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The Feasibility and Importance of Adding Measures of Actual Experience to Cross-Sectional Data Collection

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  • Francine D. Blau
  • Lawrence M. Kahn

Abstract

We use Michigan Panel Study of Income Dynamics data and data from a 2008 telephone survey of adults conducted by Westat for the Princeton Data Improvement Initiative (PDII) to explore the importance and feasibility of adding retrospective questions about actual work experience to cross-sectional data sets. We demonstrate that having such actual experience data is important for analyzing women's post-school human capital accumulation, residual wage inequality, and the gender pay gap. Further, our PDII survey results show that it is feasible to collect actual experience data in cross-sectional telephone surveys like the March Current Population Survey annual supplement.

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  • Francine D. Blau & Lawrence M. Kahn, 2011. "The Feasibility and Importance of Adding Measures of Actual Experience to Cross-Sectional Data Collection," NBER Working Papers 17241, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:17241
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    1. The Feasibility and Importance of Adding Measures of Actual Experience to Cross-Sectional Data Collection
      by maximorossi in NEP-LTV blog on 2011-08-10 22:05:55

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    Cited by:

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    2. Francine D. Blau & Lawrence M. Kahn, 2017. "The Gender Wage Gap: Extent, Trends, and Explanations," Journal of Economic Literature, American Economic Association, vol. 55(3), pages 789-865, September.
    3. Katie Meara & Francesco Pastore & Allan Webster, 2020. "The gender pay gap in the USA: a matching study," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(1), pages 271-305, January.
    4. Carl Lin, 2016. "How Do Immigrants From Taiwan Fare In The U.S. Labor Market?," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 61(05), pages 1-38, December.
    5. Morris M. Kleiner & Alan B. Krueger, 2013. "Analyzing the Extent and Influence of Occupational Licensing on the Labor Market," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 173-202.
    6. L. Rachel Ngai & Barbara Petrongolo, 2017. "Gender Gaps and the Rise of the Service Economy," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(4), pages 1-44, October.
    7. Maria Esther Oswald-Egg & Ursula Renold, 2019. "No Experience, No Employment: The Effect of Vocational Education and Training Work Experience on Labour Market Outcomes after Higher Education," KOF Working papers 19-469, KOF Swiss Economic Institute, ETH Zurich.
    8. Raitano Michele & Vona Francesco, 2018. "From the Cradle to the Grave: The Influence of Family Background on the Career Path of Italian Men," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(6), pages 1062-1088, December.
    9. Estrella Gomez-Herrera & Frank Müller-Langer, 2019. "Is There a Gender Wage Gap in Online Labor Markets? Evidence from Over 250,000 Projects and 2.5 Million Wage Bill Proposals," CESifo Working Paper Series 7779, CESifo.
    10. Santos, Sérgio P. & São José, José M.S., 2018. "Measuring and decomposing the gender pay gap: A new frontier approachAuthor-Name: Amado, Carla A.F," European Journal of Operational Research, Elsevier, vol. 271(1), pages 357-373.
    11. Maurizio Franzini & Fabrizio Patriarca & Michele Raitano, 0. "Market competition and parental background wage premium: the role of human and relational capital," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 0, pages 1-27.
    12. Jeffrey T. Denning & Brian Jacob & Lars Lefgren & Christian vom Lehn, 2019. "The Return to Hours Worked Within and Across Occupations: Implications for the Gender Wage Gap," NBER Working Papers 25739, National Bureau of Economic Research, Inc.
    13. Oswald-Egg, Maria Esther & Renold, Ursula, 2021. "No experience, no employment: The effect of vocational education and training work experience on labour market outcomes after higher education," Economics of Education Review, Elsevier, vol. 80(C).
    14. Rebekka Christopoulou & Theodora Kosma, 2009. "Skills and Wage Inequality in Greece: Evidence from Matched Employer-Employee Data, 1995-2002," GreeSE – Hellenic Observatory Papers on Greece and Southeast Europe 26, Hellenic Observatory, LSE.
    15. Kevin F. Hallock, 2013. "Data Improvement and Labor Economics," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 1-16.
    16. Yekaterina Chzhen & Karen Mumford & Catia Nicodemo, 2013. "The Gender Pay Gap in the Australian Private Sector: Is Selection Relevant Across the Earnings Distribution?," The Economic Record, The Economic Society of Australia, vol. 89(286), pages 367-381, September.
    17. Zveglich, Joseph E. & van der Meulen Rodgers, Yana & Laviña, Editha A., 2019. "Expected work experience and the gender wage gap: A new human capital measure," Economic Modelling, Elsevier, vol. 83(C), pages 372-383.
    18. Maurizio Franzini & Fabrizio Patriarca & Michele Raitano, 2020. "Market competition and parental background wage premium: the role of human and relational capital," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(3), pages 291-317, September.
    19. Braga, Breno, 2018. "Earnings dynamics: The role of education throughout a worker’s career," Labour Economics, Elsevier, vol. 52(C), pages 83-97.

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    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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