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Misclassification Errors and the Underestimation of U.S. Unemployment Rates

Author

Listed:
  • Feng, Shuaizhang

    () (Shanghai University of Finance and Economics)

  • Hu, Yingyao

    () (Johns Hopkins University)

Abstract

Using recent results in the measurement error literature, we show that the official U.S. unemployment rates substantially underestimate the true levels of unemployment, due to misclassification errors in labor force status in Current Population Surveys. Our closed-form identification of the misclassification probabilities relies on the key assumptions that the misreporting behaviors only depend on the true values and that the true labor force status dynamics satisfy a Markov-type property. During the period of 1996 to 2009, the corrected monthly unemployment rates are 1 to 4.6 percentage points (25% to 45%) higher than the official rates, and are more sensitive to changes in business cycles. Labor force participation rates, however, are not affected by this correction. We also provide results for various subgroups of the U.S. population defined by gender, race and age.

Suggested Citation

  • Feng, Shuaizhang & Hu, Yingyao, 2010. "Misclassification Errors and the Underestimation of U.S. Unemployment Rates," IZA Discussion Papers 5057, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp5057
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    References listed on IDEAS

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    1. Henry S. Farber, 1999. "Alternative and Part-Time Employment Arrangements as a Response to Job Loss," NBER Working Papers 7002, National Bureau of Economic Research, Inc.
    2. Stephen R. G. Jones & W. Craig Riddell, 1999. "The Measurement of Unemployment: An Empirical Approach," Econometrica, Econometric Society, vol. 67(1), pages 147-162, January.
    3. Dean R. Hyslop, 1999. "State Dependence, Serial Correlation and Heterogeneity in Intertemporal Labor Force Participation of Married Women," Econometrica, Econometric Society, vol. 67(6), pages 1255-1294, November.
    4. Thierry Magnac & Michael Visser, 1999. "Transition Models With Measurement Errors," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 466-474, August.
    5. Hu, Yingyao, 2008. "Identification and estimation of nonlinear models with misclassification error using instrumental variables: A general solution," Journal of Econometrics, Elsevier, vol. 144(1), pages 27-61, May.
    6. Peracchi, Franco & Welch, Finis, 1995. "How representative are matched cross-sections? Evidence from the Current Population Survey," Journal of Econometrics, Elsevier, vol. 68(1), pages 153-179, July.
    7. Abowd, John M & Zellner, Arnold, 1985. "Estimating Gross Labor-Force Flows," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 254-283, June.
    8. Farber, Henry S, 1999. "Alternative and Part-Time Employment Arrangements as a Response to Job Loss," Journal of Labor Economics, University of Chicago Press, vol. 17(4), pages 142-169, October.
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    Cited by:

    1. Elsby, Michael W.L. & Hobijn, Bart & Şahin, Ayşegül, 2015. "On the importance of the participation margin for labor market fluctuations," Journal of Monetary Economics, Elsevier, vol. 72(C), pages 64-82.
    2. Jung, Philip & Kuhn, Moritz, 2012. "Earnings losses and labor mobility over the life-cycle," MPRA Paper 40287, University Library of Munich, Germany.
    3. Hyslop, Dean R. & Townsend, Wilbur, 2017. "Employment misclassification in survey and administrative reports," Economics Letters, Elsevier, vol. 155(C), pages 19-23.
    4. Guerrazzi, Marco & Ksebi, Ilham, 2018. "Measuring unemployment by means of official data and administrative records: Empirical and theoretical perspectives," MPRA Paper 87227, University Library of Munich, Germany.
    5. repec:eee:jcecon:v:45:y:2017:i:2:p:304-324 is not listed on IDEAS
    6. Shuaizhang Feng & Yingyao Hu & Robert Moffitt, 2015. "Long Run Trends in Unemployment and Labor Force Participation in China," NBER Working Papers 21460, National Bureau of Economic Research, Inc.
    7. Michael Elsby & Bart Hobijn & Sahin, Aysegül, 2013. "On the Importance of the Participation Margin for Market Fluctuations," Working Paper Series 2013-05, Federal Reserve Bank of San Francisco.
    8. DiTraglia, Francis J. & García-Jimeno, Camilo, 2019. "Identifying the effect of a mis-classified, binary, endogenous regressor," Journal of Econometrics, Elsevier, vol. 209(2), pages 376-390.
    9. repec:spr:izamig:v:8:y:2018:i:1:d:10.1186_s40176-018-0125-7 is not listed on IDEAS
    10. John Komlos, 2019. "The Real U.S. Unemployment Rate Is Twice the Official Rate, and the Phillips Curve," CESifo Working Paper Series 7859, CESifo Group Munich.
    11. Lu, Ruichang & Luo, Yao & Xiao, Ruli, 2014. "An MPEC estimator for misclassification models," Economics Letters, Elsevier, vol. 125(2), pages 195-199.
    12. Ragui Assaad & Caroline Krafft & Shaimaa Yassin, 2018. "Comparing retrospective and panel data collection methods to assess labor market dynamics," IZA Journal of Migration and Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 8(1), pages 1-34, December.
    13. Ng, Travis, 2014. "Bailing outsourcing," Journal of Comparative Economics, Elsevier, vol. 42(4), pages 983-993.
    14. Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
    15. Zhang, Yinjunjie & Xu, Zhicheng Phil & Palma, Marco A., 2017. "Misclassification Errors of Subjective Well-being: A New Approach to Mapping Happiness," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258553, Agricultural and Applied Economics Association.
    16. repec:bla:ecinqu:v:56:y:2018:i:3:p:1846-1869 is not listed on IDEAS
    17. Feng, Shuaizhang & Hu, Yingyao & Sun, Jiandong, 2018. "On the robustness of alternative unemployment measures," Economics Letters, Elsevier, vol. 166(C), pages 1-5.
    18. Jung, Philip & Kuhn, Moritz, 2012. "Earnings Losses and Labor Mobility over the Lifecycle," IZA Discussion Papers 6835, Institute of Labor Economics (IZA).
    19. Meyer, Bruce D. & Mittag, Nikolas, 2017. "Misclassification in binary choice models," Journal of Econometrics, Elsevier, vol. 200(2), pages 295-311.
    20. Feng, Shuaizhang & Guo, Naijia, 2019. "Labor Market Dynamics in Urban China and the Role of the State Sector," IZA Discussion Papers 12170, Institute of Labor Economics (IZA).
    21. Andrew C. Chang & Phillip Li, 2018. "Measurement Error In Macroeconomic Data And Economics Research: Data Revisions, Gross Domestic Product, And Gross Domestic Income," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1846-1869, July.
    22. Shuaizhang Feng & Naijia Guo, 2019. "Labor Market Dynamics in Urban China and the Role of the State Sector," Working Papers 2019-008, Human Capital and Economic Opportunity Working Group.
    23. Nikolay Gospodinov & Ivana Komunjer & Serena Ng, 2014. "Minimum Distance Estimation of Dynamic Models with Errors-In-Variables," FRB Atlanta Working Paper 2014-11, Federal Reserve Bank of Atlanta.
    24. John Komlos, 2019. "Estimating Labor Market Slack, U.S. 1994-2019," CESifo Working Paper Series 7941, CESifo Group Munich.
    25. Yingyao Hu, 2015. "Microeconomic models with latent variables: applications of measurement error models in empirical industrial organization and labor economics," CeMMAP working papers CWP03/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    More about this item

    Keywords

    Current Population Survey; unemployment rate; labor force participation rate; misclassification; measurement error;

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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