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Why Do Fixed-Effects Models Perform So Poorly? The Case of Academic Salaries

  • Daniel S. Hamermesh

A large and growing line of research has used longitudinal data to eliminate unobservable individual effects that may bias cross-section parameter estimates. The resulting estimates, though unbiased, are generally quite imprecise. This study shows that the imprecision can arise from the measurement error that commonly exists in the data used to represent the dependent variable in these studies. The example of economists' salaries, which are administrative data free of measurement error, demonstrates that estimates based on changes in longitudinal data can be precise. The results indicate the importance of improving the measurement of the variables to which the increasingly high-powered techniques designed to analyze panel data are applied. The estimates also indicate that the payoff to citations to scholarly work is not an artifact of unmeasured individual effects that could be biasing previous estimates of the determinants of academic salaries.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 2135.

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Date of creation: Jan 1987
Date of revision:
Publication status: published as Southern Economic Journal, Vol.56, No. 1, pp. 39-45, (July 1989).
Handle: RePEc:nbr:nberwo:2135
Note: LS
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  1. Douglas Holtz-Eakin & Whitney K. Newey & Harvey S. Rosen, 1989. "Implementing Causality Tests with Panel Data, with an Example from LocalPublic Finance," NBER Technical Working Papers 0048, National Bureau of Economic Research, Inc.
  2. Breusch, T S & Pagan, A R, 1980. "The Lagrange Multiplier Test and Its Applications to Model Specification in Econometrics," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 239-53, January.
  3. Freeman, Richard Barry, 1984. "Longitudinal Analyses of the Effects of Trade Unions," Scholarly Articles 4631951, Harvard University Department of Economics.
  4. Duncan, Greg J & Stafford, Frank P, 1980. "Do Union Members Receive Compensating Wage Differentials?," American Economic Review, American Economic Association, vol. 70(3), pages 355-71, June.
  5. Griliches, Zvi & Hausman, Jerry A., 1986. "Errors in variables in panel data," Journal of Econometrics, Elsevier, vol. 31(1), pages 93-118, February.
  6. Duncan, Greg J & Hill, Daniel H, 1985. "An Investigation of the Extent and Consequences of Measurement Error in Labor-Economic Survey Data," Journal of Labor Economics, University of Chicago Press, vol. 3(4), pages 508-32, October.
  7. Brown, Charles, 1980. "Equalizing Differences in the Labor Market," The Quarterly Journal of Economics, MIT Press, vol. 94(1), pages 113-34, February.
  8. Edward P. Lazear, 1974. "Age, Experience and Wage Growth," NBER Working Papers 0051, National Bureau of Economic Research, Inc.
  9. Chowdhury, Gopa & Nickell, Stephen, 1985. "Hourly Earnings in the United States: Another Look at Unionization, Schooling, Sickness, and Unemployment Using PSID Data," Journal of Labor Economics, University of Chicago Press, vol. 3(1), pages 38-69, January.
  10. Gary Solon, 1986. "Bias in Longitudinal Estimation of Wage Gaps," NBER Technical Working Papers 0058, National Bureau of Economic Research, Inc.
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