Quadratic Funding under Incomplete Information
This thesis explores the properties and limitations of the quadratic funding mechanism, a public goods provision mechanism that has been considered in contexts such as global public goods provision and donor coordination. This thesis shows that quadratic funding is not efficient under incomplete information, and proposes and uses two numeric measures to calculate the size of this mechanism’s inefficiency in a variety of situations. A reviewer praised the professional style of the research, the timeliness of the topic choice and that the thesis identifies an important drawback of the quadratic funding mechanism.
This research is related to our research direction profile on global priorities research.
Researcher profile

Luis Mota Freitas
Luis studied a Bachelor's degree in Economics after reading about it on the 80,000 Hours website, as it seemed like a good way to develop a useful toolkit for thinking about how the world works. During his studies, he became interested in global priorities research, so after he graduated he joined the Global Priorities Institute as a Predoctoral Research Fellow. He's currently applying to PhD programs in Economics, and hopes to use his career to do academic research that will further understanding of foundational aspects for doing good in the world.
Researcher profile
What was your thesis topic?
In what ways do you think your topic improves the world?
In what ways have you changed your mind since you finished writing it?
What recommendations would you make to others interested in taking a similar direction with their research?
Some potential applications of quadratic funding that I mentioned above, like donor coordination or donation matching, still lack a definition that allows us to clearly distinguish them from the traditional public goods provision problem. A promising step in finding a solution to these problems is coming up with such definitions in a formal model, so we can think about what the best solution to these particular problems might look like, and what makes them distinct from problems already discussed in the academic literature.
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