Problem
Research questions and friction points this paper is trying to address.
multidimensional screening
searchable menus
greedy search
utility-maximizing
Searchable Menus
๐ค AI Summary
ๆฌๆ็ ็ฉถไบๅจๅค็ปด็ญ้ไธญ๏ผ้่ฟ้ๅถ่ๅๅฏๆ็ดขๆงๆฅ็ฎๅไปฃ็ไบบ้ๆฉ่ฟ็จ็ๆนๆณ๏ผๆๅบไบๆไผๅฏๆ็ดข่ๅ็่ฎพ่ฎกใ
๐ Abstract
Multidimensional screening is (in)famously intractable. In this paper, we study optimal screening mechanisms subject to a tractability constraint from the agent's perspective. Specifically, we require that the menu of options offered by the designer can be ordered so that, regardless of her preference type, the agent can find a utility-maximizing option via greedy search: any locally optimal choice must also be globally optimal. In one-dimensional screening with the single-crossing property, this requirement has no bite. In multidimensional environments, however, searchability restricts the set of implementable outcomes. In the multiproduct monopoly problem, the optimal searchable menu is a sparse upgrade menu: higher tiers offer higher allocation probabilities for every good, and the number of tiers is at most the number of goods. In a multidimensional screening problem with money and ordeals, the optimal searchable menu offers the agent a single way to obtain the good. In income taxation with rich multidimensional heterogeneity, a tax schedule is searchable if and only if it is progressive.
Innovation
Methods, ideas, or system contributions that make the work stand out.
searchable menus
multidimensional screening
greedy search
sparse upgrade menu
progressive tax schedule
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