Crypto-Microeconomics: The Distribution of Bitcoin Wealth Among Diverse Economic Agents
For researchers and policymakers studying cryptocurrency inequality, this provides a micro-level framework confirming persistent wealth concentration, though it is an incremental application of existing metrics to a new dataset.
This paper proposes a 'Crypto-Microeconomic Observability Framework' to analyze Bitcoin wealth distribution across five agent classes, finding that wealth is highly concentrated with Service entities holding 75.15% of observed BTC and near-maximal within-class inequality (e.g., Gini = 0.9993 for Individuals).
Bitcoin (BTC) wealth distribution is often studied with macro indicators like wallet balances, prices, network activity, fees, and hashrate. This letter proposes a "Crypto-Microeconomic Observability Framework" to examine micro-level Bitcoin wealth disparities across five labeled agent classes: Service, Abuse, Malware, Individuals, and Benign. Using descriptive, inequality, and longitudinal concentration metrics, we show that Bitcoin wealth is highly concentrated across major classes, consistent with a persistent "Whale-Effect". Service entities hold the largest share of observed BTC (75.15%), while Abuse controls a disproportionately large share relative to its entity count (24.26% of BTC vs. 3.53% of entities). Individuals, Abuse, and Service show near-maximal within-class inequality (e.g., Gini = 0.9993 for Individuals), and time-series analysis indicates these patterns persist. Overall, Bitcoin wealth among labeled economic agents remains structurally uneven and concentrated in a small subset of entities.