arXiv subjects

Marek Pycia

Publications and source records attributed to Marek Pycia.

3 recordsLinked to original sources

arXiv2026

Complex Menus in Discriminatory Pricing

Advances in technology decrease the costs of offering and choosing from large menus of varieties. As these complexity costs fall, how large are the menus offered by monopolists likely to become? For the multi-product or multi-attribute case, ubiquitous in practice, we show that optimal menus are generically infinite in the absence of complexity costs. Complexity costs can decrease the menu size, but it grows without bound as these costs decrease. These results have no analogue in the single-dimensional model and do not rely on non-linearities in production costs or preferences; the extensive product differentiation is caused by screening considerations alone.

econ.TH↗

arXiv2026

Mechanism Design with Information Leakage

We study the design of mechanisms---e.g., auctions---when the designer does not control information flows between mechanism participants. A mechanism equilibrium is leakage-proof if no player conditions their actions on leaked information; a property distinct from both ex-post and posterior incentive compatibility. Only leakage-proof mechanisms can implement social choice functions in environments with leakage; efficient auctions and revenue-maximizing ones need to be leakage-proof. Second-price and ascending auctions are leakage-proof, while first-price auctions need not be. Appropriately designed Dutch auctions are leakage-proof and attain optimal revenue even with irregular value distributions. In multi-unit environments, leakage-proof mechanisms can attain the optimal Bayesian revenue even when dominant-strategy mechanisms cannot.

econ.TH↗

arXiv2026

Minimizing Volatility: Optimal Adjustment with Evolving Feasibility Constraints

Minimizing volatility and adjustment costs is of central importance in many economic environments, yet it is often complicated by evolving feasibility constraints. We study a decision maker who repeatedly selects an action from a stochastically evolving interval of feasible actions in order to minimize either average adjustment costs or variance. We show that for strictly convex adjustment costs (such as quadratic variation), the optimal decision rule is a reference rule in which the decision maker minimizes the distance to a target action. In general, the optimal target depends both on the previous action and the expectation of future constraints; but for the special case where the constraints follow a random walk, the optimal mechanism is to simply target the previous action. If the decision maker minimizes variance, the optimal policy is also a reference rule, but the target is a constant, which is not necessarily equal to the long-term average action. Compared to mid-point heuristics, these optimal rules may substantially reduce quadratic variation and variance, in natural environments by $50\%$ or more. Applied to stock market auctions, our results provide an explanation for the wide-spread use of reference price rules. We also apply our results to bilateral trade in over-the-counter markets, capacity planning in supply chains, and positioning in political agenda setting.

econ.TH↗