A look at “radical markets” and quadratic voting: regulating markets with markets themselves

The book Radical Markets, by jurist Eric Posner and economist Glen Weyl, attempts an interesting new approach to a topic that seeks to use the power of the market itself to regulate markets.

Part 1.
The book Radical Markets, by jurist Eric Posner and economist Glen Weyl, attempts an interesting new approach to a subject that seeks to regulate markets by the power of the market itself. Prior to this book, numerous theoretical pioneers have tried, from Keynes to Hayek, from regulation to deregulation, Radical Markets offers a way of thinking that “reconciles” the left and the right and develops a new idea – why not be more radical in expanding markets and using the power of markets themselves to regulate them? itself to regulate the market? Why not try to use more market-based mechanisms to achieve public reform of private property rights? Why not use better mathematical and game theory tools to design a more balanced voting infrastructure?

Ultimately, the question becomes whether a “free market socialism” can be designed to solve the problem of distributing public goods. Would such a newly designed market solve today’s problems?

Quadratic Financing is a mechanism designed to solve the problem of inefficiency in financing public goods, such as open source software development, that Vitalik and Harvard University’s Zoë Hitzig, co-author of the book, and Microsoft’s Glen Weyl, discuss in a 2018 collaborative paper. A mechanism designed to address inefficiencies in financing software development (free-riding, non-competitive underinvestment). Since then, Vitalik has recommended this mechanism design on several occasions, such as in Gitcoin Grants to aid practice. The new economic model they propose in their paper, Liberal Radicalism (LR, liberal radicalism), offers an avant-garde new rule for optimally allocating public goods with DAOs.

As described in the article “Radical Markets: Regulating Markets with the Power of the Market Itself,” take private property rights such as property and land as an example: on the issue of private rights to land, there are two dominant models: the government sells land in a lump sum but restricts transactions; or no restrictions and pays annual property taxes. Both of these breed many problems, such as corruption, property tax assessment and various other problems.

Scholars, represented by Harberger, have proposed a new taxation scheme, the “Harberger Tax” or “Self-Assessment Tax on Public Ownership”. It may make private property rights like “real estate” somehow more mobile. For example, we would “require” privately owned property to be publicly marked up and taxed annually at a percentage of that price, and anyone in the market could buy the asset at that public price, just as they would buy and sell stocks.

If owners are allowed to specify the value of their property themselves and pay an annual tax rate of 2%. They must be willing to sell to anyone at that price, regardless of how much they estimate for their property. If the tax rate equals the probability that the property will be sold each year, then optimal allocative efficiency is achieved: for every $1 increase in the value of the self-assessed property, the tax paid increases by $0.02, and this also means that there is a 2% probability that someone will buy the property and be willing to pay an extra $1, so there is no incentive to cheat on all sides.

According to the rational man hypothesis, if the asking price is higher than a reasonable price, more taxes will be paid; if it is lower than a reasonable price, it will be quickly and easily bought, which seems to achieve the best allocative efficiency of the property transaction, except for the problem that such a highly liquid property may change hands every day. But there are now a plethora of financial derivatives based on property values, and trading title out of use is not as unrealistic as one might think. For example, UPRETS, Centrifuge, and others are trying to incorporate physical assets into mortgage pools in mainstream DeFi, and asset synthesis protocols such as Synthetics, Linear, and Mirror are capturing the prices of traditional stocks, commodities, futures, etc. to trade.

A beneficial side effect of this tax is that it removes the information asymmetry flaw that exists in today’s real estate sales, where owners have an incentive to expend effort to make up properties look good, even if in a potentially misleading way. And as the Harberger tax model is set up, if you somehow fool the world that your house is worth 5% more, then when you sell it, you’ll get 5% more, but before that happens, you have to pay 5% more in taxes, or someone will snap that money off in the original price even faster.

In the article “V-God Explains “Aggressive Markets””, the authors point out that if you want to increase investment efficiency, you can use a hybrid solution with low taxes: as taxes are gradually reduced to increase investment efficiency, the loss of allocative efficiency is lower than the increase in investment efficiency. The reason is that the most valuable sales are those where the buyer is willing to pay a much higher price than the seller is willing to accept. These are the first transactions that result from declining prices because even small price reductions avoid discouraging these most valuable transactions from occurring. Indeed, the size of the social loss from monopoly power grows quadratically over the range of such power. Thus, the distributional damage caused by private ownership that can be eliminated by reducing the markup by 1/3 is: 5/9 = (3^2-2^2)/(3^2).

This concept of quadratic deadweight loss (QDL) is a truly important economic insight.

In the Internet world, domain names are a kind of “property” like property, and in the blockchain world and virtual space, there are more virtual assets in the form of NFTs (Non-Fungible Tokens), which have a limited number, public resource properties or scarcity and lack of price discovery qualities. Vitalik Buterin has argued for this new approach to market allocation of monopoly assets to reduce “vacancy” and “monopoly” in the non-profit organization ENS (Ethernet Domain Name Service).

As discussed in “Radical Markets: Regulating Markets with the Power of the Market Itself,” QV (Quadratic Voting) is essentially a novel exploration of political economy: can market forces be used to price politics and voting power? Instead of relying on majority rule, i.e., one-person-one-vote, which can lead to “tyranny of the majority,” and on easily manipulated methods such as delegates (similar to specializing in swing states to gain more electoral votes), could a market approach be introduced, where the cost of the first yes vote is 1 vote and the cost of the second yes vote could a market approach be introduced where the first yes vote costs 1 vote and the second yes vote costs 4 votes (the quadratic power of 2)?

Part 2
The DAO Architecht article explains the quadratic voting and quadratic fundraising problem described by Vitalik Buterin in “Quadratic Payments”. It also explains the DoraHacks at HackerLink.io Quadratic Voting Grant to fund blockchain developer projects.

One Person, One Vote
In public sector governance, voting is required to determine how funds are spent and, in turn, which projects receive priority funding. For example, a city allocates its budget among projects such as fixing parks, hospitals, and roads, or a public chain eco-fund co-funded by communities and institutions allocates its budget among projects such as wallets, developer tools, document editing, hackathons, community podcasts, and privacy protocols.

There are usually two ways to vote: “one person, one vote” and “one dollar, one vote”.

The essence of “one person, one vote” is that no matter how much you care about something, you can only give it one vote. In Vitalik’s article, one person, one vote is explained as follows: if you care about something (or a public good/project), then the cost of your first vote is extremely low, but if you want to continue contributing, the cost becomes infinitely high (because you only have one vote). Thus, the relationship between your contribution and your influence can be represented by the following graph.

A look at "radical markets" and quadratic voting: regulating markets with markets themselves

Image credit: Quadratic Payments

One dollar one vote (or one unit Token one vote)
One Dollar One Vote is a way to vote with money (or Token). This approach allows people who care more about an issue to contribute more (provided you have enough money/Token). PoS consensus, for example, implements this idea. Obviously, this approach leads to the ability to buy influence with money. For example a community wants to allocate a budget on two public infrastructure projects: building a road and building a garden on a street corner. Probably most people are more concerned about the road, but one rich person who lives on the corner is very concerned about building a garden on the corner. At this point, this rich person can pay a lot of money, and as a result, the project that most people care about may lose to the project that very few people care about. The relationship between your contribution and your influence can be represented by the following graph.

A look at "radical markets" and quadratic voting: regulating markets with markets themselves

What if we want to take into account people’s concerns about different issues while avoiding the dilemma of “buying influence with money”?

Quadratic Voting
Quadratic Voting is a compromise solution to this problem. Quadratic voting can be implemented with a very simple mechanism: for each unit of vote purchased, the price of the vote increases by one unit. For example, if we vote with USDC, the first vote is 1 USDC, the second vote is 2 USDC, …, and the nth vote is n USDC.

A look at "radical markets" and quadratic voting: regulating markets with markets themselves

Image credit: Quadratic Payments

Thus, if a person wants to vote n on a project, it costs about (n^2)/2 USDC, so the payout cost is quadratic in the number of votes. Thus, as you can see from the graph above, quadratic voting linearly matches the amount of support for a project with the number of votes available.


A look at "radical markets" and quadratic voting: regulating markets with markets themselves
A look at "radical markets" and quadratic voting: regulating markets with markets themselves
A look at "radical markets" and quadratic voting: regulating markets with markets themselves

Quadratic Funding (Quadratic Funding)
The next question is, what if the number of projects that can be voted on is dynamic? This situation can be handled with Quadratic Funding.

Quadratic funding allows voting to become an endogenous process for funding projects. Anyone can contribute to a project and complete a vote while contributing.

A look at "radical markets" and quadratic voting: regulating markets with markets themselves

This contribution/voting process can be described using the above diagram.

  1. Each green square represents the amount of one contribution, the area C of the large square can be interpreted as the total grant pool amount, and the yellow part area S can be interpreted as a pool of externally supported grant funds. We arrange all the green squares on the diagonal of the large square. At this point, the amount put in by each contributor is Ci, and SS can be interpreted as a pool of externally supported grants

Then the area of the large square is.

A look at "radical markets" and quadratic voting: regulating markets with markets themselves

The amount of the grant is

A look at "radical markets" and quadratic voting: regulating markets with markets themselves

at any time, as long as there is one more contributor, then

A look at "radical markets" and quadratic voting: regulating markets with markets themselves
  1. If the S and grant pools do not match exactly, they can be prorated based on the yellow area
  2. Multiple small contributions can result in a large yellow area, thus allowing the project to win a larger funding match

For example, if a project has ten people, each contributing 1 USDC, then the total contribution is 10 USDC. at this point, the area of the large square is 100, so the yellow portion of the area is 90. with sufficient funding, the project could be funded for a total of 100 USDC, with 10 USDC coming from contributors and 90 USDC coming from grant funds.

Quadratic funding can be further understood from two perspectives. First, anyone’s funding of a project is not only meaningful to herself, but also amplifies the value of other funders, and this amplification is quadratic (if N people are involved in the contribution, then there will be N × (N-1)/2N × (N-1)/2 combinations. Thus, quadratic funding solves the “tragedy of the commons” problem to some extent. Conversely, quadratic giving is a special case of quadratic voting: all funders are voting for the project during the grant process, while the grant pool is “reversing the vote. Overall, quadratic voting and quadratic funding balance “one person, one vote” and “one dollar, one vote” and avoid the problems associated with each of these “extremes” of voting. The problems associated with each of these “extreme” voting methods are avoided.

How Second-Party Fundraising Solves the Tragedy of the Commons
The tragedy of the commons stems from the fact that no one wants to pay for a public good/project, even though many people end up benefiting from the public good or project. In quadratic voting, the influence of the average contributor increases. If a person has 10,000 units of money/Token, he can generate about 100 units of influence (votes) instead of 10,000 votes. And in quadratic funding, each person’s contribution gets the project more matching funds (n people’s funding leads to a quadratic order of magnitude of n matching funds).

What problems are not solved by quadratic voting and quadratic funding
Identity Bribery. If someone can create an infinite number of identities that can be voted on, then using these identities, one vote per identity can maximize influence. In the traditional world, forged identities and votes can enable this attack, and the usual way to resist it is to verify a unique ID (or signature). On the blockchain, this can be done by replicating multiple addresses, but note that this incurs significant processing fees and higher account management costs. In the worst case, quadratic voting is downgraded to “one dollar one vote”.

Collusion. If an attacker knows who has the votes, he can harvest the votes by getting many people to sell their votes (Ballot Harvesting has caused serious fraud in many countries). In the worst case, quadratic voting is once again downgraded to “one dollar a vote”. An on-chain solution to this problem is to make users completely anonymous when their identity can be verified, for example by using zero-knowledge proofs and some other cryptographic algorithms.

Rational Ignorance (RI). In a one-person-one-vote system, each person may choose not to contribute (or not to vote) because they consider that their actions contribute too little to the final outcome. This problem cannot be completely solved, but based on the discussion above, quadratic voting and quadratic funding clearly alleviate this problem to a large extent. As you can see, this problem is even more severe in large-scale public project voting/funding. In the blockchain world, many of the public projects we encounter are small to medium scale, so some of the problems described above become less severe, making quadratic funding more effective.

Currently, quadratic voting and quadratic funding are used in the Colorado State Legislature [2], GitCoin Grants, Pickle Finance, and the DoraHacks BSC Grant.

Posted by:CoinYuppie,Reprinted with attribution to:https://coinyuppie.com/a-look-at-radical-markets-and-quadratic-voting-regulating-markets-with-markets-themselves/
Coinyuppie is an open information publishing platform, all information provided is not related to the views and positions of coinyuppie, and does not constitute any investment and financial advice. Users are expected to carefully screen and prevent risks.

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