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A Federal Reserve Bank of Cleveland working paper <a href="https://www.clevelandfed.org/publications/working-paper/2026/wp-2616-cryptocurrencies-in-household-finance?utm_source=chatgpt.com” rel=”nofollow noopener” target=”_blank”>noted, on July 14, 2026, that <a href="https://xpertsstudio.com/bitcoin-etfs-see-biggest-weekly-inflow-in-10-months-during-rally/” title=”Bitcoin ETFs see biggest weekly inflow in 10 months during rally”>Bitcoin’s history acts as a guide for how much cryptocurrency Americans want to hold or buy.
Economists Michael Weber, Bernardo Candia, Olivier Coibion and Yuriy Gorodnichenko analyzed multiple cross-sections of household-survey data in the U.S., with a randomized information experiment in the second quarter of 2025, and an interview sample size per wave of 15,000 to 25,000.
Households who were exposed to the trailing 12-month Bitcoin return increased their target cryptocurrency allocation by two percentage points — approximately a 47% increase over the control group’s mean target allocation of 4.3%. Households exposed to the trailing Bitcoin return were more likely to purchase cryptocurrency in a later wave of the survey by a margin of 2.5 percentage points.
In 2021, the average return expected one year later from owners was 22%, and was lower for nonowners at 7%, but in 2025 these rates retreated somewhat from 22% and 7%, respectively. Owners sought 13.8%; nonowners expected 4.7%.
Expected returns were also correlated with ownership, as each percentage point increase in expected return corresponded to an increase of 0.8 percentage points in the probability of holding cryptocurrency. The randomized experiment lends support to causation.
In that experiment, participants got either information on Bitcoin, the S&P 500, GameStop or inflation. Bitcoin treatments included information on Bitcoin’s 14.3% previous-year return or a price chart. Both raised desired crypto allocations (partly on account of reduced cash, checking, and savings account allocations), and both raised desired stock allocations.
Subsequent responses suggest that the treatment raises the probability of buying crypto by 2.5 percentage points. Given that before the treatment, about 11% of subjects bought crypto, Bitcoin information treatment increased the unconditional probability of buying crypto by around 23%. The strongest responses were among nonowners who knew little about crypto.
The authors state that the evidence supports a feedback mechanism in which returns on Bitcoin price in the past attract more market participants, a potential bubble mechanism, without claiming that all Bitcoin price increase periods are followed by a self-perpetuating price increase.
The paper also considered the effect of Bitcoin gains on household consumption of durable goods such as computers and refrigerators, where households are highly exposed to Bitcoin and show little change in the consumption of nondurables.
Since this research is preliminary, the opinions expressed above are those of the authors and do not necessarily reflect the position of the Cleveland Fed or the Federal Reserve System.
Source: bitcoinfoundation.org