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Reconciling the divergence in aggregate U.S. wage series

Julien Champagne

No 718, 2014 Meeting Papers from Society for Economic Dynamics

Abstract: This paper documents the gradual divergence in trend growth and business cycle volatility of two popular aggregate hourly wage series for the U.S. economy: average hourly compensation from the Labor Productivity and Cost (LPC) program and average hourly earnings from the Current Employment Statistics (CES). While the LPC wage increased by about 70% over the past four decades and became markedly more volatile starting in the 1980s, the CES wage grew by only about 20% over the same period and experienced a large drop in volatility post-1980. We establish that the divergence between the two aggregate hourly wage series is due to the different evolution of average labor earnings. Average hours worked, by contrast, evolve very similarly. We then use labor earnings data from the Current Population Survey (CPS), the National Income and Product Accounts (NIPAs), and Piketty and Saez (2003) in an attempt to reconcile the divergence between LPC and CES labor earnings. Our analysis indicates that differences in earnings concept and population coverage can account for a large part of the divergence. Our analysis also shows that earnings differences between the CPS and the LPC can be attributed almost entirely to earnings of high-income individuals and supplements such as employer contributions to pension and health plans, which are included in the LPC but not in the CPS. This result is interesting in its own right given the widespread use of micro earnings data from the CPS in cross-sectional studies.

Date: 2014
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Related works:
Journal Article: Reconciling the divergence in aggregate U.S. wage series (2017) Downloads
Working Paper: Reconciling the divergence in aggregate U.S. wage series (2016) Downloads
Working Paper: Reconciling the Divergence in Aggregate U.S. Wage Series (2016) Downloads
Working Paper: Reconciling the divergence in aggregate U.S. wage series (2015) Downloads
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