This paper uses recently available data on the top of the wealth distribution to study the relationship between asset prices and wealth inequality. I document three stylized facts: (1) the share of wealth invested in equity increases sharply in the right tail of the wealth distribution, (2) when stock market returns are high, wealth inequality increases and (3) higher wealth inequality predicts lower future stock returns. These facts correspond to the basic predictions of asset pricing models with heterogeneous agents. Quantitatively, however, standard models with heterogeneous agents cannot fully capture the joint dynamics of asset prices and the wealth distribution. Augmenting the model with additional sources of fluctuations in wealth inequality, namely in the form of time-varying investment opportunities for wealthy households, is crucial to match the observed fluctuations in wealth inequality and in asset prices.
There has been a dramatic rise in top wealth inequality in the United States since 1980. To shed light on this phenomenon, I derive an analytical formula that decomposes the growth of top wealth shares into three terms: the relative wealth growth of individuals in the top, a term due to idiosyncratic returns, and a term due to population renewal. I then map each term to the data using the annual ranking of Forbes Magazine's list of the 400 wealthiest Americans. The decomposition reveals that the rise in top wealth shares in 1982-1994 is mostly driven by idiosyncratic returns, while the rise in top wealth shares in 1995-2015 is mostly driven by the relative growth of individuals at the top.
We show that the cash-flow exposure of banks to interest rate risk, or income gap, affects the transmission of monetary policy to bank lending and real activity. In the cross-section of banks, income gap predicts the sensitivity of cash-flows and lending to interest rates. The effect of income gap is larger or similar in magnitude to that of previously identified factors, such as leverage, bank size or asset liquidity. To alleviate endogeneity concerns, we build loan-level data to control for firm-level demand shocks. This analysis also allows us to link banks' interest risk exposure to firm investment and employment.