Shoshana Vasserman

dblp:165/2985 · DBLP profile ↗
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3ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · unresolved

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Artificial intelligence and machine learning · 3 · 1 first-author · 1 since 2021Theory of computation · 2 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
YearPublicationVenuePosition
2022 Robust Bounds for Welfare Analysis
abstract
Economists routinely make functional form assumptions about consumer demand to obtain welfare estimates. How sensitive are welfare estimates to these assumptions? We answer this question by providing bounds on welfare that hold for families of demand curves commonly considered in different literatures. We show that commonly chosen functional forms, such as linear, exponential, and CES demand, are extremal in different families: they yield either the highest or lowest welfare estimate among all demand curves in those families. To illustrate our approach, we apply our results to the welfare analysis of energy subsidies, trade tariffs, pensions, and income taxation.
Zi Yang Kang, Shoshana Vasserman
EC2
2020 Voluntary Disclosure and Personalized Pricing
S. Nageeb Ali, Greg Lewis, Shoshana Vasserman
EC3
2015 Implementing the Wisdom of Waze
Shoshana Vasserman, Michal Feldman, Avinatan Hassidim
IJCAI1