In this paper we explore the common and growing practice called job title inflation which serves a signal jamming role that reduces the signaling value of promotions. We first explore a two-period model and show how job title inflation can arise in equilibrium and increase social welfare both because workers directly value impressive sounding job titles and because the practice reduces job assignment inefficiencies due to signaling. We then introduce into the model an investment choice for young workers concerning human capital accumulation and show that job title inflation can decrease rather than increase welfare in that case. That is, when promotions and the associated wage increases serve as an important incentive for investing in human capital, the use of job title inflation can persist even though the pract

ALT When is social learning efficient if agents have heterogeneous preferences over a set of actions? When myopic agents generate information only about the action they choose, efficiency requires balance such that all high-value actions are discovered. We characterize the value of policies that control the flow of past information to future agents. Under full transparency of past information, the probability of efficient outcomes is approximately one if and only if the prior and preferences are balanced and the log-likelihood ratio distribution satisfies a set of intuitive moment conditions. Noisy bad news is a canonical example. By contrast, approximate efficiency is obtainable on the set of arbitrary adaptive information policies if and only if the prior alone is balanced. Moreover, it suffices to use adaptive evidence policies which permanently and fully disclose subsets of past information. When the prior is imbalanced and approximate efficiency is unattainable, we characterize the va

ALT We analyze auctions with interdependent values and horizontally differentiated bidders, where good news for one bidder is bad news for the other bidders. This generates a winner's bliss, reversing the well-known winner's curse: winning means buying an object that is more valuable than a naïve estimate suggests. Our main result is about the English auction. We introduce the “own effect property,” generalizing the single-crossing condition, to prove the existence of an efficient ex-post equilibrium. Regarding revenue, we show that with affiliated signals, the English auction yields no more revenue than the second-price auction, while independent signals yield the standard revenue equivalence.

ALT We study steady-state equilibria of a sequential learning game in which each agent chooses between a safe action and a risky action of unknown profitability. Before choosing, each agent observes how many of the last m agents adopted the risky action, but not whether they were informed or what their adoption costs were. We show that uninformed agents' imitation decisions can be strategic complements: the more likely uninformed agents are to join risky-action herds, the more informative those herds become about the action's profitability. When this complementarity gives rise to multiple equilibria, the one that maximizes the probability of imitation by uninformed agents also maximizes agents' welfare.

ALT We explore the implications of the principle of monotonicity in the problem of sharing the revenues raised from subscriptions to music streaming platforms among content providers. We formalize various forms of this principle as several axioms for popularity indices, which generate sharing rules in this setting. We show that, combined with some other basic axioms (such as additivity, symmetry, or pairwise homogeneity), they provide axiomatic characterizations of focal indices for this problem, as well as more general families comprising them.

ALT I study the coarse revenue guarantee (CRG) of the single-unit first-price auction with common values. The CRG is the minimum expected revenue over all information structures and all Bayes coarse correlated equilibria (BCCE), the equilibrium notion to which no-regret learning leads. Identical play, in which all bidders submit the same bid, attains the worst-case revenue, and this reduction yields a closed-form characterization. The coarse guarantee is positive and increases with the number of bidders N. It lies strictly below the revenue guarantee of Bergemann, Brooks and Morris (2017) at every finite n, and the gap between the two closes at rate log N / N. I extend the analysis to reserve prices, symmetric and asymmetric priors, other standard auctions, and an unknown value distribution.