IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp5512.html
   My bibliography  Save this paper

Does It Matter Who Responded to the Survey? Trends in the U.S. Gender Earnings Gap Revisited

Author

Listed:
  • Lee, Jungmin

    (Seoul National University)

  • Lee, Sokbae

    (Institute for Fiscal Studies, London)

Abstract

Blau and Kahn (JOLE, 1997; ILRR, 2006) decomposed trends in the U.S. gender earnings gap into observable and unobservable components using the PSID. They found that the unobservable part contributed significantly not only to the rapidly shrinking earnings gap in the 1980s, but also to the slowing-down of the convergence in the 1990s. In this paper, we extend their framework to consider measurement error due to the use of proxy/representative respondents. First, we document a strong trend of changing gender composition of household-representative respondents toward more females. Second, we estimate the impact of the changing gender composition on Blau and Kahn's decomposition. We find that a non-ignorable portion of changes in the gender gap could be attributed to changes in the self/proxy respondent composition. Specifically, the actual reduction in the gender gap can be smaller than what the estimates without taking into account the measurement error might suggest. We conclude that a careful validation study would be necessary to ascertain the magnitude of the spurious measurement error effects.

Suggested Citation

  • Lee, Jungmin & Lee, Sokbae, 2011. "Does It Matter Who Responded to the Survey? Trends in the U.S. Gender Earnings Gap Revisited," IZA Discussion Papers 5512, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp5512
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp5512.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Reuben Gronau & Daniel S. Hamermesh, 2008. "The Demand for Variety: A Household Production Perspective," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 562-572, August.
    2. Francine D. Blau & Lawrence M. Kahn, 2006. "The U.S. Gender Pay Gap in the 1990S: Slowing Convergence," ILR Review, Cornell University, ILR School, vol. 60(1), pages 45-66, October.
    3. Mathiowetz, Nancy A & Duncan, Greg J, 1988. "Out of Work, Out of Mind: Response Errors in Retrospective Reports of Unemployment," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 221-229, April.
    4. Bound, John & Krueger, Alan B, 1991. "The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?," Journal of Labor Economics, University of Chicago Press, vol. 9(1), pages 1-24, January.
    5. Blau, Francine D & Kahn, Lawrence M, 1997. "Swimming Upstream: Trends in the Gender Wage Differential in 1980s," Journal of Labor Economics, University of Chicago Press, vol. 15(1), pages 1-42, January.
    6. Pischke, Jorn-Steffen, 1995. "Measurement Error and Earnings Dynamics: Some Estimates from the PSID Validation Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 305-314, July.
    7. Bollinger, Christopher R, 1998. "Measurement Error in the Current Population Survey: A Nonparametric Look," Journal of Labor Economics, University of Chicago Press, vol. 16(3), pages 576-594, July.
    8. Mellow, Wesley & Sider, Hal, 1983. "Accuracy of Response in Labor Market Surveys: Evidence and Implications," Journal of Labor Economics, University of Chicago Press, vol. 1(4), pages 331-344, October.
    9. Kristensen, Nicolai & Westergård-Nielsen, Niels C., 2006. "A Large-Scale Validation Study of Measurement Errors in Longitudinal Survey Data," IZA Discussion Papers 2329, Institute of Labor Economics (IZA).
    10. Christopher R. Bollinger, 2001. "Response Error and the Union Wage Differential," Southern Economic Journal, John Wiley & Sons, vol. 68(1), pages 60-76, July.
    11. 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 508-532, October.
    12. Christopher R. Bollinger, 2003. "Measurement Error in Human Capital and the Black-White Wage Gap," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 578-585, August.
    13. 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.
    14. Mroz, Thomas A, 1987. "The Sensitivity of an Empirical Model of Married Women's Hours of Work to Economic and Statistical Assumptions," Econometrica, Econometric Society, vol. 55(4), pages 765-799, July.
    15. Bound, John & Brown, Charles & Duncan, Greg J & Rodgers, Willard L, 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 345-368, July.
    16. repec:pri:indrel:dsp01gb19f581g is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Christopher R. Bollinger & Barry T. Hirsch, 2013. "Is Earnings Nonresponse Ignorable?," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 407-416, May.
    2. Misty Heggeness & Marta Murray-Close, 2019. "Manning Up and Womaning Down: How Husbands and Wives Report Earnings When She Earns More," Opportunity and Inclusive Growth Institute Working Papers 28, Federal Reserve Bank of Minneapolis.
    3. Jose Galdo & Ana C Dammert & Degnet Abebaw, 2021. "Gender Bias in Agricultural Child Labor: Evidence from Survey Design Experiments," The World Bank Economic Review, World Bank, vol. 35(4), pages 872-891.
    4. Anja Roth & Michaela Slotwinski, 2018. "Gender Norms and Income Misreporting within Households," CESifo Working Paper Series 7298, CESifo.
    5. Christopher R. Bollinger & Barry T. Hirsch, 2010. "GDP & Beyond – die europäische Perspektive," RatSWD Working Papers 165, German Data Forum (RatSWD).
    6. Bollinger, Christopher R. & Hirsch, Barry & Hokayem, Charles M. & Ziliak, James P., 2018. "Trouble in the Tails? What We Know about Earnings Nonresponse Thirty Years after Lillard, Smith, and Welch," IZA Discussion Papers 11710, Institute of Labor Economics (IZA).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Christopher R. Bollinger & Amitabh Chandra, 2005. "Iatrogenic Specification Error: A Cautionary Tale of Cleaning Data," Journal of Labor Economics, University of Chicago Press, vol. 23(2), pages 235-258, April.
    2. Lynn, Peter & Jäckle, Annette & Sala, Emanuela & P. Jenkins, Stephen, 2004. "Validation of survey data on income and employment: the ISMIE experience," ISER Working Paper Series 2004-14, Institute for Social and Economic Research.
    3. Bollinger, Christopher R. & Hirsch, Barry & Hokayem, Charles M. & Ziliak, James P., 2018. "Trouble in the Tails? What We Know about Earnings Nonresponse Thirty Years after Lillard, Smith, and Welch," IZA Discussion Papers 11710, Institute of Labor Economics (IZA).
    4. de Nicola, Francesca & Giné, Xavier, 2014. "How accurate are recall data? Evidence from coastal India," Journal of Development Economics, Elsevier, vol. 106(C), pages 52-65.
    5. Brownstone, David & Valletta, Robert G, 1996. "Modeling Earnings Measurement Error: A Multiple Imputation Approach," The Review of Economics and Statistics, MIT Press, vol. 78(4), pages 705-717, November.
    6. Arie Kapteyn & Jelmer Y. Ypma, 2007. "Measurement Error and Misclassification: A Comparison of Survey and Administrative Data," Journal of Labor Economics, University of Chicago Press, vol. 25(3), pages 513-551.
    7. Cyrille Hagneré & Arnaud Lefranc, 2006. "Étendue et conséquences des erreurs de mesure dans les données individuelles d'enquête : une évaluation à partir des données appariées des enquêtes emploi et revenus fiscaux," Post-Print hal-01651144, HAL.
    8. Kristensen, Nicolai & Westergård-Nielsen, Niels C., 2006. "A Large-Scale Validation Study of Measurement Errors in Longitudinal Survey Data," IZA Discussion Papers 2329, Institute of Labor Economics (IZA).
    9. Peter Gottschalk & Minh Huynh, 2010. "Are Earnings Inequality and Mobility Overstated? The Impact of Nonclassical Measurement Error," The Review of Economics and Statistics, MIT Press, vol. 92(2), pages 302-315, May.
    10. Paulus, Alari, 2015. "Tax evasion and measurement error: An econometric analysis of survey data linked with tax records," ISER Working Paper Series 2015-10, Institute for Social and Economic Research.
    11. Adam Bee & Joshua Mitchell & Nikolas Mittag & Jonathan Rothbaum & Carl Sanders & Lawrence Schmidt & Matthew Unrath, 2023. "National Experimental Wellbeing Statistics - Version 1," Working Papers 23-04, Center for Economic Studies, U.S. Census Bureau.
    12. ChangHwan Kim & Christopher R. Tamborini, 2014. "Response Error in Earnings," Sociological Methods & Research, , vol. 43(1), pages 39-72, February.
    13. John Abowd & Martha Stinson, 2011. "Estimating Measurement Error in SIPP Annual Job Earnings: A Comparison of Census Bureau Survey and SSA Administrative Data," Working Papers 11-20, Center for Economic Studies, U.S. Census Bureau.
    14. Akee, Randall K. Q., 2007. "Errors in Self-Reported Earnings: The Role of Previous Earnings Volatility," IZA Discussion Papers 3263, Institute of Labor Economics (IZA).
    15. Whalley, Alexander, 2011. "Education and labor market risk: Understanding the role of data cleaning," Economics of Education Review, Elsevier, vol. 30(3), pages 528-545, June.
    16. Burt S. Barnow & David Greenberg, 2015. "Do Estimated Impacts on Earnings Depend on the Source of the Data Used to Measure Them? Evidence From Previous Social Experiments," Evaluation Review, , vol. 39(2), pages 179-228, April.
    17. John Bound & Charles Brown & Greg J. Duncan & Willard L. Rodgers, 1989. "Measurement Error In Cross-Sectional and Longitudinal Labor Market Surveys: Results From Two Validation Studies," NBER Working Papers 2884, National Bureau of Economic Research, Inc.
    18. Javier Escobal & Sonia Laszlo, 2008. "Measurement Error in Access to Markets," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(2), pages 209-243, April.
    19. Bollinger, Christopher R, 1998. "Measurement Error in the Current Population Survey: A Nonparametric Look," Journal of Labor Economics, University of Chicago Press, vol. 16(3), pages 576-594, July.
    20. Jesse Bricker & Gary V. Engelhardt, 2007. "Measurement Error in Earnings Data in the Health and Retirement Study," Working Papers, Center for Retirement Research at Boston College wp2007-16, Center for Retirement Research, revised Oct 2007.

    More about this item

    Keywords

    gender earnings gap; survey response error; proxy response;
    All these keywords.

    JEL classification:

    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp5512. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.