Welcome to the personal webpage of Fernando Duarte,
Economist at the Federal Reserve Bank of New York
Economist at the Federal Reserve Bank of New York
- How to Escape a Liquidity Trap with Interest Rate Rules
I study how central banks should communicate monetary policy in liquidity trap scenarios in which the zero lower bound on nominal interest rates is binding. Using a standard New Keynesian model, I argue that the key to preventing self-fulfilling deflationary spirals and anchoring expectations is to promise to keep nominal interest rates pegged at zero for a length of time that depends on the state of the economy. I derive necessary and sufficient conditions for this type of state contingent forward guidance to implement the welfare maximizing equilibrium as a globally determinate (i.e., unique) equilibrium. Even though the zero lower bound prevents the Taylor principle from holding, determinacy can be obtained if the central bank sufficiently extends the duration of the zero interest rate peg in response to deflationary or contractionary changes in expectations or outcomes. Fiscal policy is passive, so it plays no role for determinacy. The interest rate rules I consider are easy to communicate, require little institutional change and do not entail any unnecessary social welfare losses.
- Fire-Sale Spillovers and Systemic Risk
with Thomas Eisenbach. June, 2018.
We reveal and track over time the factors that make the financial system vulnerable to fire sales by constructing an index of aggregate vulnerability. The index starts increasing in 2004, before any other major systemic risk measure, more than doubling by 2008. The fire-sale specific factors of delevering speed and concentration of illiquid assets account for the majority of this increase. Individual banks' contributions to aggregate vulnerability are an excellent five-year-ahead predictor of SRISK. Had they been available at the time, these balance sheet-based measures would have been a useful early indicator of when and where vulnerabilities were building up.
- Empirical Network Contagion for U.S. Financial Institutions
with Collin Jones. November, 2017.
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.
- Financial Vulnerability and Monetary Policy
with Tobias Adrian. September, 2017.
We present a microfounded New Keynesian model that features financial vulnerabilities. Financial intermediaries' occasionally binding value at risk constraints give rise to vulnerabilities that generate time varying downside risk of the output gap. Monetary policy impacts the output gap directly via the IS curve, and indirectly via its impact on the tightness of the value at risk constraint. The optimal monetary policy rule always depends on nancial vulnerabilities in addition to output, inflation, and the real rate. We show that a classic Taylor rule exacerbates downside risk of GDP growth relative to an optimal Taylor rule, thus generating welfare losses associated with negative skewness of GDP growth.
- Institutional Investors' Intrinsic Trading Frequency and the Cross-Section of Stock Returns
with Sahar Parsa. May, 2013.
We show a novel relation between the institutional investors’ intrinsic trading frequency—a commonly used proxy for the investors’s investment horizon— and the cross-section of stock returns. We show that the 20% of stocks with the lowest trading frequency earn mean returns that are 6 percentage points per year higher than the 20% of stocks that have the highest trading frequency. The magnitude and predictability of these returns persist or even increase when risk-adjusted by common indicators of systematic risks such as the Fama-French, liquidity or momentum factors. Our results show that the characteristics of stock holders affect expected returns of the very securities they hold, supporting the view that heterogeneity among investors is an important dimension of asset prices.
- Cross-sectional inflation risk in menu cost models with heterogeneous firms
with Jonas Mishara-Blomberger. December, 2012.
We show that firms in models with menu costs, when calibrated to have the empirically observed frequency and size of individual-goods price adjustments, have stock returns that are always positively correlated with inflation. The cross-sectional dispersion in this correlation is almost negligible, even though firms have very diverse micro-level pricing behavior. Because in this class of models positive nominal shocks are good states of nature and the correlation between stock returns and inflation is positive, agents are willing to pay a premium to hold assets whose returns covary negatively with inflation. In contrast, we empirically find that the dispersion in the correlation between stock returns and inflation is about 100 times larger than in the model, and that correlations are negative about half the time. Furthermore, and also at odds with sticky-price models, investors require a premium to hedge against states of high inflation. Because firms’ heterogeneity is the key mechanism that generates a high degree of monetary non-neutrality in the models, our results suggest that we do not yet have a full account of the monetary transmission mechanism, and that asset prices can provide important information about it.
- Aggregate Investment and Stock Returns
with Leonid Kogan and Dmitry Livdan. April, 2012.
In this paper we study the relation between returns on the aggregate stock market and ggregate real investment. While it is well known that the aggregate investment rate is negatively correlated with subsequent excess stock market returns, we find that it is positively correlated with future stock market volatility. Thus, conditionally on past aggregate investment, the mean-variance tradeoff in aggregate stock returns is negative. We interpret these patterns within a general equilibrium production economy. In our model, investment is determined endogenously in response to two types of shocks: shocks to productivity and preference shocks affecting discount rates. Preference shocks affect expected stock returns, aggregate investment rate, and stock return volatility in equilibrium, helping model reproduce the empirical relations between these variables. Thus, our results emphasize that the time-varying price of aggregate risk plays and important role in shaping the aggregate investment dynamics.
- Comment on "Forward Guidance: Communication, Commitment, or Both?" by Marco Bassetto (Ungated version)
Journal of Monetary Economics, Volume 108, December 2019
- Time-Varying Inflation Risk and the Cross Section of Stock Returns
with Martijn Boons, Frans de Roon, and Marta Szymanowska. April, 2019.
Journal of Financial Economics, forthcoming
We show that inflation risk is priced in stock returns and that inflation risk premia in the cross-section and the aggregate market vary over time, even changing sign as in the early 2000s. This time variation is due to both price and quantities of inflation risk changing over time. Using a consumption-based asset pricing model, we argue that inflation risk is priced because inflation predicts real consumption growth. The historical changes in this predictability and in stocks' inflation betas can account for the size, variability, predictability and sign reversals in inflation risk premia.
- Monetary Policy and Financial Conditions: A Cross-Country Study
with Tobias Adrian, Federico Grinberg and Tommaso Mancini-Griffoli.
Chapter 7, Advancing the Frontiers of Monetary Policy, Tobias Adrian, Doug Laxton and Maurice Obstfeld, editors, International Monetary Fund, Washington DC, April 2018
Loose financial conditions forecast high output growth and low output volatility up to six quarters into the future, generating time varying downside risk to the output gap which we measure by GDP-at-Risk (GaR). This finding is robust across countries, conditioning variables, and time periods. We study the implications for monetary policy in a reduced form New Keynesian model with financial intermediaries that are subject to a Value at Risk (VaR) constraint. Optimal monetary policy depends on the magnitude downside risk to GDP, as it impacts the consumption-savings decision via the Euler constraint, and the financial conditions via the tightness of the VaR constraint. The optimal monetary policy rule exhibits a pronounced response to shifts in financial conditions for most countries in our sample. Welfare gains from taking financial conditions into account are shown to be sizable.
Working paper version (ungated)
- The Equity Risk Premium: A Review of Models
with Carlo Rosa.
Federal Reserve Bank of New York Economic Policy Review, Volume 21, Number 2, December 2015
We estimate the equity risk premium (ERP) by combining information from twenty models. The ERP in 2012 and 2013 reached heightened levels — of around 12 percent — not seen since the 1970s. We conclude that the high ERP was caused by unusually low Treasury yields.
Latest ERP estimates (September 2019)