The Cost of Labor Adjustment: Inferences from the Gap

By Russell Cooper and Jonathan L. Willis
December 2002; Last Revised July 2004
RWP 02-11
Research Division 
Federal Reserve Bank of Kansas City 

Abstract

      The paper studies labor adjustment costs. Our focus is on inferring the structure of adjustment costs at the micro-level from aggregate observations of employment and hours growth. We specify a dynamic optimization problem at the plant level, allowing for both convex and non-convex adjustment costs. We estimate the parameters of the adjustment process using an indirect inference procedure in which simulated moments are matched with data moments. For this study we use estimates of reduced-form adjustment functions obtained by the "gap methodology" reported in Caballero and Engel (1993) as data moments. Contrary to evidence at the micro level in support of non-convex adjustment costs, our findings indicate that piecewise quadratic adjustment costs are sufficient to match these aggregate moments.

Keywords: Aggregate Employment, Employment, Adjustment Costs

JEL Codes: E24, J23, J6

Russell Cooper is a professor of economics at the University of Texas and, when this paper was written, was a visiting scholar at the Federal Reserve Bank of Minneapolis. Jonathan L. Willis is an economist at the Federal Reserve Bank of Kansas City. The authors would like to thank the NSF for financial support. Cooper thanks the Federal Reserve Bank of Minneapolis for its hospitality during revisions of this manuscript.  The views expressed in this paper are those of the authors and do not necessarily represent the views of the Federal Reserve Bank of Kansas City, Federal Reserve Bank of Minneapolis, or the Federal Reserve System.

Cooper e-mail:  cooper@eco.utexas.edu
Willis e-mail:  jonathan.willis@kc.frb.org

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