Real-Time Inequality∗ Thomas Blanchet (Paris School of Economics) Emmanuel Saez (UC Berkeley and NBER) Gabriel Zucman (UC Berkeley and NBER) November 23, 2023
Abstract This paper constructs monthly distributions of national income for the United States. We develop a methodology to disaggregate annual distributions and project monthly changes in a timely manner by combining high-frequency public data sources. This allows us to estimate growth by social groups as soon as quarterly macroeconomic growth numbers are released, and to track the distributional impacts of government policies during and in the aftermath of recessions in real time. We test and validate our methodology by implementing it retrospectively back to 1976. Estimates are available at https: //realtimeinequality.org and are regularly updated with new releases of the national accounts. JEL Codes: E01, H2, H5, J3.
∗
Thomas Blanchet: thomas.blanchet@wid.world; Emmanuel Saez: saez@econ.berkeley.edu; Gabriel Zucman: zucman@berkeley.edu. We thank Akcan Balkir, Anand Bharadwaj, and James Feng for outstanding research assistance, and Heather Boushey, Dennis Fixler, Marina Gindelsky, Damon Jones, Robert Kornfeld, Greg Leiserson, Danny Yagan, and numerous conference participants for helpful comments and reactions. We acknowledge financial support from the Center for Equitable Growth at UC Berkeley, the Carnegie Foundation, NSF grant SES-1559014, the Stone Foundation, and the European Research Council. This paper is supplemented by a website, https://realtimeinequality.org, with regularly updated inequality and distributional growth estimates and detailed visualizations. All our data and programs are also posted online at this address.