Reconciling the divergence in aggregate U.S. wage series

Julien Champagne, André Kurmann and Jay Stewart

Labour Economics, 2017, vol. 49, issue C, 27-41

Abstract: Average hourly wages from the Labor Productivity and Costs (LPC) program, the Current Population Survey (CPS) and the Current Employment Statistics (CES) survey have diverged, both in trend and volatility. Supplements and irregular earnings of high-income workers, included in the LPC but not in the two other datasets, have grown more rapidly and have become more volatile, accounting for most of the divergence between LPC and CPS earnings. The more restrictive worker coverage in the CES explains a large part of the divergence between CPS and CES earnings. The results have important implications for the choice of wage series in macroeconomic analysis.

Keywords: Wages and salaries; Supplements; Irregular earnings; Worker coverage; Divergence in trend and volatility (search for similar items in EconPapers)
JEL-codes: E01 E24 E30 J30 (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0927537117302701
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Reconciling the divergence in aggregate U.S. wage series (2016)
Working Paper: Reconciling the Divergence in Aggregate U.S. Wage Series (2016)
Working Paper: Reconciling the divergence in aggregate U.S. wage series (2015)
Working Paper: Reconciling the divergence in aggregate U.S. wage series (2014)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:labeco:v:49:y:2017:i:c:p:27-41

DOI: 10.1016/j.labeco.2017.08.002

Access Statistics for this article

Labour Economics is currently edited by A. Ichino

More articles in Labour Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().