arXiv subjects

Kemal Ozbek

Publications and source records attributed to Kemal Ozbek.

7 recordsLinked to original sources

arXiv2026

Auction Design with Private Priors and Costly Learning

We study two-stage auctions in which bidders privately know their valuation priors and learning costs, while the seller jointly designs information acquisition, continuation allocation, and payments. Revenue maximization requires screening learning costs while satisfying cross-prior incentives, potentially distorting both experimentation and continuation allocation. We derive a revenue representation involving allocated posterior values, virtual learning costs, and prior-dependent rents, and characterize cross-prior incentives through difference inequalities. We establish existence of optimal mechanisms for finite experiment menus and arbitrary prior distributions. With finite prior support, bounded finite-category linear programs approximate optimal revenue at a linear rate while preserving exact dynamic incentive compatibility and interim individual rationality. Their dual yields joint optimality conditions for experimentation, allocation, and payments. A two-prior example demonstrates that efficient continuation can be revenue-suboptimal and that cost-contingent experimentation can strictly increase revenue.

econ.TH↗

arXiv2026

Implicit Smooth Ambiguity: Perception, Attitude, and Identification

This paper develops a model of identifiable smooth ambiguity in a finite-state Anscombe-Aumann framework in which ambiguity perception and the ambiguity-attitude representation may depend on the act's endogenous certainty-equivalent utility level. The framework separates two sources of utility-level dependence that standard smooth-ambiguity models hold fixed. Neutral-transfer experiments within revealed cells recover conditional beliefs, while compensation experiments across cells recover cell weights and locally revealed ambiguity-attitude scales. These objects have distinct behavioral content. After the within-level structure is extended globally, ambiguity perception is identified at each certainty-equivalent level, whereas variation in admissible level-specific global attitude indices need not by itself reflect behaviorally identified variation in ambiguity attitude. Cross-level restrictions determine when the locally revealed attitude scales can instead be represented by one common global ambiguity-attitude index. The baseline characterization yields a doubly implicit smooth-ambiguity representation with level-specific perception and potentially level-specific global attitude indices. Requiring one common ambiguity-attitude index gives an intermediate stable-attitude model in which only perception may vary; imposing perception stability as well yields standard identifiable smooth ambiguity within the maintained full-support, neutrally separated, fixed-partition environment with at least three revealed cells. The contribution is therefore a behavioral decomposition of utility-level dependence in smooth ambiguity into separately revealed perception and attitude components.

econ.TH↗

arXiv2026

Utility-Level-Dependent Ambiguity

Experimental evidence suggests that ambiguity-sensitive choice can vary systematically with the circumstances of a decision. This paper isolates one channel within a stable preference relation: ambiguity weighting may depend on the act's certainty-equivalent level. After the standard Anscombe-Aumann calibration of consequence utility, a set of behavioral axioms yields a unique continuous family of normalized monotone capacities $\{ν_v\}_{v\in(0,1)}$. Each nonendpoint act is evaluated by the Choquet integral associated with the capacity at its own interior certainty-equivalent level, while nonendpoint acts on the same indifference surface share the same capacity. Binary event comparisons identify local event weights at each elicited level and trace their cross-level variation, providing tests of the fixed-capacity restriction. Local uncertainty aversion is equivalent to convexity of $ν_v$ and yields an implicit multiple-priors representation with certainty-equivalent-indexed local cores. Certainty translation invariance holds if and only if the capacity is fixed across levels, recovering the maintained nondegenerate fixed-capacity Choquet expected utility benchmark; global mixture-betweenness yields implicit additive utility, and imposing both restrictions recovers full-support subjective expected utility. The capacity schedule is a reduced-form ambiguity weighting whose variation may reflect changes in ambiguity perception, ambiguity attitude, or both.

econ.TH↗

arXiv2026

Bayesian Persuasion under Bias Management

A principal delegates choice to an agent whose decision depends on both beliefs and tastes. The principal can steer the delegated decision using two costly instruments: (i) an information policy that determines a Bayes--plausible distribution of posteriors, and (ii) a bias-management policy that shifts the agent's effective taste. We study a binary-state, two-action, convex hull of two benchmark tastes specialization with posterior-separable information costs. The analysis admits an inner--outer decomposition: optimal bias management is bang--bang (either no intervention or the minimal intervention needed to flip the agent's action), while the optimal information policy is characterized by concavification of an endogenous posterior value function that already incorporates optimal management and information costs. This structure clarifies how information acquisition and bias management interact; they can be complements, substitutes, or both depending on the primitives of the model. Information changes which posteriors are realized and hence where management is used; management reshapes the curvature and kinks of the posterior value function and hence the marginal value of information. The model delivers regime classifications for pooling vs. informativeness and for management at different posteriors within informative signals, and highlights how comparative statics can be monotone or non-monotone depending on how concavification contact points move with costs.

econ.TH↗

arXiv2025

Axiomatic Foundations of Bayesian Persuasion

In this paper, we study axiomatic foundations of Bayesian persuasion, where a principal (i.e., sender) delegates the task of choice making after informing a biased agent (i.e., receiver) about the payoff relevant uncertain state (see, e.g., Kamenica and Gentzkow (2011)). Our characterizations involve novel models of Bayesian persuasion, where the principal can steer the agent's bias after acquiring costly information. Importantly, we provide an elicitation method using only observable menu-choice data of the principal, which shows how to construct the principal's subjective costs of acquiring information even when he anticipates managing the agent's bias.

econ.TH↗

arXiv2025

Optimal Auction Design under Costly Learning

We study optimal auction design in an independent private values environment where bidders can endogenously -- but at a cost -- improve information about their own valuations. The optimal mechanism is two-stage: at stage-1 bidders register an information acquisition plan and pay a transfer; at stage-2 they bid, and allocation and payments are determined. We show that the revenue-optimal stage-2 rule is the Vickrey--Clarke--Groves (VCG) mechanism, while stage-1 transfers implement the optimal screening of types and absorb information rents consistent with incentive compatibility and participation. By committing to VCG ex post, the pre-auction information game becomes a potential game, so equilibrium information choices maximize expected welfare; the stage-1 fee schedule then transfers an optimal amount of payoff without conditioning on unverifiable cost scales. The design is robust to asymmetric primitives and accommodates a wide range of information technologies, providing a simple implementation that unifies efficiency and optimal revenue in environments with endogenous information acquisition.

econ.TH↗

arXiv2025

Flexible Learning via Noise Reduction

We develop a novel framework for costly information acquisition in which a decision-maker learns about an unobserved state by choosing a signal distribution, with the cost of information determined by the distribution of noise in the signal. We show that a natural set of axioms admits a unique integral representation of the cost function, and we establish the uniform dominance principle: there always exists an optimal experiment that generates signals with uniform noise. The uniform dominance principle allows us to reduce the infinite-dimensional optimization problem of finding an optimal information structure to finding a single parameter that measures the level of noise. We show that an optimal experiment exists under natural conditions, and we characterize it using generalized first-order conditions that accommodate non-smooth payoff functions and decision rules. Finally, we demonstrate the tractability of our framework in a bilateral trade setting in which a buyer learns about product quality.

econ.TH↗