Preference Elicitation for Participatory Budgeting

Gerdus Benadè (), Swaprava Nath (), Ariel D. Procaccia () and Nisarg Shah ()
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Gerdus Benadè: Questrom School of Business, Boston University, Boston, Massachusetts 02215
Swaprava Nath: Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, 208016 Kanpur, India
Ariel D. Procaccia: School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138
Nisarg Shah: Department of Computer Science, University of Toronto, Toronto, Ontario M5S 2E4, Canada

Management Science, 2021, vol. 67, issue 5, 2813-2827

Abstract: Participatory budgeting enables the allocation of public funds by collecting and aggregating individual preferences. It has already had a sizable real-world impact, but making the most of this new paradigm requires rethinking some of the basics of computational social choice, including the very way in which individuals express their preferences. We attempt to maximize social welfare by using observed votes as proxies for voters’ unknown underlying utilities, and analytically compare four preference elicitation methods: knapsack votes, rankings by value or value for money, and threshold approval votes. We find that threshold approval voting is qualitatively superior, and also performs well in experiments using data from real participatory budgeting elections.

Keywords: group decisions; voting committees; utility preference theory; artificial intelligence (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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