Economics, psychology and blockchain systems

Blockchain platforms are economic systems. And just like any economy, a blockchain requires that its designers define monetary policy (inflation), fiscal policy (block size), taxation (fees), voting (governance/upgrades), and provide for the common defence (securing the network). Yet, unlike traditional economies, they offer the possibility of greater freedom and transparency because they avoid the problems of centralisation and concentration of power.

So the blockchain is great for academic economists, because it is a kind of living economic laboratory. Economists have plenty of tools for designing such systems. Does it end there? No, because the blockchain does not evolve randomly but by attempts at designing new, and better, models for money, ownership, control, trade, lending, licensing, and investment. In other words, many of the key innovations of the blockchain are economic innovations, and that means we need economists to help design them.

The problem with traditional economics is that it has two major assumptions, based on which the entire economic system is built. First, it assumes humans are rational and always and consistently optimise their utility (happiness, satisfaction). Second, economic theory assumes that on macro economic level there is or tends to be an equilibrium or balance which economics systems need to attain. In other words, we assume wisdom of the crowds and efficient market hypothesis. But what if neither is true, at least some times?

Humans are irrational by design. Just look at some of the decisions each of us make on a daily basis. We may vote for policies that go against our own economic interests. We make food selections that are at odds with our physical health. So there’s no clear, codeable logic in much of our behaviour.

Blockchain systems are, by design, difficult to change once deployed. Repairs and improvements to these systems are difficult. Protocols with billion-dollar valuations could disappear overnight. Things can get very acrimonious. Check the infamous Bitcoin block size debate. And one of the most difficult aspects for blockchain platform creators is accurately predicting people’s behaviour. That would be a relatively easy task if humans had a consistency, rational behaviour or an overarching logic in how they go about their lives.

Good news is that there is an entire field studying this – human irrationality and how to incentivise humans – very phenomenon, including Nobel laureates Daniel Kahneman and Amos Tversky and former Clinton advisor Cass Sunstein, who discovered that changing the default setting from “opt-in” to “opt-out” on things such as organ donation on a driver’s license and 401k contributions at work could dramatically improve uptake. This seemingly little change tapped on our Default Bias, enabling individuals to adjust their contribution levels (to retirement), but even the flummoxed novice who did nothing is at least socking some money away for retirement and taking advantage of company matching payments.

It turns out that we have a huge number of cognitive biases and knowing these and knowing how to go around these or nudge or incentivise us to act in desired ways is the key to understanding and predicting human behaviour accurately. One of most commonly-observed cognitive biases is loss aversion. Loss aversion derives from our innate motive to prefer avoiding losses rather than achieving similar gains. Kahneman and Tversy conducted an experiment asking people if they would accept a bet based on the flip of a coin. If the coin came up tails the person would lose $100, and if it came up heads, they would win $200. The results of the experiment showed that on average people needed to gain about twice (1.5x – 2.5x) as much as they were willing to lose in order to proceed forward with the bet (meaning the potential gain must have been at least twice as much as the potential loss). However, from traditional economic theory perspective, one’s risk appetite to losing or gaining $100 is the same.

The most tangible of incentives on blockchain platforms are digital tokens. Tokens usually represent currency, digital asset or some form of value in given blockchain system. Getting incentives right is fundamental to network growth, reflected in increased token adoption that yields positive network effects. Once this flywheel gets started, it serves as the ongoing funding mechanism for future development. Without it, the network cannot achieve self-sustainability. The value of the community and the token is what incentivises new members to join initially. If that value is off, new people don’t join and a death spiral begins. Once members are in, there needs to be a sustainable and growing value in the system to keep them using the tokens, participating in the community and helping the system grow. While token was the allure, the incentive system needs to account for conflicting interests of different types of users, system changes and perceived value and expectations from the system and, most importantly, it cannot necessarily based on the value of token itself. There are a few systems that help evaluate blockchain projects, including T3CG framework which is pretty solid.

Cryptoeconomics is hard as it requires expertise and mastery of mechanism design, contract theory, game theory, behavioral economics, public policy, macro-economics, and a solid understanding of decentralized technology in order to the design robust, sustainable and valuable blockchain economies. Hence is boils down to designing  incentive systems based on known biases – default bias, endowment effectbandwagon effect, etc –  and other factors, including cultural values, public policies, system-specific goals.

I am very excited by potential of blockchain systems but also humbled by the realization that we have just scratched the surface on how to build optimal blockchain systems.

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