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Downward Nominal Wage Flexibility: Real or Measurement Error?

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  • Gottschalk, Peter T.

    ()
    (Boston College)

Abstract

This paper presents a new method to correct for measurement error in wage data and applies this method to address an old question. How much downward wage flexibility is there in the U.S? We apply standard methods developed by Bai and Perron (1998b) to identify structural breaks in time series data. Applying these methods to wage histories allows us to identify when each person experienced a change in nominal wages. The length of the period of constant nominal wages is left unrestricted and is allowed to differ across individuals, as is the size and direction of the nominal wage change. We apply these methods to data from the Survey of Income and Program Participation. The evidence we provide indicates that the probability of a cut in nominal wages is substantially overstated in data that is not corrected for measurement error.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 1327.

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Length: 35 pages
Date of creation: Oct 2004
Date of revision:
Publication status: published in: Review of Economics and Statistics, 2005, 87 (3), 556-568
Handle: RePEc:iza:izadps:dp1327

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Keywords: nominal wage rigidity; measurement error;

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  1. Bound, John & Krueger, Alan B, 1991. "The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?," Journal of Labor Economics, University of Chicago Press, vol. 9(1), pages 1-24, January.
  2. Michael P. Keane, 1990. "Nominal contracting theories of unemployment: evidence from panel data," Discussion Paper / Institute for Empirical Macroeconomics 27, Federal Reserve Bank of Minneapolis.
  3. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843 Elsevier.
  4. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
  5. Brown, James N & Light, Audrey, 1992. "Interpreting Panel Data on Job Tenure," Journal of Labor Economics, University of Chicago Press, vol. 10(3), pages 219-57, July.
  6. George A. Akerlof & William R. Dickens & George L. Perry, 1996. "The Macroeconomics of Low Inflation," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 27(1), pages 1-76.
  7. Alan S. Blinder & Don H. Choi, 1989. "A Shred of Evidence on Theories of Wage Stickiness," NBER Working Papers 3105, National Bureau of Economic Research, Inc.
  8. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
  9. Bound, John, et al, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-68, July.
  10. David Card & Dean Hyslop, 1997. "Does Inflation “Grease the Wheels of the Labor Market”?," NBER Chapters, in: Reducing Inflation: Motivation and Strategy, pages 71-122 National Bureau of Economic Research, Inc.
  11. McLaughlin, Kenneth J., 1994. "Rigid wages?," Journal of Monetary Economics, Elsevier, vol. 34(3), pages 383-414, December.
  12. Joseph G. Altonji & Paul J. Devereux, 1999. "The Extent and Consequences of Downward Nominal Wage Rigidity," NBER Working Papers 7236, National Bureau of Economic Research, Inc.
  13. Kahn, Shulamit, 1997. "Evidence of Nominal Wage Stickiness from Microdata," American Economic Review, American Economic Association, vol. 87(5), pages 993-1008, December.
  14. Shea, John, 1995. "Union Contracts and the Life-Cycle/Permanent-Income Hypothesis," American Economic Review, American Economic Association, vol. 85(1), pages 186-200, March.
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