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Working Paper
Accounting for the Sources of Macroeconomic Tail Risks
Using a multi-industry real business cycle model, we empirically examine the microeconomic origins of aggregate tail risks. Our model, estimated using industry-level data from 1972 to 2016, indicates that industry-specific shocks account for most of the third and fourth moments of GDP growth.
Working Paper
The Tail that Wags the Economy: Beliefs and Persistent Stagnation
The Great Recession was a deep downturn with long-lasting effects on credit, employment and output. While narratives about its causes abound, the persistence of GDP below pre-crisis trends remains puzzling. We propose a simple persistence mechanism that can be quantified and combined with existing models. Our key premise is that agents don't know the true distribution of shocks, but use data to estimate it non-parametrically. Then, transitory events, especially extreme ones, generate persistent changes in beliefs and macro outcomes. Embedding this mechanism in a neoclassical model, we find ...
Working Paper
The Missing Tail Risk in Option Prices
This paper contributes to the literature on deviations from rational expectations in financial markets and to the literature on evaluating density forecasts. We first develop a novel statistic to evaluate the overall accuracy of distributional forecasts, and find two methods that yield accurate distributional forecasts. We then propose another statistic to examine the relative accuracy over the entire distribution range. Our results indicate more oil price realizations in the left tail than predicted. We argue that this finding points to a persistent behavioral forecasting bias and a ...
Working Paper
Assessing Macroeconomic Tail Risks in a Data-Rich Environment
We use a large set of economic and financial indicators to assess tail risks of the three macroeconomic variables: real GDP, unemployment, and inflation. When applied to U.S. data, we find evidence that a dense model using principal components (PC) as predictors might be misspecified by imposing the “common slope” assumption on the set of predictors across multiple quantiles. The common slope assumption ignores the heterogeneous informativeness of individual predictors on different quantiles. However, the parsimony of the PC-based approach improves the accuracy of out-of-sample forecasts ...
Working Paper
The Missing Tail Risk in Option Prices
This paper contributes to the literature on deviations from rational expectations in financial markets and to the literature on evaluating density forecasts. We first develop a novel statistic to evaluate the overall accuracy of distributional forecasts, and find two methods that yield accurate distributional forecasts. We then propose another statistic to examine the relative accuracy over the entire distribution range. Our results indicate more oil price realizations in the left tail than predicted. We argue that this finding points to a persistent behavioral forecasting bias and a ...
Journal Article
COVID-19: Scarring Body and Mind
"Belief scarring" from the COVID-19 pandemic may generate prolonged effects on the economy—with economic costs greater than the drop in GDP in 2020.
Working Paper
Scarring Body and Mind: The Long-Term Belief-Scarring Effects of COVID-19
The largest economic cost of the COVID-19 pandemic could arise if it changed behavior long after the immediate health crisis is resolved. A common explanation for such a long-lived effect is the scarring of beliefs. We show how to quantify the extent of such belief changes and determine their impact on future economic outcomes. We find that the long-run effect of the COVID crisis depends crucially on whether bankruptcies and changes in habit make existing capital obsolete. A policy that avoided most permanent separation of workers from capital could generate a much larger benefit than ...