Using a large-scale survey of U.S. households during the Covid-19 pandemic, we study how new information about fiscal and monetary policy responses to the crisis affects households' expectations. We provide random subsets of participants in the Nielsen Homescan panel with different combinations...

This paper provides the first comprehensive econometric analysis of the causes of bank distress during the Depression. We assemble bank-level data for virtually all Fed member banks, and combine those data with county-level, state-level, and national-level economic characteristics to capture...

We develop a deep learning model to detect emotions embedded in press conferences after the meetings of the Federal Open Market Committee and examine the influence of the detected emotions on financial markets. We find that, after controlling for the Fed's actions and the sentiment in policy...

This paper begins by developing a framework for price and interest rate determination under suspension of convertibility during the national banking period. The model is applied to interpret unanticipated price level shocks and expected deflation during the period of green back inconvertibility(...

We introduce FDIF, a measure of Fed communication surprise based on the text of FOMC statements. FDIF measures the difference between text-implied and actual values of key market variables. Positive FDIF of countercyclical variables (e.g., credit spreads) is associated with negative...