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Financial Markets

Cryptocurrencies: Welfare Gains vs Escalating Systemic Risks

Posted by e-axes on May 7, 2025

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Cryptocurrencies as economic buffers

B. Biais, J.C. Rochet, and S. Villeneuve develop a continuous-time, general equilibrium model where agents can invest in productive assets and either government-issued fiat money or cryptocurrency. The government funds public spending through seigniorage (money creation) and wealth taxes, and may act in a non-benevolent (self-interested) manner. The model allows for the possibility of hyperinflation and incorporates the risk that cryptocurrencies can crash (due to sunspots or technological failures). Agents decide how to allocate their wealth to buffer productivity shocks and maximize utility, while the government chooses monetary and fiscal policies.

Findings:

  • In well-functioning economies with benevolent governments, cryptocurrencies have little impact because agents prefer stable fiat money.
  • In countries with non-benevolent governments prone to excessive money creation and hyperinflation, the presence of cryptocurrencies disciplines government policy: If the government inflates too much, agents switch to cryptocurrencies, limiting the government’s ability to extract rents through inflation.  This competition caps inflation and increases agents’ welfare compared to a scenario without crypto.
  • The disciplining effect of crypto is stronger when the risk of a cryptocurrency crash is low; if crypto is very risky, it constrains government policy less.
  • The model helps explain why crypto adoption is high in countries with unstable currencies and high inflation, and why some governments oppose cryptocurrencies.
  • Overall, cryptocurrencies can serve as a “lifeline” in dysfunctional economies by providing an alternative store of value and limiting the government’s ability to pursue predatory monetary policies.

Do cryptocurrencies matter?
Authors: B. Biais (HEC), J.C. Rochet (TSE), S. Villeneuve (TSE)
From: HEC Paris Business School, Toulouse School of Economics

Bitcoin’s cross-border dynamics

Eugenio M Cerutti, Jiaqian Chen, and Martina Hengge investigate how Bitcoin is used for cross-border transactions, using global data from both on-chain (blockchain-based) and off-chain (exchange-based, e.g., LocalBitcoins) transactions.

Key findings

Geographical and transactional patterns:

  • Bitcoin is used for cross-border transactions worldwide, with high intensities in regions such as Latin America, Africa, Asia, and Eastern Europe.
  • On-chain transactions are, on average, much larger than off-chain transactions (e.g., average on-chain transaction ≈ 13.3 BTC vs. off-chain ≈ 0.018 BTC), reflecting different user groups and purposes.
  • Bitcoin cross-border flows can be sizable relative to GDP in some countries, especially where traditional capital flows are small.

Drivers of bitcoin vs. capital flows:

  • On-chain flows (Chainalysis): Respond differently to traditional capital flow drivers compared to conventional capital flows. For example, on-chain flows increase with global risk aversion (VIX), whereas traditional capital inflows decrease.
  • Off-chain flows (LocalBitcoins): Show little sensitivity to global risk or dollar strength but are positively related to domestic factors like high interest differentials and the Bitcoin parallel rate premium-a proxy for exchange rate pressure and capital controls.
  • Capital flows (EPFR/IIF): Decline with higher global risk aversion and a stronger US dollar, consistent with established literature.

Policy implications:

  • Bitcoin cross-border flows have not replaced traditional capital flows but may facilitate circumvention of capital controls, especially via off-chain P2P markets.
  • Cerutti et al. emphasize the systemic risks from crypto’s ties to traditional finance, advocating strict regulations. This conflicts with the paper by Biais et al.’s welfare gains, highlighting a tension between theoretical benefits and policymakers’ stability concerns.




A Primer on Bitcoin Cross-Border Flows: Measurement and Drivers
Authors: Eugenio M Cerutti, Jiaqian Chen, Martina Hengge
From: IMF

 

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