For future alpaca farmers, Sexton and Saitone laid out some of the major hallmarks of a speculative bubble, including: (1) The asset not the product is the thing being marketed (i.e. live alpacas, not fiber),Bitcoin cult members sell users the dream of egalitarian wealth, when in reality the math and code behind Bitcoin simply created a system where existing capital is proportionally transfered into Bitcoin during the temporary hyperinflationary phase at an accelerated rate based on how early one begins to to set up server farms. Early users spent measurably less capital to generate significantly more of the supply. The Bitcoin protocol and mining algorithm is not some fancy complex math (Bitcoin mining math amounts to a lottery system, more capital gives more lottery ticket printers). Mining boils down to wasting more work and energy for less output as time passes.
(2) investors have unrealistic expectations (alpaca fiber would replace wool, despite the lack of infrastructure; and besides the fact that people don’t really wear that much wool),Cryptocoins seek to turn money and now entire industries and services into speculative gift cards where the majorty of the supply is in the hands of a few "pre-sale ICO" kings and a few existing wealthy whales who have set up large warehouses in China, Washington, South East Asia, etc. Are we to expect the future robber barons who bought a bunch of gamer graphics cards to waste energy running this software deserve anything?
(3) information is controlled through industry sources (most of the information the researchers were able to dig up was put out by breeding associations),Even in the more reputable publications, journalists boil down the computer science into the marketing claims of what Blockchain and smart contracts cultist CLAIM it can do. These are solutions in search of problems.
(4) small scale investors predominate (Foster Farms did not open an alpaca plant).The cult of bagholders think they are the kings.
One important point: if we actually include all 7 billion people on the earth, most of whom have zero BTC or Ethereum, the Gini coefficient is essentially 0.99+. And if we just include all balances, we include many dust balances which would again put the Gini coefficient at 0.99+. Thus, we need some kind of threshold here. The imperfect threshold we picked was the Gini coefficient among accounts with ≥185 BTC per address, and ≥2477 ETH per address. So this is the distribution of ownership among the Bitcoin and Ethereum rich with $500k as of July 2017.https://medium.com/@balajis/quantifying-decentralization-e39db233c28e
In what kind of situation would a thresholded metric like this be interesting? Perhaps in a scenario similar to the ongoing IRS Coinbase issue, where the IRS is seeking information on all holders with balances >$20,000. Conceptualized in terms of an attack, a high Gini coefficient would mean that a government would only need to round up a few large holders in order to acquire a large percentage of outstanding cryptocurrency — and with it the ability to tank the price.
With that said, two points. First, while one would not want a Gini coefficient of exactly 1.0 for BTC or ETH (as then only one person would have all of the digital currency, and no one would have an incentive to help boost the network), in practice it appears that a very high level of wealth centralization is still compatible with the operation of a decentralized protocol. Second, as we show below, we think the Nakamoto coefficient is a better metric than the Gini coefficient for measuring holder concentration in particular as it obviates the issue of arbitrarily choosing a threshold.
...However, the maximum Gini coefficient has one obvious issue: while a high value tracks with our intuitive notion of a “more centralized” system, the fact that each Gini coefficient is restricted to a 0–1 scale means that it does not directly measure the number of individuals or entities required to compromise a system.
Specifically, for a given blockchain suppose you have a subsystem of exchanges with 1000 actors with a Gini coefficient of 0.8, and another subsystem of 10 miners with a Gini coefficient of 0.7. It may turn out that compromising only 3 miners rather than 57 exchanges may be sufficient to compromise this system, which would mean the maximum Gini coefficient would have pointed to exchanges rather than miners as the decentralization bottleneck.
Conversely, if one considers “number of distinct countries with substantial mining capacity” an essential subsystem, then the minimum Nakamoto coefficient for Bitcoin would again be 1, as the compromise of China (in the sense of a Chinese government crackdown on mining) would result in >51% of mining being compromised.
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