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Keywords:pandemics 

Journal Article
The Uncertainty Channel of the Coronavirus

The outbreak of the novel coronavirus, or COVID-19, has severely disrupted economic activity through various supply and demand channels. The pandemic can also have pervasive economic impact by raising uncertainty. In the past, sudden and outsized spikes in uncertainty have led to large and protracted increases in unemployment and declines in inflation. These effects are similar to those resulting from declines in aggregate demand. Monetary policy accommodation, such as interest rate cuts, can help cushion the economy from such uncertainty shocks.
FRBSF Economic Letter , Volume 2020 , Issue 07 , Pages 05

Report
The Effect of the Central Bank Liquidity Support during Pandemics: Evidence from the 1918 Influenza Pandemic

The coronavirus outbreak raises the question of how central bank liquidity support affects financial stability and promotes economic recovery. Using newly assembled data on cross-county flu mortality rates and state-charter bank balance sheets in New York State, we investigate the effects of the 1918 influenza pandemic on the banking system and the role of the Federal Reserve during the pandemic. We find that banks located in more severely affected areas experienced deposit withdrawals. Banks that were members of the Federal Reserve System were able to access central bank liquidity, enabling ...
Staff Reports , Paper 928

Working Paper
Addressing COVID-19 Outliers in BVARs with Stochastic Volatility

Incoming data in 2020 posed sizable challenges for the use of VARs in economic analysis: Enormous movements in a number of series have had strong effects on parameters and forecasts constructed with standard VAR methods. We propose the use of VAR models with time-varying volatility that include a treatment of the COVID extremes as outlier observations. Typical VARs with time-varying volatility assume changes in uncertainty to be highly persistent. Instead, we adopt an outlier-adjusted stochastic volatility (SV) model for VAR residuals that combines transitory and persistent changes in ...
Working Papers , Paper 2021-02

Working Paper
Measuring Uncertainty and Its Effects in the COVID-19 Era

We measure the effects of the COVID-19 outbreak on macroeconomic and financial uncertainty, and we assess the consequences of the latter for key economic variables. We use a large, heteroskedastic vector autoregression (VAR) in which the error volatilities share two common factors, interpreted as macro and financial uncertainty, in addition to idiosyncratic components. Macro and financial uncertainty are allowed to contemporaneously affect the macroeconomy and financial conditions, with changes in the common component of the volatilities providing contemporaneous identifying information on ...
Working Papers , Paper 202032

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, classical and Bayesian quantile regressions, quantile MIDAS 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 ...
Working Papers , Paper 202013R

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 Papers , Paper 202013

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 Papers , Paper 202013R2

Working Paper
Longer-Run Economic Consequences of Pandemics

How do major pandemics affect economic activity in the medium to longer term? Is it consistent with what economic theory prescribes? Since these are rare events, historical evidence over many centuries is required. We study rates of return on assets using a dataset stretching back to the 14th century, focusing on 12 major pandemics where more than 100,000 people died. In addition, we include major armed conflicts resulting in a similarly large death toll. Significant macroeconomic after-effects of the pandemics persist for about 40 years, with real rates of return substantially depressed. In ...
Working Paper Series , Paper 2020-09

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