Data and code for: Growing Income Inequality in the United States and other Advanced Economies

Principal Investigator(s): View help for Principal Investigator(s) Florian Hoffmann, University of British Columbia; David S. Lee, Princeton University; Thomas Lemieux, University of British Columbia

Version: View help for Version V1

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README.pdf	application/pdf	244.7 KB	12/13/2020 08:05:PM

Project Citation:

Hoffmann, Florian, Lee, David S., and Lemieux, Thomas. Data and code for: Growing Income Inequality in the United States and other Advanced Economies. Nashville, TN: American Economic Association [publisher], 2021. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-01-26. https://doi.org/10.3886/E122201V1

Project Description

Summary: This paper studies the contribution of both labor and non-labor income in the growth in income inequality in the United States and large European economies. The paper first shows that the capital to labor income ratio disproportionately increased among high-earnings individuals, further contributing to the growth in overall income inequality. That said, the magnitude of this effect is modest, and the predominant driver of the growth in income inequality in recent decades is the growth in labor earnings inequality. Far more important than the distinction between total income and labor income, is the way in which educational factors account for the growth in U.S. labor and capital income inequality. Growing income gaps among different education groups as well as composition effects linked to a growing fraction of highly-educated workers have been driving these effects, with a noticeable role for occupational and locational factors for women. Findings for large European economies indicate that inequality has been growing fast in Germany, Italy, and the United Kingdom, though not in France. Capital income and education don’t play as much as a role in these countries as in the United States.

Scope of Project

Subject Terms: inequality; education; incomes

JEL Classification:
I24 Education and Inequality
J31 Wage Level and Structure; Wage Differentials

Geographic Coverage: United States, United Kingdom, Italy, France, Germany

Time Period(s): 1975 – 2018

Collection Date(s): 1976 – 2019

Universe: Adult noninstitutionalized population

Data Type(s): survey data

Methodology

Data Source:

United States:

Flood, Sarah, Miriam King, Renae Rodgers, Steven Ruggles and J. Robert Warren. “Integrated Public Use Microdata Series, Current Population Survey: Version 7.0 [dataset].” Minneapolis, MN: IPUMS, 2020.

U.S. Census Bureau. 1975-2010. “Revised Income Topcodes for the Annual Social and Economic Survey (ASEC) Public Use Files.” United States Department of Commerce.

Bureau of Labor Statistics. 1975-2018. “CPI for All Urban Consumers (CPI-U), All items in U.S. city average, all urban consumers, not seasonally adjusted– CUUR0000SA0.” United States Department of Labor

France, Italy and United Kingdom:

Luxembourg Income Study (LIS) Database. 2020. http://www.lisdatacenter.org (multiple countries; May 2020). Luxembourg: LIS

Germany:

Statistisches Bundesamt. “Einkommens- und Verbrauchsstichprobe (EVS data), survey years 1998-2013.” Accessed on the RDC of the Federal Statistical Office and Statistical Offices of the Laender.

Statistisches Bundesamt. 1998-2013. “Verbraucherpreisindex fuer Deutschland, Lange Reihen ab 1948 – Oktober 2020.” DeStatis.

Unit(s) of Observation: Individuals

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Published Versions

V1 [2021-01-26]

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