We study optimal interest-rate policy in a New Keynesian model in which the economy can experience financial crises and the probability of a crisis depends on credit conditions. The optimal adjustment to interest rates in response to credit conditions is (very) small in the model calibrated to...

Using only daily data on bond and stock returns, we identify and characterize flight to safety (FTS) episodes for 23 countries. On average, FTS days comprise less than 3% of the sample, and bond returns exceed equity returns by 2.5 to 4%. The majority of FTS events are country-specific not...

We use non-Gaussian features in U.S. macroeconomic data to identify aggregate supply and demand shocks while imposing minimal economic assumptions. Recessions in the 1970s and 1980s were driven primarily by supply shocks, later recessions were driven primarily by demand shocks, and the Great...

We extract aggregate demand and supply shocks for the US economy from real-time survey data on inflation and real GDP growth using a novel identification scheme. Our approach exploits non-Gaussian features of macroeconomic forecast revisions and imposes minimal theoretical assumptions. After...

Some key structural features of the U.S. economy appear to have changed in the recent decades, making the conduct of monetary policy more challenging. In particular, there is high uncertainty about the levels of the natural rate of interest and unemployment as well as about the effect of...

This paper reviews the theoretical literature at the intersection of macroeconomics and finance to draw lessons on the connection between vulnerabilities in the financial system and the macroeconomy, and on how monetary policy affects that connection. This literature finds that financial...

We build a new measure of credit and financial market sentiment using Natural Language Processing on Twitter data. We find that the Twitter Financial Sentiment Index (TFSI) correlates highly with corporate bond spreads and other price- and survey-based measures of financial conditions. We...