IDEAS home Printed from https://ideas.repec.org/p/wiw/wiwrsa/ersa16p157.html
   My bibliography  Save this paper

Assessment of labour market returns in the case of gender unique human capital

Author

Listed:
  • Tiiu Paas
  • Maryna Tverdostup

Abstract

Maryna Tverdostup, Tiiu Paas, ERSA 2016: The paper focuses on the identification of the unique, non-reached by the opposite gender human capital and the analysis of its effect on the earning profiles of unique human capital holders. The overwhelming research aim is to better understand the possible reasons behind gender wage disparities, focusing on the unique features of male and female human capital and their returns. When assessing the gender pay disparities, variation of human capital characteristics across males and females is assumed to be one of the decisive factors of differences in the wage outcomes across gender groups. However, males and females may not only differ in the set of individual characteristics, but also the distributions of these variables can hardly overlap, inducing the issue which is commonly referred to as 'support problem?. Empirical part of the paper relies on the Survey of Adult Skills (PIAAC - Program for the International Assessment of Adult Competencies) data (OECD 2013), including the estimates of cognitive abilities in literacy, numeracy and problem solving in technology-rich environment. We develop our empirical study using PIAAC national database for Estonia as a small, rapidly developing European economy characterized by high rate of female labor force participation and gender wage disparities. The issue of gender wage disparities is especially topical in the case of small and developing economies where labour markets are particularly sensitive to any gaps in returns to labour. Therefore, we believe that Estonian case is relevant in a wage gap research framework allowing making certain generalizations that will be of particular policy value for other relatively quickly developing economies and regions, where women's labour participation rate is high and/or has a tendency to increase. In this paper, the unique, non-reached by the opposite gender human capital is identified and its effect on the earning profiles of unique human capital holders is analysed implementing several matching procedures and non-parametric decomposition. The results of the study show that the unique combination of skills, as a main component of the human capital, reached by males and females and unattained by opposite gender is one of the key sources of gender disparity in a human capital. The results revealed that male-unique human capital is at large extent embodied in combination of outstanding numerical and problem solving abilities, being often a strong competitive advantage of males. All in all, the novel perspective towards gender disparities in human capital and introducing a concept of gender-unique human capital within the wage gap framework, proved that men's and women's profiles cannot be directly compared, as particular characteristics are exclusive for certain gender. Ignoring this notion leads to overestimation of discriminatory labor market effects and thus imprecise wage inequality estimation.

Suggested Citation

  • Tiiu Paas & Maryna Tverdostup, 2016. "Assessment of labour market returns in the case of gender unique human capital," ERSA conference papers ersa16p157, European Regional Science Association.
    • Handle: RePEc:wiw:wiwrsa:ersa16p157
    as

    Download full text from publisher

    File URL: https://www-sre.wu.ac.at/ersa/ersaconfs/ersa16/Paper157_MarynaTverdostup.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bertrand, Marianne, 2011. "New Perspectives on Gender," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 17, pages 1543-1590, Elsevier.
    2. David Neumark & Roy J. Bank & Kyle D. Van Nort, 1996. "Sex Discrimination in Restaurant Hiring: An Audit Study," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(3), pages 915-941.
    3. DiNardo, John & Fortin, Nicole M & Lemieux, Thomas, 1996. "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach," Econometrica, Econometric Society, vol. 64(5), pages 1001-1044, September.
    4. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    5. Sangeeta Pratap & Erwan Quintin, 2001. "Are labor markets segmented in Argentina? a semiparametric approach," Center for Latin America Working Papers 0701, Federal Reserve Bank of Dallas.
    6. 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.
    7. Hanushek, Eric A. & Schwerdt, Guido & Wiederhold, Simon & Woessmann, Ludger, 2015. "Returns to skills around the world: Evidence from PIAAC," European Economic Review, Elsevier, vol. 73(C), pages 103-130.
    8. Christofides, Louis N. & Polycarpou, Alexandros & Vrachimis, Konstantinos, 2013. "Gender wage gaps, ‘sticky floors’ and ‘glass ceilings’ in Europe," Labour Economics, Elsevier, vol. 21(C), pages 86-102.
    9. Vassil, Kristjan & Eamets, Raul & Mõtsmees, Pille, 2014. "Socio-demographic Model of Gender Gap in Expected and Actual Wages in Estonia," IZA Discussion Papers 8604, Institute of Labor Economics (IZA).
    10. Solomon W. Polachek & Jun Xiang, 2009. "The Gender Pay Gap across Countries: A Human Capital Approach," SOEPpapers on Multidisciplinary Panel Data Research 227, DIW Berlin, The German Socio-Economic Panel (SOEP).
    11. David Card & Ana Rute Cardoso & Patrick Kline, 2016. "Bargaining, Sorting, and the Gender Wage Gap: Quantifying the Impact of Firms on the Relative Pay of Women," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(2), pages 633-686.
    12. Flavio Cunha & James J. Heckman, 2008. "Formulating, Identifying and Estimating the Technology of Cognitive and Noncognitive Skill Formation," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
    13. Nicole M. Fortin, 2008. "The Gender Wage Gap among Young Adults in the United States: The Importance of Money versus People," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
    14. Catia Nicodemo & Raul Ramos, 2012. "Wage differentials between native and immigrant women in Spain," International Journal of Manpower, Emerald Group Publishing Limited, vol. 33(1), pages 118-136, March.
    15. O'Neill, June & Polachek, Solomon, 1993. "Why the Gender Gap in Wages Narrowed in the 1980s," Journal of Labor Economics, University of Chicago Press, vol. 11(1), pages 205-228, January.
    16. Nicodemo, Catia & Ramos, Raul, 2011. "Wage Differentials between Native and Immigrant Women in Spain: Accounting for Differences in the Supports," IZA Discussion Papers 5571, Institute of Labor Economics (IZA).
    17. Bas ter Weel, 2008. "The Noncognitive Determinants of Labor Market and Behavioral Outcomes: Introduction to the Symposium," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
    18. Donald B. Rubin, 1977. "Assignment to Treatment Group on the Basis of a Covariate," Journal of Educational and Behavioral Statistics, , vol. 2(1), pages 1-26, March.
    19. Albrecht, James & van Vuuren, Aico & Vroman, Susan, 2009. "Counterfactual distributions with sample selection adjustments: Econometric theory and an application to the Netherlands," Labour Economics, Elsevier, vol. 16(4), pages 383-396, August.
    20. Gary S. Becker, 1964. "Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, First Edition," NBER Books, National Bureau of Economic Research, Inc, number beck-5.
    21. Javier Alejo & Maria Florencia Gabrielli & Walter Sosa-Escudero, 2014. "The Distributive Effects of Education: An Unconditional Quantile Regression Approach," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 29(1), pages 53-76, April.
    22. James Albrecht & Anders Bjorklund & Susan Vroman, 2003. "Is There a Glass Ceiling in Sweden?," Journal of Labor Economics, University of Chicago Press, vol. 21(1), pages 145-177, January.
    23. Nopo, Hugo R. & Daza, Nancy & Ramos, Johanna, 2011. "Gender Earnings Gaps in the World," IZA Discussion Papers 5736, Institute of Labor Economics (IZA).
    24. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    25. Lin Xiu & Morley Gunderson, 2014. "Glass ceiling or sticky floor? Quantile regression decomposition of the gender pay gap in China," International Journal of Manpower, Emerald Group Publishing Limited, vol. 35(3), pages 306-326, May.
    26. Wayne A. Grove & Andrew Hussey & Michael Jetter, 2011. "The Gender Pay Gap Beyond Human Capital: Heterogeneity in Noncognitive Skills and in Labor Market Tastes," Journal of Human Resources, University of Wisconsin Press, vol. 46(4), pages 827-874.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Maryna Tverdostup & Tiiu Paas, 2019. "Valuation Of Human Capital And The Gender Wage Gap In Europe," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 118, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    3. Joanna Tyrowicz & Lucas van der Velde, 2017. "When the opportunity knocks: large structural shocks and gender wage gaps," GRAPE Working Papers 2, GRAPE Group for Research in Applied Economics.
    4. Kaya, Ezgi, 2019. "Gender wage gap across the quantiles:What is the role of firm segregation?," Cardiff Economics Working Papers E2019/7, Cardiff University, Cardiff Business School, Economics Section.
    5. Bonaccolto-Töpfer, Marina & Briel, Stephanie, 2022. "The gender pay gap revisited: Does machine learning offer new insights?," Labour Economics, Elsevier, vol. 78(C).
    6. Christl, Michael & Köppl-Turyna, Monika & Gnan, Phillipp, 2017. "Wage Differences Between Immigrants and Natives in Austria: The Role of Literacy Skills," GLO Discussion Paper Series 145, Global Labor Organization (GLO).
    7. Nan L. Maxwell & Nathan Wozny, 2021. "Gender Gaps in Time Use and Labor Market Outcomes: What’s Norms Got to Do with it?," Journal of Labor Research, Springer, vol. 42(1), pages 56-77, March.
    8. Töpfer, Marina, 2017. "Detailed RIF decomposition with selection: The gender pay gap in Italy," Hohenheim Discussion Papers in Business, Economics and Social Sciences 26-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    9. Cody Cook & Rebecca Diamond & Jonathan V Hall & John A List & Paul Oyer, 2021. "The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers [Measuring the Gig Economy: Current Knowledge and Open Issues]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(5), pages 2210-2238.
    10. Hennig, Jan-Luca & Stadler, Balazs, 2021. "Firm-specific pay premiums and the gender wage gap in 21 European countries," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242354, Verein für Socialpolitik / German Economic Association.
    11. Juan Manuel del Pozo Segura, 2017. "Has the Gender Wage Gap been Reduced during the 'Peruvian Growth Miracle?' A Distributional Approach," Documentos de Trabajo / Working Papers 2017-442, Departamento de Economía - Pontificia Universidad Católica del Perú.
    12. Boris Hirsch & Philipp Lentge, 2021. "Non-Base Compensation and the Gender Pay Gap," Working Paper Series in Economics 404, University of Lüneburg, Institute of Economics.
    13. Sonja C. Kassenboehmer & Mathias G. Sinning, 2014. "Distributional Changes in the Gender Wage Gap," ILR Review, Cornell University, ILR School, vol. 67(2), pages 335-361, April.
    14. Masso, Jaan & Meriküll, Jaanika & Vahter, Priit, 2022. "The role of firms in the gender wage gap," Journal of Comparative Economics, Elsevier, vol. 50(2), pages 454-473.
    15. Francesconi, Marco & Parey, Matthias, 2018. "Early gender gaps among university graduates," European Economic Review, Elsevier, vol. 109(C), pages 63-82.
    16. Anne‐Sophie Bruno & Nathalie Greenan & Jeremy Tanguy, 2021. "Does the Gender Mix Influence Collective Bargaining on Gender Equality? Evidence from France," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 60(4), pages 479-520, October.
    17. Töpfer, Marina, 2017. "Detailed RIF Decomposition with Selection - The Gender Pay Gap in Italy," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168422, Verein für Socialpolitik / German Economic Association.
    18. Miamo Wendji, Clovis & Kouhomou, Clemence Zite, 2020. "Ecart salarial de genre au Cameroun : une analyse de son trend et de son ampleur entre 2001 et 2014 [Gender wage gap in Cameroon : an analysis of the trend and extent between 2001 and 2014]," MPRA Paper 100288, University Library of Munich, Germany, revised 10 May 2020.
    19. Hirsch, Boris & Lentge, Philipp, 2021. "Non-Base Compensation and the Gender Pay Gap," IZA Discussion Papers 14551, Institute of Labor Economics (IZA).
    20. Magda, Iga & Salach, Katarzyna, 2019. "Gender Pay Gap Patterns in Domestic and Foreign-Owned Firms," IZA Discussion Papers 12453, Institute of Labor Economics (IZA).

    More about this item

    Keywords

    human capital; gender wage gap; non-parametric decomposition; PIAAC; Estonia;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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

    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:wiw:wiwrsa:ersa16p157. 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: Gunther Maier (email available below). General contact details of provider: http://www.ersa.org .

    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.