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Measuring Labor Earnings Inequality using Public-Use March Current Population Survey Data: The Value of Including Variances and Cell Means When Imputing Topcoded Values

Author

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  • Richard V. Burkhauser
  • Shuaizhang Feng
  • Jeff Larrimore
Abstract
Using the Census Bureau's internal March Current Population Surveys (CPS) file, we construct and make available variances and cell means for all topcoded income values in the public-use version of these data. We then provide a procedure that allows researchers with access only to the public-use March CPS data to take advantage of this added information when imputing its topcoded income values. As an example of its value we show how our new procedure improves on existing imputation methods in the labor earnings inequality literature.

Suggested Citation

  • Richard V. Burkhauser & Shuaizhang Feng & Jeff Larrimore, 2008. "Measuring Labor Earnings Inequality using Public-Use March Current Population Survey Data: The Value of Including Variances and Cell Means When Imputing Topcoded Values," NBER Working Papers 14458, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:14458
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    References listed on IDEAS

    as
    1. Richard V. Burkhauser & Shuaizhang Feng & Stephen P. Jenkins, 2009. "Using The P90/P10 Index To Measure U.S. Inequality Trends With Current Population Survey Data: A View From Inside The Census Bureau Vaults," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(1), pages 166-185, March.
    2. Richard Burkhauser & Shuaizhang Feng & Stephen Jenkins & Jeff Larrimore, 2011. "Estimating trends in US income inequality using the Current Population Survey: the importance of controlling for censoring," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(3), pages 393-415, September.
    3. Juhn, Chinhui & Murphy, Kevin M & Pierce, Brooks, 1993. "Wage Inequality and the Rise in Returns to Skill," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 410-442, June.
    4. Bishop, John A & Chiou, Jong-Rong & Formby, John P, 1994. "Truncation Bias and the Ordinal Evaluation of Income Inequality," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(1), pages 123-127, January.
    5. Thomas Lemieux, 2006. "Increasing Residual Wage Inequality: Composition Effects, Noisy Data, or Rising Demand for Skill?," American Economic Review, American Economic Association, vol. 96(3), pages 461-498, June.
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    Cited by:

    1. Stephen P. Jenkins & Richard V. Burkhauser & Shuaizhang Feng & Jeff Larrimore, 2009. "Measuring Inequality Using Censored Data: A Multiple Imputation Approach," Discussion Papers of DIW Berlin 866, DIW Berlin, German Institute for Economic Research.
    2. Burkhauser, Richard V. & Feng, Shuaizhang & Larrimore, Jeff, 2010. "Improving imputations of top incomes in the public-use current population survey by using both cell-means and variances," Economics Letters, Elsevier, vol. 108(1), pages 69-72, July.

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    More about this item

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

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