April 3, 2023
Written by WID.world

Uncovering the Dynamics of the Wealth Distribution


This paper introduces a new way of decomposing the evolution of the wealth distribution using a simple continuous time stochastic model, which separates the effects of mobility, savings, labor income, rates of return, demography, inheritance, and assortative mating. Based on two results from stochastic calculus, I show that this decomposition is nonparametrically identified and can be estimated based solely on repeated cross-sections of the data. I estimate it in the United States since 1962 using historical data on income, wealth, and demography. I find that the main drivers of the rise of the top 1% wealth share since the 1980s have been, in decreasing level of importance, higher savings at the top, higher rates of return on wealth (essentially in the form of capital gains), and higher labor income inequality. I then use the model to study the effects of wealth taxation. I derive simple formulas for how the tax base reacts to the net-of-tax rate in the long run, which nest insights from several existing models, and can be calibrated using estimable elasticities. In the benchmark calibration, the revenue-maximizing wealth tax rate at the top is high (around 12%), but the revenue collected from the tax is much lower than in the static case.



  • Thomas Blanchet, World Inequality Lab, Paris School of Economics, thomas.blanchet@psemail.eu
  • An online simulator for the United States that uses the formulas developed in this paper is available at https://thomasblanchet.github.io/wealth-tax/. All the data and replication codes are available at https://github.com/thomasblanchet/uncovering-wealth-dynamics.


  • press@wid.world.com


I thank Jess Benhabib, François Bourguignon, Laurent Bach, Frank Cowell, Xavier d’Haultfoeuille, Thomas Piketty, Muriel Roger, Emmanuel Saez, Gabriel Zucman, as well as numerous seminar and conference participants for helpful discussions and comments.