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Working Paper
What is Certain about Uncertainty?
Researchers, policymakers, and market participants have become increasingly focused on the effects of uncertainty and risk on financial market and economic outcomes. This paper provides a comprehensive survey of the many existing measures of risk, uncertainty, and volatility. It summarizes what these measures capture, how they are constructed, and their effects, paying particular attention to large uncertainty spikes, such as those appearing concurrently with the outbreak of COVID-19. The measures are divided into three types: (1) news-based, survey- based, and econometric; (2) asset market ...
Discussion Paper
Vulnerable Growth
Traditional GDP forecasts potentially present an overly optimistic (or pessimistic) view of the state of the economy: by focusing on the point estimate for the conditional mean of growth, such forecasts ignore risks around the central forecast. Yet, policymakers around the world increasingly focus on risks to the central forecast in policy debates. For example, in the United States the Federal Open Market Committee (FOMC) commonly discusses the balance of risks in the economy, with the relative prominence of this discussion fluctuating with the state of the economy. In a recent paper, we ...
Working Paper
Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions
A rapidly growing body of research has examined tail risks in macroeconomic outcomes. Most of this work has focused on the risks of significant declines in GDP, and it has relied on quantile regression methods to estimate tail risks. Although much of this work discusses asymmetries in conditional predictive distributions, the analysis often focuses on evidence of downside risk varying more than upside risk. We note that this pattern in risk estimates over time could obtain with conditional distributions that are symmetric but subject to simultaneous shifts in conditional means (down) and ...
Working Paper
Modeling the Evolution of Expectations and Uncertainty in General Equilibrium
We develop methods to solve general equilibrium models in which forward-looking agents are subject to waves of pessimism, optimism, and uncertainty that turn out to critically affect macroeconomic outcomes. Agents in the model are fully rational, conduct Bayesian learning, and they know that they do not know. Therefore, agents take into account that their beliefs will evolve according to what they will observe. This framework accommodates both gradual and abrupt changes in beliefs and allows for an analytical characterization of uncertainty. Shocks to beliefs affect economic dynamics and ...
Working Paper
A Tale of Four Tails: Inflation, the Policy Rate, Longer-Term Rates, and Stock Prices
We analyze empirical links between the perceived tail-risk of inflation, the policy rate, longer-term interest rates, and equity prices in the U.S. Their simultaneous changes enable us to distinguish between a systematic and "exogenous" response to monetary-policy news. And, those tail risks' co-movements are accounted for in quantifying the magnitude and persistence of their responses to key shocks. We find that: (i) in the medium-term, all four tail risks respond significantly and contemporaneously to domestic and foreign monetary-policy announcements, except for the equity tail risk to ...
Working Paper
Nowcasting Tail Risks to Economic Activity with Many Indicators
This paper focuses on tail risk nowcasts of economic activity, measured by GDP growth, with a potentially wide array of monthly and weekly information. We consider different models (Bayesian mixed frequency regressions with stochastic volatility, classical and Bayesian quantile regressions, quantile MIDAS regressions) and also different methods for data reduction (either the combination of forecasts from smaller models or forecasts from models that incorporate data reduction). The results show that classical and MIDAS quantile regressions perform very well in-sample but not out-of-sample, ...
Working Paper
Nowcasting Tail Risks to Economic Activity with Many Indicators
This paper focuses on nowcasts of tail risk to GDP growth, with a potentially wide array of monthly and weekly information. We consider different models (Bayesian mixed frequency regressions with stochastic volatility, as well as classical and Bayesian quantile regressions) and also different methods for data reduction (either forecasts from models that incorporate data reduction or the combination of forecasts from smaller models). Our results show that, within some limits, more information helps the accuracy of nowcasts of tail risk to GDP growth. Accuracy typically improves as time moves ...
Working Paper
Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions
A rapidly growing body of research has examined tail risks in macroeconomic outcomes. Most of this work has focused on the risks of significant declines in GDP, and has relied on quantile regression methods to estimate tail risks. In this paper we examine the ability of Bayesian VARs with stochastic volatility to capture tail risks in macroeconomic forecast distributions and outcomes. We consider both a conventional stochastic volatility specification and a specification featuring a common volatility factor that is a function of past financial conditions. Even though the conditional ...
Report
Vulnerable growth
We study the conditional distribution of GDP growth as a function of economic and financial conditions. Deteriorating financial conditions are associated with an increase in the conditional volatility and a decline in the conditional mean of GDP growth, leading the lower quantiles of GDP growth to vary with financial conditions and the upper quantiles to be stable over time: Upside risks to GDP growth are low in most periods while downside risks increase as financial conditions become tighter. We argue that amplification mechanisms in the financial sector generate the observed growth ...
Working Paper
Uncertainty and Growth Disasters
This paper documents several stylized facts on the real effects of economic uncertainty. First, higher uncertainty is associated with a more dispersed and negatively skewed distribution of output growth. Second, the response of economic growth to an increase in uncertainty is highly nonlinear and asymmetric. Third, higher asset volatility magnifies the negative impact of uncertainty on growth. We develop and estimate an analytically tractable model in which rapid adoption of new technology may raise economic uncertainty which causes measured productivity to decline. The equilibrium growth ...