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Errors in Self-Reported Earnings: The Role of Previous Earnings Volatility

  • Akee, Randall K. Q.


    (University of California, Los Angeles)

I report the measurement error in self-reported earnings for a developing country. Administrative data from the Federated States of Micronesia’s (FSM) Social Security office are matched to the FSM Census data for the wage sector employed. I find that the error in annual self-reported earnings is centered on zero but less efficient than results from the US. Additionally the error is not classical in nature – I find evidence for mean reversion in the data. Using previous annual earnings history contained in the FSM Social Security data, I construct accurate measures of past deviations of administratively recorded earnings to identify the impact of transitory income on current reporting of earnings. Prior earnings volatility is an important determinant of the error in earnings for the current period. However, the effect of prior shocks diminish significantly over time – suggesting that information on transitory income shocks will be helpful in evaluating the usefulness of self-reported earnings measures in applied work. Finally, I use information on an exogenous and transitory shock to FSM household incomes (typhoons) to correct for errors in self-reported earnings. I find that the coefficients from these corrected regressions approach those that use administrative data on earnings in a consumption regression.

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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 3263.

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Length: 36 pages
Date of creation: Dec 2007
Date of revision:
Publication status: published in: Journal of Development Economics, 2011, 96 (2), 409 - 421
Handle: RePEc:iza:izadps:dp3263
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  1. Peter Gottschalk & Minh Huynh, 2006. "Are Earnings Inequality and Mobility Overstated? The Impact of Non-Classical Measurement Error," Boston College Working Papers in Economics 649, Boston College Department of Economics.
  2. 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.
  3. Robert A. Moffitt & Peter Gottschalk, 2002. "Trends in the Transitory Variance of Earnings in the United States," Economic Journal, Royal Economic Society, vol. 112(478), pages C68-C73, March.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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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