Asset Prices and Wealth Inequality (2017)
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.
Ups and Downs: How Idiosyncratic Volatility Drives Top Wealth Inequality (2018)
This paper examines the role of idiosyncratic volatility in driving the recent rise in top wealth inequality. Because the composition of households in top percentiles changes over time, the growth of top wealth shares is not simply equal to the average wealth growth of households in top percentiles relative to the economy. It also depends on a displacement term, which is driven by the entry and exit of households in top percentiles. I relate analytically the displacement term to the dispersion of wealth shocks among top households. Using the Forbes 400 list, I document that the displacement term accounts for more than half the rise in top wealth inequality in the United States since 1983. I discuss the implications of this result for wealth mobility, as well as for the relationship between inequality and technological innovation.
Bank Exposure to Interest-Rate Risk and the Transmission of Monetary Policy with A. Landier, D. Sraer and D. Thesmar (2016)
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.