Using the Pareto Distribution to Improve Estimates of Topcoded Earnings

19 Pages Posted: 12 Apr 2014

See all articles by Philip Armour

Philip Armour

Cornell University

Richard V. Burkhauser

Cornell University - Department of Policy Analysis & Management (PAM); University of Melbourne, Melbourne Institute

Jeff Larrimore

Board of Governors of the Federal Reserve System

Multiple version iconThere are 3 versions of this paper

Date Written: April 1, 2014

Abstract

Inconsistent censoring in the public-use March Current Population Survey (CPS) limits its usefulness in measuring labor earnings trends. Using Pareto estimation methods with less-censored internal CPS data, we create an enhanced cell-mean series to capture top earnings in the public-use CPS. We find that previous approaches for imputing topcoded earnings systematically understate top earnings. Annual earnings inequality trends since 1963 using our series closely approximate those found by Kopczuk, Saez, & Song (2010) using Social Security Administration data for commerce and industry workers. However, when we consider all workers, earnings inequality levels are higher but earnings growth is more modest.

Suggested Citation

Armour, Philip and Burkhauser, Richard V. and Larrimore, Jeff, Using the Pareto Distribution to Improve Estimates of Topcoded Earnings (April 1, 2014). US Census Bureau Center for Economic Studies Paper No. CES-WP-14-21, Available at SSRN: https://ssrn.com/abstract=2423537 or http://dx.doi.org/10.2139/ssrn.2423537

Philip Armour (Contact Author)

Cornell University ( email )

No Address Available

Richard V. Burkhauser

Cornell University - Department of Policy Analysis & Management (PAM) ( email )

120 Martha Van Rensselaer Hall
Ithaca, NY 14853
United States

University of Melbourne, Melbourne Institute ( email )

Level 5, FBE Building, 111 Barry Street
161 Barry Street
Carlton, VIC 3053
Australia

Jeff Larrimore

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

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