The Cryptonetwork-and-City Analytical Approach

Every week the Mosaic research team will delve into important topics within the cryptoasset space.

Jason Yannos and Eliézer Ndinga

Introduction

Identifying and understanding the key components and drivers needed to evaluate the sustainability of both cities and cryptonetworks is no easy task. While cities have had their data analyzed and mulled over for more than 100 years, cryptonetworks such as Bitcoin are still in their early days. Nonetheless, cities and decentralized networks share common traits, both are complex systems and when observed with an outsider’s eye, they seem messy.

This article is divided into two parts:

  • the first addresses and highlights the key value drivers of real estate and how they could potentially relate to cryptoassets
  • the second takes a comprehensive look at a wide range of well-tested indicators used to assess cities and how they could potentially translate into a cryptoasset valuation.

PART I — A Primer on Price Drivers

Across the globe in each country and city, real estate markets share four common fundamental drivers related to value:

  • Demographics
  • Government Policies
  • The Economy and Its Future Growth Prospects (or lack thereof)
  • Interest Rates

At the heart of these four drivers is the state of a market’s economy and its prospects for growth. A city’s economic growth fuels job opportunities — acting as a magnet to attract talent from all corners of the globe — and sparks excess demand for property above the average level of demand. Additionally, demographics contribute as a city must have an adequate working age populace relative to the proportion of those entering retirement phases. Entrepreneurial individuals seek accommodative policies from regulators to start enterprises and low interest lowers the cost of borrowing money which encourages businesses to increase expenditures on investments.

When we shift out of analyzing the fundamental drivers of property prices and zoom into the drivers of decentralized networks, an overlap clearly exists. While those developing cryptoasset valuation frameworks have yet to reach consensus on the key drivers of value, common factors exist between the two asset classes — real estate and cryptoassets — which are helpful to assess decentralized networks:

  • Community
  • Governance
  • Use Case and Total Addressable Market
  • Token Economics

Similar to the fundamental factors of real estate valuation, arguably one of the most important factors in decentralized networks today is the network’s potential for economic growth. For example, what is the use case of the network, alongside its Total Addressable Market (TAM), and is this network growing? Relative to a real-world economy, this would be an assessment of whether or not an economy is experiencing economic growth and the prospects for future growth.

Another leading factor for assessing a decentralized network is the network’s community which is similar to the demographic profiles and overall health of communities within cities from the microeconomic level. Flip through any decentralized network’s Telegram group, Twitter, GitHub, and Reddit and you’ll be able to gauge the general quality and sentiment of its community. The community of a network is the equivalent of a cities demographics. In the real world, the quality of a community in any city and the profile of its demographics play a major role in the price of properties as individuals naturally place a value on vibrant communities with low crime rates. In a distributed network, part of the value of the network is determined by the contribution and purpose of the community in various forms. Are these members looking to evangelize for a short period of time the network to proverbially “shill their bags” or are these members long term believers in the ethos of the network with the aim of helping it grow and succeed?

Accommodative policies from a government alongside low interest rates generally help boost the economic activity of a community in the real world which in turn, leads to appreciation in the value of real estate prices. Although governance and token economics of a decentralized network are not equal, they do share some overlapping traits with these two factors and do contribute to the value of a network. Is the governance of the network accommodative to the general populace of the network or is it restrictive and skewed to a selected few who hold more power? Inflation and deflation are common properties of most token economics; however, is the level of inflation or deflation within the network adequate incentivizing individuals to participate in the network or are they outrageous and present substantial risk over the medium and long term? Consideration of these factors when assessing a network is of paramount importance when determining the underlying value of the network today and its prospects for growth in the future.

PART II — A Comprehensive Dive into Key Indicators

As part of our analysis, we rely on city-specific indicators and define how these can be converted into the crypto world. In the table below we list major city-centric indicators, which enables us to compare and determine crypto-specific ones. We then categorize these latter indicators by data accessibility (high, medium, or low). Our approach in today’s article is to zero in on certain indicators that we at Mosaic consider of paramount importance. The fact that some are inconspicuous means that relevant data are either not easily accessible or quantifiable.

Note that all the listed indicators are correlated and provide a broad picture that helps us understand the different dynamics of a cryptonetwork. This list is non-exhaustive and is subject to customization for various use cases and is likely to change and update as the crypto industry matures.

Indicators

Source: How to Quantify A Successful City

Inconspicuous crypto indicators

The following indicators have LOW accessibility.

  • Unemployment Rate

In cryptonetworks, we define the Unemployment Rate as the number of qualified contributors to determine the magnitude of potentially unqualified ones. While there is currently a limited number of blockchain developers there is an increasing demand due to the proliferation of crypto projects. Potentially this results in a high employment rate for qualified blockchain developers but it is difficult to say what the “unemployment rate” for non-blockchain developers is or the effect this has on delayed development and growth in the industry.

  • Labor Export and Brain Drain

One way to measure a city’s economic vitality and strength is by determining Labor Export and Brain Drain. While the former indicates the number of jobs exported for cheap labor, the latter constitutes the quantity of educated and talented individuals seeking better economic opportunities elsewhere. However, such instance is nuanced in the open source world of cryptonetworks where one can voluntarily contribute to building any network. We believe such an indicator would be analogous to:

  • Developers fleeing one cryptonetwork for another due to a loss of faith in the utility of a network and its underlying token.
  • Miners running away from securing the network due to a decreasing return on investment (ROI).
  • Full nodes overwhelmed with growing and expensive storage requirements.
  • School Quality and Access to Health Care

Health and education are crucial elements that solidify the sustainability of a city over time. Similarly, a healthy cryptonetwork provides transparent information and simplifies the user and developer experience with a coherent developer toolkit and an ease of access to education for its community. These elements are driven by the community itself and undoubtedly lead to a greater developer and user adoption.

  • City Loyalty

What City Loyalty is to cities, Protocol Loyalty is to cryptonetworks. This indicator is difficult to quantify but can be observed through actions such as network initiatives, contributions, and the quality of community engagement. Fervent network contributors and users are the backbone of a cryptonetwork and will safeguard the network against all odds. Analogous to cities in the real world, impact indicators like School Quality and Access to Health Care, Innovation Rates, Wage Growth, and Job Growth are all first order proxies to the economic and social health of a population within a city at the micro level.

  • Friendliness, Tolerance, and Inclusion

The tolerance and inclusion of new members and people’s perception of a crypto community, are factors which also affect adoption. Although difficult to quantify, it seems reasonable to say that a welcoming and supportive community will help the network thrive and avoid the creation of ghetto-esque sub-communities that could reject different viewpoints.

Other indicators

The following indicators have MEDIUM accessibility.

  • Inequality levels

Inequality in cities can be translated through the disparity in Wealth Distribution. Similarly, in a cryptonetwork, the distribution of a native coin or token represents its wealth distribution. In the crypto world, depending on the Sybil-resistance method, be it Proof of Work (PoW), Proof of Stake (PoS) or Delegated Proof of Stake (DPoS), the state of the network can be impacted in many ways.

  • PoW-based networks: The richest stakeholders can influence the state of the network through computational power by purchasing the most efficient and expensive mining-specific machines (ASICs). Similarly, the richest citizens of a city can also influence the dynamics of a city through various forms of investment.
  • PoS and DPoS-based networks aka Minority Rule: The richest holders have more influence and power over the governance of the network than poorer actors, which could potentially create oligarchies like those that exist in Russia.

The network structure and future is dependent on the formation of the Sybil-resistance methods, and understanding their potential implications is of importance.

Moreover, when observing the distribution of a network’s currency, one must take into consideration the number of coins allowed and potentially traded in the open market. In an oligopoly, if a concentrated number of wealthy market participants dump the native currency, a major collapse in the price could occur and therefore result in fear and uncertainty.

  • Population Growth Rate

While measuring the population density of a city is fairly simple thanks to registration offices, assessing the user base of a crypto network is a challenging endeavour. The users of cryptonetworks interact with generated cryptographic addresses. To preserve privacy, each time a transaction is about to occur, the common practice is to generate a new address. Hence, observers might think that there are hundreds of thousands of users at any given time, whereas there could be just a few hundred. Determining the number of a network’s unique addresses is a major issue and requires both accurate heuristics and great effort to come up with real estimations.

  • Corruption Levels & Violent Crime Rates

The Corruption Perception Index (CPI) is only assessed for countries rather than cities. The index measures the corruption level through freedom of speech, independent media and whether a given country encourages an open and engaged civil society. However, in the crypto world, this can be measured by the cost of executing a 51 percent attack.

  • 51-percent attacks:

Malicious actors control over 51 percent of the hash power of a network and can deny certain transactions (ie, lack of freedom of speech) and enrich themselves by double spending their own coins. The cost of a 51-percent attack — the rental cost for an hour to get enough hashing power, is crucial to know as it determines the likelihood for such events to occur. In other words, the higher the cost, the less likely such attack could happen.

The following indicators have HIGH accessibility.

  • Philosophical Ideologies & City Copycats

On the one hand, the number of forks or splits in a cryptonetwork can be referred to as the divide between philosophical ideologies in a city. If the tolerance level of differing views is minimal, the community is essentially divided and thus fragile.

On the other hand, in the open source world, forks also indicate that new cryptonetworks copy the model of an original network. This phenomenon already exists with cities that aspire to become the next Silicon Valley, and can be seen with cryptonetworks that aim to become the better Bitcoin such as Dash.

  • Affordability

The less affordable a network is, the more likely it will become centralized, due to the high barrier to entry for network contributors such as miners and full nodes. This results in the rise of Bitcoin mining pools and masternodes pools in the Dash network.

This phenomenon is similar to high-cost-of-living cities such as New York City, London, and Tokyo. Analogous to Bitcoin mining pools, in expensive cities, there is a proliferation of shared apartments as it becomes unaffordable for many young workers to rent even a small apartment on their own.

Conclusion

As a new phenomenon that is nuanced and multi-faceted, the challenge lies in the definition of cryptonetworks before engaging in mathematical formulas for valuation purposes. However, these heuristics have helped us identify the most obvious definition of cryptonetworks, which have been mistakenly referred to as ‘firms’ and even ‘coral reefs’. In fact, with the conversion of city indicators into cryptonework indicators, we have illustrated the similarities of both cities and cryptonetworks and created an analytical methodology which we hope will help the community observe and evaluate crypto projects in the future.

End of weekly research report

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This article is intended for informational purposes only. The views expressed herein are not and should not be construed as legal or investment advice or recommendations. Recipients of this article should do their own due diligence, considering their specific financial circumstances, investment objectives, and risk tolerance before investing. The individuals contributing to this article have positions in some or all of the assets discussed. This article is neither an offer, nor the solicitation of an offer, to buy or sell any of the assets mentioned herein.