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On The Sources And Size Of Employment Adjustment Costs

  • Lucia Foster

Micro employment adjustment costs affect not only establishment-level dynamics but can also affect aggregate employment dynamics. The difficulties in directly observing and measuring these adjustment costs necessitate an indirect approach in order to learn more about the sources and size of these costs. This paper examines differences in employment adjustments by worker and establishment characteristics using micro-level data for approximately 11,000 U.S. manufacturing plants. Differences in the speed of adjustment within the organizing framework of the traditional partial adjustment model are used to identify the source and size of employment adjustment costs. The estimates are undertaken using three different techniques and under a variety of assumptions concerning market structure, worker heterogeneity, and degree of interrelation of inputs. The estimates show that employment adjustment speeds differ over worker and establishment characteristics in a manner that is consistent with the underlying adjustment cost stories. These differences suggest that systematic changes in the distribution of establishments over these characteristics can influence aggregate employment dynamics in response to a shock through compositional effects.

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Paper provided by Center for Economic Studies, U.S. Census Bureau in its series Working Papers with number 99-7.

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Date of creation: May 1999
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Handle: RePEc:cen:wpaper:99-7
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  1. Ricardo J. Caballero & Eduardo Engel & John Haltiwanger, 1996. "Aggregate Employment Dynamics: Building from Microeconomic Evidence," Documentos de Trabajo 6, Centro de Economía Aplicada, Universidad de Chile.
  2. Katharine G. Abraham & Susan N. Houseman, 1993. "Job Security and Work Force Adjustment: How Different are U.S. and Japanese Practices?," Book chapters authored by Upjohn Institute researchers, in: Christopher F. Buechtemann (ed.), Employment Security and Labor Market Behavior: Interdisciplinary Approaches and International Evidence, pages 180-199 W.E. Upjohn Institute for Employment Research.
  3. James D Adams & Adam B Jaffe, 1994. "The Span of the Effect of R&D in the Firm and Industry," Working Papers 94-7, Center for Economic Studies, U.S. Census Bureau.
  4. Beggs, John J. & Nerlove, Marc, 1988. "Biases in dynamic models with fixed effects," Economics Letters, Elsevier, vol. 26(1), pages 29-31.
  5. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
  6. Bresson, G & Kramarz, F & Sevestre, P, 1992. "Heterogeneous Labor and the Dynamics of Aggregate Labor Demand: Some Estimations Using Panel Data," Empirical Economics, Springer, vol. 17(1), pages 153-68.
  7. Eric J. Bartelsman & Wayne Gray, 1996. "The NBER Manufacturing Productivity Database," NBER Technical Working Papers 0205, National Bureau of Economic Research, Inc.
  8. Caballero, Ricardo J & Engel, Eduardo M R A, 1993. "Microeconomic Adjustment Hazards and Aggregate Dynamics," The Quarterly Journal of Economics, MIT Press, vol. 108(2), pages 359-83, May.
  9. Bergstrom, Villy & Panas, Epaminondas E, 1992. "How Robust Is the Capital-Skill Complementarity Hypothesis?," The Review of Economics and Statistics, MIT Press, vol. 74(3), pages 540-46, August.
  10. Berman, Eli & Bound, John & Griliches, Zvi, 1994. "Changes in the Demand for Skilled Labor within U.S. Manufacturing: Evidence from the Annual Survey of Manufactures," The Quarterly Journal of Economics, MIT Press, vol. 109(2), pages 367-97, May.
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