Assistant Professor
Department of Economics
Columbia University
1131 International Affairs Building, NY 10027
mg3901@columbia.edu
CV
Working Papers

AssetPrice Redistribution with A. Fagereng, E. GouinBonenfant, M. Holm, B. Moll, and G. Natvik
R&R, Journal of Political Economy
Over the last several decades, there has been a large increase in asset valuations across many asset classes. While these rising valuations had important effects on the distribution of wealth, little is known regarding their effect on the distribution of welfare . To make progress on this question, we develop a sufficient statistic for the moneymetric welfare effect of deviations in asset valuations (i.e., changes in asset prices keeping cash flows fixed). This welfare effect depends on the present value of an individual's net asset sales rather than asset holdings: higher asset valuations benefit prospective sellers and harm prospective buyers. We estimate this quantity using panel microdata covering the universe of financial transactions in Norway from 1994 to 2019. We find that the rise in asset valuations had large redistributive effects: it redistributed from the young towards the old and from the poor towards the wealthy.

Wealth Inequality and Asset Prices
R&R, Review of Economic Studies
Wealthy households disproportionately invest in equity, causing equity returns to generate large and persistent fluctuations in top wealth inequality. Motivated by this fact, I build an equilibrium model of the wealth distribution where agents have heterogeneous exposures to aggregate risk. While the wealth distribution is stochastic in the model, I show that it exhibits a Pareto tail, with a (timeinvariant) index that depends on the average logarithmic return of top households. The model features a twoway feedback between asset prices and wealth inequality, which amplifies the response of top wealth inequality to aggregate income shocks in the shortrun while dampening it in the mediumrun. Aggregate shocks generate particularly large fluctuations in the right tail of the wealth distribution, as higher percentiles are more exposed to aggregate risk and take a longer time to mean revert.
Publications

Wealth Inequality in a Low Rate Environment with E. GouinBonenfant
Econometrica (2024)
Journal version  Supplemental Appendix  Replication repository
We study the effect of interest rates on wealth inequality. While lower rates decrease the growth rate of rentiers, they also increase the growth rate of entrepreneurs 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 lifetime equity and debt issuance rate of individuals in the right tail of the wealth distribution. We estimate this sufficient statistic using new data on the trajectory of top fortunes in the U.S. Overall, we find that the secular decline in interest rates (or more generally of required rates of returns) can account for about 40% of the rise in Pareto inequality; that is, the degree to which the super rich pulled ahead relative to the rich.

Sorting Out the Effect of Credit Supply with B. Chang and H. Hong
Journal of Financial Economics (2023)
Journal version  Replication repository
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
Econometrica (2023)
Journal version  Replication repository  Stata command
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 closedform 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 InterestRate Risk and the Transmission of Monetary Policy with A. Landier, D. Sraer, and D. Thesmar
Journal of Monetary Economics (2021)
Journal version
The cashflow 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 loanlevel data, even when we control for firmspecific credit demand. When monetary policy tightens, firms borrowing from banks with a larger income gap reduce their investment by less than other firms.