In chapter one, New Evidence on Convenient Asset Demand, I study aggregate demand for short-term convenient assets. I estimate the slope of the aggregate demand curve for these assets, which governs how a given change in convenient assets outstanding changes their convenience yield. I innovate relative to the existing literature by using a new instrument, which is a direct measure of T-bill issuance surprises relative to the projections of a well-informed market newsletter, Wrightson ICAP. I argue that Wrightson surprises are plausibly uncorrelated with changes in convenience demand, and are a methodological improvement over the literature's previous approaches. Using local projection methods, I find that the demand curve for short-term convenient assets is meaningfully steep only in the very short-run. A $100 billion increase in the supply of T-bills depresses T-bill convenience yields by 10.4 basis points, on average, in the week of the increase. However, the long-run effect is much more modest, with a $100 billion higher stock of T-bills only depressing convenience yields by 1.1 basis points.

In chapter two, Empirical Network Contagion for US Financial Institutions, coauthored with Fernando Duarte, we construct an empirical measure of expected network spillovers that arise through default cascades for the US financial system for the period 2002-2016. Compared to existing studies, we include a much larger cross-section of US financial firms that comprise all bank holding companies, all broker-dealers and all insurance companies, and consider their entire empirical balance sheet exposures instead of relying on simulations or on exposures arising just through one specific market (like the Fed Funds market) or one specific financial instrument (like credit default swaps). We find negligible expected spillovers from 2002 to 2007 and from 2013 to 2016. However, between 2008 and 2012, we find that default spillovers can amplify expected losses by up to 25\%, a significantly higher estimate than previously found in the literature.

In chapter three, Money Fund Demand and Regulatory Reform, coauthored with Abhi Gupta, we introduce an empirical framework for estimating a complete asset demand system in US money markets. The novel approach uses end-of-quarter window dressing by certain financial firms as a supply shock, to estimate the yield sensitivity of different money market investors. This framework can be used to investor-level demand parameters and compute pricing counterfactuals, to ask whether post-2016 regulatory reforms have led to more or less elastic market demand. Our framework is specially catered to be feasible to estimate with existing data on US money markets.