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Gini Coefficient Based Wealth Distribution in the Bitcoin Network: A Case Study

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Computing, Analytics and Networks (ICAN 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 805))

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Abstract

Bitcoin has gained widespread attention globally in 2013 and is the first online currency based on a peer to peer network without any central authority or third parties. Its market capitalization reached US$ 8.5 billion in December 2013. However, despite its popularity some issues like network security (thefts), anonymity (privacy) and wealth distribution (inequality) have plagued it. Of considerable importance is the last issue of unequal wealth distribution as it may create a huge socio-economic burden for the society. A group of researchers estimated that the GINI coefficient for the network was at an all time high of 0.985 in Jan 2013 and that the rich were getting richer as the network grew. In the present work it has been strived to determine how the GINI actually increases or decreased depending upon the wealth distribution. For doing this a raw transaction of data of more than 36 million transactions has been sourced and a list of all users and their wealth in the network has been computed. The final results are very alarming as GINI has increased to 0.997 by the end of 2013 and the market share of top 10 holders alone has reached 6.6% of the entire market. Therefore, the rich have actually got richer and steps should be taken to curb such a wealth accumulation model in the network.

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Correspondence to Manas Gupta .

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Gupta, M., Gupta, P. (2018). Gini Coefficient Based Wealth Distribution in the Bitcoin Network: A Case Study. In: Sharma, R., Mantri, A., Dua, S. (eds) Computing, Analytics and Networks. ICAN 2017. Communications in Computer and Information Science, vol 805. Springer, Singapore. https://doi.org/10.1007/978-981-13-0755-3_15

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  • DOI: https://doi.org/10.1007/978-981-13-0755-3_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0754-6

  • Online ISBN: 978-981-13-0755-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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