This paper studies how monetary policy jointly affects asset prices and the real economy in the United States. I develop an estimator that uses high-frequency surprises as a proxy for the structural monetary policy shocks. This is achieved by integrating the surprises into a vector autoregressive model as an exogenous variable. I use current short-term rate surprises because these are least affected by an information effect. When allowing for time-varying model parameters, I find that compared to the response of output, the reaction of stock and house prices to monetary policy shocks was particularly low before the 2007–2009 financial crisis.

ABSTRACT Aggregate U.S. bank lending to firms expanded following the outbreak of COVID‐19. Using loan‐level supervisory data, we show that this expansion was driven by draws on credit lines by large firms. Banks that experienced larger credit line drawdowns restricted term lending more, crowding out credit to smaller firms, which reacted by reducing investment. A structural model calibrated to match our empirical results shows that while credit lines increase total bank credit in bad times, they redistribute credit from firms with high propensities to invest to firms with low propensities to invest, exacerbating the decrease in aggregate investment.

We investigate the transmission of monetary policy to household consumption using administrative data on the universe of households in Norway. On the basis of identified monetary policy shocks, we estimate the dynamic responses of consumption, income, and saving along the liquid asset distribution of households. For low-liquidity but also for high-liquidity households, changes in disposable income are associated with a sizable consumption reaction. The impact consumption response is closely linked to interest rate exposure, which is negative at the bottom but positive at the top of the distribution. Indirect effects of monetary policy gradually build up and eventually outweigh the direct effects.