The Distribution of IOTA Tokens

Ingo Fiedler
4 min readMar 7, 2017

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In the last post I carved out the essential properties of a token-based machine economy — scalability, zero transaction costs, and offline transactions — and argued that IOTA is currently the only protocol that meets all of these requirements. Meeting the demand of zero transaction costs comes with the necessity of providing a “premined” token, where a part or, in this case, all tokens that will ever be available, already exist. Having shown that this does not imply an insecure network — since validation of transactions is not based on a mining process — there is still the concern that premined tokens foster an unfair distribution of tokens, especially when the developers of the protocol hold a large part and consequently could dominate the network. In this post I will present the actual distribution of IOTA tokens across addresses by investigating the two latest snapshots of the network.

In total, 2,779,530,283,277,761 Iota or roughly 2,800,000 Gigaiota (Gi) exist. On November 27th around 48% of all Iota were claimed by their owners. Until the 4th of February, additional 12% of Iota were claimed for a total of 60%. The number of addresses with a positive balance increased from 472 to 657 (+39%) and the number of addresses with more than 1 Gi (around $9 at current market price) increased from 334 to 494 (+48%). It can be seen that the increase in addresses is lower for high-value addresses (+23% for addresses holding >10,000 Gi and +36% for addresses >1,000 Gi), suggesting that new addresses are less often whales compared to old addresses. The largest address in both snapshots is the same with 86,046 Gi and the four largest addresses did actually not change between or during the snapshots.

These statistics suggest that the concentration of wealth among the largest addresses has decreased over time. And indeed, the amount of claimed tokens held by the ten largest addresses decreased from 34.92% to 29.22%. The GINI-coefficient as a measure of concentration of wealth, however, stayed rather flat at around 82%.

The GINI-coefficient of 82% seems rather high when compared to the GINI coefficient of global income, which globally lies at 65% across the year 2013. However, although the GINI coefficient is most often used in the realm of income analysis, it cannot be compared to a GINI of wealth. Hence, the Iota wealth GINI needs to be compared to the GINI of global wealth, which lies at 91.5% in 2015 or 89.2% in 2000. This suggests that the Iota wealth distribution is less concentrated than the wealth distribution of our global society. Another tweak would be to account for the purchase power of wealth and compare the GINI of Iota to the GINI of Purchasing Power Parity (PPP) wealth, which was at 80.4% in 2008 and thus very close to the GINI of Iota.

Granted, one user can own multiple addresses and thus the concentration of wealth among addresses is not the same as the concentration of wealth among users. However, since there is no way of knowing the individuals behind the addresses, there is no way to address this issue. Instead, it might be helpful to compare the concentration of IOTA tokens with the concentration of a different virtual token: Bitcoin. The GINI coefficient of wealth in the Bitcoin network is much higher than in the IOTA network and lies at an astonishing 99%. Some part of this concentration might come from cold wallet addresses managed by large exchanges where the respective bitcoins belong to many users. However, additional analyses show that this effect is rather small and can be neglected.

It can thus be concluded that the tokens in the IOTA network are distributed rather equally, at least from the risk perspective of the network being hijacked by one or a group of large whales. In addition, it should be noted that the developers hold their Iota in a foundation and these account for only around 5% of all available tokens. Combined with the non-profit nature of a foundation this leads to the conclusion that IOTA is certainly not a “get-rich-quick-attempt” of the developers.

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This blog post is part of a series on IOTA consisting of three articles:

1. Properties of a Token-Based Machine Economy

2. The Distribution of IOTA Tokens

3. Optimal Inflation Rate in a Machine-Based Economy

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Ingo Fiedler

Blockchain Research Lab, University of Hamburg, Concordia University