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Frameworks

Economist, scientific Director of the graduate FINTECH, Director of research Thalamus Lab, Ranepa
Chapter 6. Optics for blockchains and DLTs
Alexander Didenko
Blockchain for Startups
Cryptoeconomic systems could be analyzed from various points of view. In this last longread of the course I present three of them: complexity theory, institutionalism, and tokenomics.

Complexity theory

Making a long story short, complex system is a system, which can be described by a relatively small number of variables, as compared to a variety of behaviors and phenomena it can generate. Examples of such complex systems "primitives" are Lorence attractor and prey-predator system (described by Lottke-Volterra equations).
Many interesting open access agent-based systems are shared here, here, and here. Rosa et al. (2019), Poir et al. (2019), Kaligotla and Macal (2018), and many others explore various aspects of agent-based modeling of blockchains systems. The advantages of agent-based modeling in developing tokenomics (we will discuss this term later in this long read) are described here. Details on the ODD protocol could be taken from Grimm et al. (2006).
The most abundant part of peer-reviewed literature on complex systems issues in blockchains is dedicated to the chaotic behavior of cryptocurrency prices. Adjepong and Alagidede (2020) is the latest example of such a paper with a good literature review of its predecessors. Ben Davenport, blockchain startup founder, and technology investor describes in his blog a positive feedback loop, leading to Bitcoin's price growth. Another non-linearity horror story here is bitcoin's death spiral, although many stipulate that it is a hoax scenario. Some apply the concept of emergent phenomenons to the Bitcoin network to speculate about further developments of the Bitcoin consensus mechanism. Complex systems are interconnected, i.e., they can change the state of each other. In this respect De Domenico and Baronchelli (2019) review the case of Ethereum's flash-crash which happened on the 21st June 2017 and come to conclusions, that blockchain systems should be regarded not as isolated technical systems, but as parts of more complex broader "interconnected socio-technical systems". Spontaneous social coordination on micro-level in such systems may lead to a catastrophic cascade of events affecting both blockchain and surrounding systems. They coin the term “emergent centralization" to describe and explain the flash crash. Another — this time macro-level — take on complexity theory issues in the blockchain field is offered in this article on JPM coin. Authors argue, that major obstacle for blockchains to "topple Wall Street" is path-dependence — another property of complex systems. They write "decentralized, an open financial system based on something like Bitcoin may be superior along many lines to today's system, brokered by big financial intermediaries. Many of us might choose it over the status quo". This echoes the topic of our next video on institutionalism in blockchains.

Optics for institutionalism

Blockchain institutions could be regarded as moving equilibriums in social meta-games, but in itself it is rules of the game as well. Kroll et al. (2013) and Davidson et al. (2018) are absolute must-reads to gain an institutional framework for blockchains. From a practical point of view, these two texts offer a great introduction to the blockchain community building.

Tokenomics

Behavioral economy

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