Abstract Wealthy households disproportionately invest in equity, causing equity returns to generate large and persistent fluctuations in top wealth inequality. Motivated by this observation, I study the joint dynamics of asset prices and wealth inequality in a model where a subset of agents (entrepreneurs) hold levered positions on the economy. In the model, as in the data, the wealth distribution is stochastic and it exhibits a Pareto tail, with a tail index that depends on the logarithmic average return of top households. The model features a feedback loop between asset prices and wealth inequality, which amplifies the effect of aggregate shocks on the economy. The model, calibrated to the U.S. data, can account for a substantial portion of the fluctuations in asset prices and top wealth shares over the 20th century.

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.

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.

We document that banks that cut lending more during the Great Recession were lending to riskier firms ex-ante. To understand the aggregate implications of this sorting pattern, we build an assignment model in which banks have heterogeneous costs to take on risky loans and firms have different credit risks. In the model, aggregate loan volume depends on the entire distribution of bank holding costs and firm credit risks. We then use our model to recover the change in the distribution of bank holding costs during the Great Recession and show that it explains two-thirds of the decline of aggregate loan volume during this period.

Over the last several decades, there has been a large increase in asset 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 (money metric) welfare effect of a change in asset valuations, which depends on the present value of an individual’s net asset sales: rising asset prices 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 rising asset valuations had large redistributive effects: they redistributed from the young towards the old and from the poor towards the wealthy