Quadratic Funding under Constrained Matching Funds

Abstract

In this paper I examine some of the properties of the mechanism proposed by Buterin, Hitzig, and Weyl (2019) for public goods financing, under a limited pool of matching funds. I explore questions to understand under which conditions social efficiency will most likely be compromised, such as for example, what determines the size of the optimal pool of matching funds. I also investigate incentives for strategic behavior in contribution giving. Then, using data collected from Gitcoin Grants, a platform where the mechanism is currently implemented, I present stylized facts on the behavior of contributors and analyze the extent of the proposed propositions. Among other findings, I document a tendency of small contributions by backers, scattered among multiple projects, attributable in some extent to strategic behavior. Such contributions stimulate a rapid increase in target quadratic funding matching requirements, and the funding constraint is reached very early in the rounds. I also provide evidence consistent with the idea that contributors internalize the funding constraint restriction and reduce their contributions during the financing round.