Digital Currencies
Paper Session
Saturday, Jan. 4, 2025 8:00 AM - 10:00 AM (PST)
- Jesus Fernandez-Villaverde, University of Pennsylvania
A Macroeconomic Model of Central Bank Digital Currency
Abstract
We develop a quantitative New Keynesian DSGE model to study the introduction of a central bank digital currency (CBDC): government-backed digital money available to retail consumers. At the heart of our model are monopolistic banks with market power in deposit and loan markets. When a CBDC is introduced, households benefit from an expansion of liquidity services and higher deposit rates as bank deposit market power is curtailed. However, deposits also flow out of the banking system and bank lending contracts. We assess this welfare trade-off for a wide range of economies that differ in their level of interest rates. We find substantial welfare gains from introducing a CBDC with an optimal interest rate that can be approximated by a simple rule of thumb: the maximum between 0% and the policy rate minus 1%.Token-Based Platform Governance
Abstract
We develop a model to compare the governance of traditional shareholder-owned platforms to that of platforms that issue tokens. A traditional shareholder governance structure leads a platform to extract rents from its users. A platform that issues tokens for its services can mitigate this rent extraction, as rent extraction lowers the platform owners’ token seigniorage revenues. However, this mitigation from issuing “service tokens” is effective only if the platform can commit itself not to dilute the “service token” subsequently. Issuing “hybrid tokens” that bundle claims on the platform’s services and its profits enhances efficiency even absent ex-ante commitment power. Finally, giving users the right to vote on platform policies, by contrast, redistributes surplus but does not necessarily enhance efficiency.Optimal Data Security with Redundancies
Abstract
We provide an economic analysis of how the observation of data by multiple parties (redundancies)affect private and socially optimal investment in data security. Our use case is the current banking system where payment transaction data is observed by at least the sending and the receiving institution. Redundancies cause free-riding, and under investment relative to the social optimum which increases the chance of cyber attacks. We show that an optimally protected third party, e.g. a regulator that observes all payment data, can increase overall data security beyond the level provided by the social planner even though all private entities shirk upon its entry. This holds because the information environment that results from providing a third redundancy is inherently different than the information environment the social planner is faced with.
Discussant(s)
Berardino Palazzo
,
Federal Reserve Board
Michael Kumhof
,
Bank of England
Ming Yang
,
University College London
Jacob Leshno
,
University of Chicago
JEL Classifications
- G0 - General