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The labor supply response to (mismeasured but) predictable wage changes

  • Eric French

Problems with measurement error have led many researchers to criticize panel data studies of intertemporal labor supply. In this study I address the measurement error problems explicitly. I estimate the properties of measurement error in the Panel Study of Income Dynamics Validation Study. I then use this information about measurement error to purge measurement error from the Panel Study of Income Dynamics. I show there exists a large transitory wage changes predictably disappear. When estimating the labor supply response to these predictable wage changes, I account for serially correlated measurement error and for measurement error that is correlated with true hours and wages. I find almost no correlation between hours worked and predictable wage changes. Therefore, failure to control for measurement error cannot explain the low estimated labor supply elasticities in other papers.

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Paper provided by Federal Reserve Bank of Chicago in its series Working Paper Series with number WP-00-8.

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Date of creation: 2000
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Handle: RePEc:fip:fedhwp:wp-00-8
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  2. Pischke, J.S., 1994. "Measurement Error and Earnings Dynamics: Some Estimates from the PSID Validation Study," Working papers 94-01, Massachusetts Institute of Technology (MIT), Department of Economics.
  3. Casey B. Mulligan, 1999. "Substition over Time: Another Look at Life-Cycle Labor Supply," NBER Chapters, in: NBER Macroeconomics Annual 1998, volume 13, pages 75-152 National Bureau of Economic Research, Inc.
  4. John Bound & Alan B. Krueger, 1989. "The Extent of Measurement Error In Longitudinal Earnings Data: Do Two Wrongs Make A Right?," NBER Working Papers 2885, National Bureau of Economic Research, Inc.
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  7. Farber, Henry S & Gibbons, Robert, 1996. "Learning and Wage Dynamics," The Quarterly Journal of Economics, MIT Press, vol. 111(4), pages 1007-47, November.
  8. James P. Ziliak & Thomas J. Kniesner, 1999. "Estimating Life Cycle Labor Supply Tax Effects," Journal of Political Economy, University of Chicago Press, vol. 107(2), pages 326-359, April.
  9. Sherwin Rosen, 1985. "Implicit Contracts: A Survey," NBER Working Papers 1635, National Bureau of Economic Research, Inc.
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  14. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
  15. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
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  18. 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.
  19. Baker, Michael, 1997. "Growth-Rate Heterogeneity and the Covariance Structure of Life-Cycle Earnings," Journal of Labor Economics, University of Chicago Press, vol. 15(2), pages 338-75, April.
  20. Abowd, John M & Card, David, 1989. "On the Covariance Structure of Earnings and Hours Changes," Econometrica, Econometric Society, vol. 57(2), pages 411-45, March.
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  23. Heckman, James J, 1976. "A Life-Cycle Model of Earnings, Learning, and Consumption," Journal of Political Economy, University of Chicago Press, vol. 84(4), pages S11-44, August.
  24. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
  25. Carrington, William J, 1996. "The Alaskan Labor Market during the Pipeline Era," Journal of Political Economy, University of Chicago Press, vol. 104(1), pages 186-218, February.
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