Monetary policy has long been a central topic in macroeconomics. With the rise of blockchain technology, it has also become an important topic for cryptocurrencies, which were originally created as an alternative to fiat currencies and reached a market valuation of 3.5 trillion in 2025. In the context of cryptocurrency markets, "monetary policy" refers to the rules and mechanisms used to manage the supply and circulation of tokens and plays a key role in determining their success and adoption. This thesis advances research on monetary policy in both traditional macroeconomics and the emerging field of cryptocurrency markets.

In the first chapter, (Un)conventional Monetary Policy for Debt Stability, co-authored with Luisa Lambertini and Stelios Tsiaras, we study the impact of different fiscal and monetary strategies on debt stability in the wake of a large increase in debt. We propose a macroeconomic policy under which debt stability is achieved by a Quantitative Easing (QE) rule that responds to changes in the government debt-to-GDP ratio. In a New Keynesian DSGE model with household heterogeneity, financial frictions, and nominal rigidities calibrated to the U.S. economy, we show that the QE profits earned from the bond-reserve spread and remitted to the treasury are a significant source of fiscal revenues. We compare two approaches to achieving debt stabilization: increasing taxes and implementing QE, and study the effectiveness of both tools under active and passive monetary policy frameworks. We find that the QE rule can stabilize debt even without an increase in taxes, and that its general equilibrium effects are less contractionary.

The second chapter, How Algorithmic Stablecoins Fail, co-authored with Natalia Rostova, focuses on studying the design flaws in the monetary policy of stablecoins. In particular, we analyze the collapse of the largest algorithmic stablecoin TerraUSD (UST) in May 2022, which had a market capitalization of $18.7 billion. The monetary policy of UST was designed to maintain a 1:1 peg with the US dollar without holding fiat reserves. Instead, it relied on a "mint-and-burn mechanism" involving another token LUNA. We collect transaction-level data from the Terra blockchain and cryptocurrency exchanges and show that several flaws in the design of UST's monetary policy impeded its ability to stabilize the price. We also propose a simple model that demonstrates how a combination of these design features helps explain the data patterns observed during the crash.

The third chapter, ICO Lockups As a Dynamic Commitment Device, studies the monetary policies of a broad set of tokens issued by blockchain-based projects in cryptocurrency markets. In particular, I focus on a common feature used by token issuers to restrict the circulating supply of tokens: so-called "Initial Coin Offering (ICO) lockups." These lockups are temporary restrictions on the sale of tokens by project insiders, similar to IPO lockups in traditional financial markets. The release of these tokens ("unlocks") typically occurs in several discrete events over time and is fully known in advance. I collect and analyze 872 token unlock events and document that: 1) even though token unlocks are anticipated, the token price declines, on average, by 2% around an unlock event, and 2) the price effect is stronger for the first unlock than for subsequent unlocks. I then present a signaling theory model that explains this price effect.