New Evidence on Convenient Asset Demand (Job Market Paper): SSRN
Investors appear to value the extra-pecuniary benefits of certain convenient assets, which causes those assets to enjoy yields below those of less convenient benchmarks. This yield spread is the convenience yield. I empirically estimate the slope of the aggregate demand curve for short-term assets that provide these convenience services, by studying how this convenience yield varies in response to week-to-week variation in the outstanding supply of Treasury bills. Using high frequency projections of T-bill issuance quantities from Wrightson, a highly informed market newsletter, I construct a direct measure of the surprise component in T-bill auction sizes. I argue that these issuance surprises are plausibly uncorrelated with changes in convenience demand, and are a methodological improvement over the literature's standard approach of using seasonality as an instrument for convenient asset quantities. Using local projection methods and this measure of surprises as an instrument, I find that the demand curve for short-term convenient assets is meaningfully steep only in the very short-run. A $100bn 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 $100bn higher stock of T-bills only depressing convenience yields by 1.13 basis points. These estimates have implications for the quantitative implications of macroeconomic models featuring convenience yields for which the slope of this demand curve is a parameter input -- such as the R<G fiscal sustainability literature.
Money Fund Demand and Regulatory Reform (with Abhi Gupta), available as Chapter 3 of my dissertation: Link
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.
Empirical Network Contagion for U.S. Financial Institutions (with Fernando Duarte): Link
We construct an empirical measure of expected network spillovers that arise through default cascades for the U.S. financial system for the period 2002-16. Compared to existing studies, we include a much larger cross section of U.S. financial firms that comprises 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 percent, a significantly higher estimate than previously found in the literature.