Abstract: The canonical mechanism for financial asset exchange is the limit-order book. In decentralized blockchain ledgers (DeFi), costs and delays in appending new blocks to the ledger render a limit-order book impractical. Instead, a ``pricing curve'' is specified (e.g., the "constant product pricing function") and implemented using smart contracts deployed to the ledger. We develop a framework to study the equilibrium properties of such markets. Our framework provides new insights into how informational frictions distort liquidity provision in DeFi markets.
Abstract: We quantify the extent of crypto tax noncompliance and evasion, and assess the
efficacy of alternative tax enforcement interventions. The context of the study is
Norway. This context allows us to address key measurement challenges by combining de-anonymized crypto trading data with individual tax returns, survey data, and information from tax enforcement interventions. We find that crypto tax noncompliance is pervasive, even among investors trading on exchanges that share
identifiable trading data with tax authorities. However, since most crypto investors
owe little in crypto-related taxes, enforcement strategies need to be well-targeted
or cheap for benefits to outweigh costs.
Abstract: We study lending in decentralized finance facilitated by a programmable interest rate rule set by a Protocol for Loanable Funds (PLF). PLFs suffer a disadvantage when compared to traditional lending platforms, given their inability to incorporate off-chain information into the borrowing and lending rates that they set. For this reason, for a pre-determined PLF interest rate function, the DeFi equilibrium is sub-optimal when compared to a competitive lending market equilibrium. We nonetheless show that an optimally designed PLF interest rate function is able to generate equilibrium interest rates, and therefore welfare, that is arbitrarily close to a competitive lending market equilibrium when there are no frictions in the DeFi lending market.
Discussant: Joseph Abadi, Federal Reserve Bank of Philadelphia
Abstract: Blockchain-based platforms and DeFi prominently feature ``staking'': Besides offering transaction convenience, tokens are staked for generating consensus or incentivizing network activities and development, and consequently earn stakers rewards. To understand the economics of staking, token pricing, and network evolution, we model a continuous-time economy where agents heterogeneous in wealth and preference for a digital platform dynamically allocate their wealth among consumption, onchain transaction, and staking. We cast the interactions as a mean-field game with individual stochastic control and systematic shocks, and underscore aggregate staking ratio as a key variable linking staking to equilibrium reward rate and token price. We further characterize using the master equation the expected steady state of wealth and staking, and the redistribution due to staking and aggregate shocks. Long-run wealth distribution (onchain or offchain) is Pareto-like and increasing wealth concentration accompanies platform growth and welfare improvements. From a comprehensive dataset covering all major stakable tokens, we derive empirical findings corroborating the model predictions: staking ratio is positively correlated with reward rates in the cross-section and negatively correlated in the time series. Higher reward rates and wealth concentration attract greater future staking, increasing the aggregate staking ratio, which in turn positively predicts token excess returns. Finally, consumption and transaction conveniences explain the violations of uncovered interest rate parity and crypto carry premia (e.g., a long-short portfolio with OOS Sharpe ratio of 1.6) in the data.
