Assistant Professor of Economics, Columbia University
1131 International Affairs Building, NY 10027
Asset-Price Redistribution with A. Fagereng, E. Gouin-Bonenfant, M. Holm, B. Moll, and G. Natvik
Over the last several decades, there has been a large increase in valuations across many
asset classes. These rising valuations had important effects on the distribution of wealth.
However, little is known regarding their effect on the distribution of welfare . To make
progress on this question, we derive a sufficient statistic for the welfare effect of a change
in asset valuations, which depends on the present value of an individual’s net asset sales.
We estimate this quantity using panel microdata covering the universe of financial transactions in Norway from 1994 to 2015. We find that rising asset valuations had important
redistributive effects: they redistributed welfare from the young towards the old and from
the poor towards the wealthy.
Asset Prices and Wealth Inequality
Wealthy households disproportionately invest in equity, causing equity returns to generate fluctuations in wealth inequality. To examine the macro effect of these movements in the wealth distribution, I build a model in which agents have heterogeneous exposures to aggregate shocks. I show that the tail index of the wealth distribution depends of the average logarithmic return of top households. The model generates a two-way feedback between wealth inequality and asset prices, which magnifies the response of wealth inequality to aggregate shocks in the short-run but reduces it in the longer-run. The model, calibrated on U.S. data, can account for a large fraction of the fluctuations of asset prices and wealth inequality over the 20th century.
A Q-Theory of Inequality with E. Gouin-Bonenfant
We study the effect of interest rates on wealth inequality. While low rates decrease the average growth rate of existing fortunes, they increase the growth rate of new fortunes by making it cheaper to raise capital. To understand which effect dominates, we derive a sufficient statistic for the effect of interest rates on the Pareto exponent of the wealth distribution: it depends on the average equity issuance rate and leverage of individuals reaching the right tail of the distribution. We estimate this sufficient statistic using new data on the trajectory of top fortunes in the U.S. We conclude that the secular decline in discount rates has played a key role in the recent increase of top wealth inequality.
Sorting Out the Real Effects of Credit Supply with B. Chang and H. Hong
R&R, Journal of Financial Economics
We show that banks that cut lending more during the Great Recession lent to riskier firms. To examine the equilibrium effect of this sorting pattern, we build an assignment model in which banks have heterogeneous holding costs and firms have heterogeneous risks. In the model, loan volume declines more when negative credit supply shocks are concentrated on low holding cost banks like Lehman Brothers relative to high holding cost banks. We then use our model to recover the change in the distribution of bank holding costs during the Great Recession and quantify its effect on aggregate loan volume.
Decomposing the Growth of Top Wealth Shares
[Data] [Stata Program]
What drives the dynamics of top wealth inequality? To answer this question, I propose an accounting framework that decomposes the growth of the share of aggregate wealth owned by a top percentile into three terms: a within term, which is the average wealth growth of individuals initially in the top percentile relative to the economy; a between term, which accounts for individuals entering and exiting the top percentile due to changes in their relative wealth rankings; and a demography term, which accounts for individuals entering or exiting the top percentile due to death and population growth. I obtain closed-form expressions for each term in a wide range of random growth models. Evidence from the Forbes 400 list suggests that the between term accounts for half of the recent rise in top wealth inequality.
Bank Exposure to Interest-Rate Risk and the Transmission of Monetary Policy with A. Landier, D. Sraer, and D. Thesmar
Journal of Monetary Economics (2021)
The cash-flow exposure of banks to interest rate risk, or income gap, is a significant determinant of the transmission of monetary policy to bank lending and real activity. When the Fed Funds rate rises, banks with a larger income gap generate stronger earnings and contract their lending by less than other banks. This finding is robust to controlling for factors known to affect the transmission of monetary policy to bank lending. It also holds on loan-level data, even when we control for firm-specific credit demand. When monetary policy tightens, firms borrowing from banks with a larger income gap reduce their investment by less than other firms.