# Review of Gitcoin Quadratic Funding Round 3

2019 Oct 24 See all posts

Review of Gitcoin Quadratic Funding Round 3

Special thanks to the Gitcoin team and especially Frank Chen for working with me through these numbers

The next round of Gitcoin Grants quadratic funding has just finished, and we the numbers for how much each project has received were just released. Here are the top ten:

### Dominance of large projects

One other pattern that we saw in this round is that popular projects got disproportionately large grants:

To be clear, this is not just saying "more contributions, more match", it's saying "more contributions, more match per dollar contributed". Arguably, this is an intended feature of the mechanism. Projects that can get more people to donate to them represent public goods that serve a larger public, and so tragedy of the commons problems are more severe and hence contributions to them should be multiplied more to compensate. However, looking at the list, it's hard to argue that, say, Prysm ($3,848 contributed,$8,566 matched) is a more public good than Nimbus ($1,129 contributed,$496 matched; for the unaware, Prysm and Nimbus are both eth2 clients). The failure does not look too severe; on average, projects near the top do seem to serve a larger public and projects near the bottom do seem niche, but it seems clear that at least part of the disparity is not genuine publicness of the good, but rather inequality of attention. N units of marketing effort can attract attention of N people, and theoretically get N^2 resources.

Of course, this could be solved via a "layer on top" venture-capital style: upstart new projects could get investors to support them, in return for a share of matched contributions received when they get large. Something like this would be needed eventually; predicting future public goods is as important a social function as predicting future private goods. But we could also consider less winner-take-all alternatives; the simplest one would be adjusting the QF formula so it uses an exponent of eg. 1.5 instead of 2. I can see it being worthwhile to try a future round of Gitcoin Grants with such a formula ($$\left(\sum_i x_i^{\frac{2}{3}}\right)^{\frac{3}{2}}$$ instead of $$\left(\sum_i x_i^{\frac{1}{2}}\right)^2$$) to see what the results are like.

### Individual leverage curves

One key question is, if you donate $1, or$5, or $100, how big an impact can you have on the amount of money that a project gets? Fortunately, we can use the data to calculate these deltas! The different lines are for different projects; supporting projects with higher existing support will lead to you getting a bigger multiplier. In all cases, the first dollar is very valuable, with a matching ratio in some cases over 100:1. But the second dollar is much less valuable, and matching ratios quickly taper off; even for the largest projects increasing one's donation from$32 to $64 will only get a 1:1 match, and anything above$100 becomes almost a straight donation with nearly no matching. However, given that it's likely possible to get legitimate-looking Github accounts on the grey market for around those costs, having a cap of a few hundred dollars on the amount of matched funds that any particular account can direct seems like a very reasonable mitigation, despite its costs in limiting the bulk of the matching effect to small-sized donations.