IDEAS home Printed from https://ideas.repec.org/p/sas/wpaper/20134.html
   My bibliography  Save this paper

The make-up of a regression coefficient: gender gaps in the European labor market

Author

Listed:
  • M. Grazia Pittau

    (Sapienza Universita' di Roma)

  • Shlomo Yitzhaki

    (The Hebrew University of Jerusalem and Central Bureau of Statistics)

  • Roberto Zelli

    (Sapienza Universita' di Roma)

Abstract

We provide a comprehensive picture of the relationship between labor market outcomes and age by gender in all the 28 European countries covered by the European Statistics on Income and Living Conditions (EU-SILC). The analysis is based on a somewhat unconventional approach that refers to concentration curves in the context of Gini regression framework. It allows to identify ranges in the explanatory variables where local slopes change sign and/or size, i.e. the components that \make up" a regression coecient. The European countries are clustered into five groups according to their employment, hours of work and earnings age-profiles by gender, as identified by the concentration curves. The most relevant differences in age pro les concern working-hours-patterns: some countries are characterized by an almost specular behavior in men and women; other countries instead show similar patterns. Generally, earnings increase with age for both men and women. However, local regression coefficients are not monotonic over the entire age range and can even be locally negative in some countries.

Suggested Citation

  • M. Grazia Pittau & Shlomo Yitzhaki & Roberto Zelli, 2013. "The make-up of a regression coefficient: gender gaps in the European labor market," DSS Empirical Economics and Econometrics Working Papers Series 2013/4, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
    • Handle: RePEc:sas:wpaper:20134
    as

    Download full text from publisher

    File URL: http://www.dss.uniroma1.it/RePec/sas/wpaper/20134_pyz.pdf
    File Function: First version, 2013
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Claudia Olivetti, 2008. "Gender and the Labour Market: An International Perspective and the Case of Italy," Rivista di Politica Economica, SIPI Spa, vol. 98(3), pages 3-32, May-June.
    2. Shlomo Yitzhaki & Edna Schechtman, 2004. "The Gini Instrumental Variable, or the “double instrumental variable” estimator," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 287-313.
    3. Claudia Olivetti & Barbara Petrongolo, 2008. "Unequal Pay or Unequal Employment? A Cross-Country Analysis of Gender Gaps," Journal of Labor Economics, University of Chicago Press, vol. 26(4), pages 621-654, October.
    4. Francine D. Blau & Lawrence M. Kahn, 2003. "Understanding International Differences in the Gender Pay Gap," Journal of Labor Economics, University of Chicago Press, vol. 21(1), pages 106-144, January.
    5. repec:bla:econom:v:63:y:1996:i:250:p:s29-62 is not listed on IDEAS
    6. Francine D. Blau & Lawrence M. Kahn, 2000. "Gender Differences in Pay," Journal of Economic Perspectives, American Economic Association, vol. 14(4), pages 75-99, Fall.
    7. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 389-432, August.
    8. Yitzhaki, Shlomo & Schechtman, Edna, 2012. "Identifying monotonic and non-monotonic relationships," Economics Letters, Elsevier, vol. 116(1), pages 23-25.
    9. Lazear, Edward P, 1979. "Why Is There Mandatory Retirement?," Journal of Political Economy, University of Chicago Press, vol. 87(6), pages 1261-1284, December.
    10. repec:bla:econom:v:50:y:1983:i:197:p:3-17 is not listed on IDEAS
    11. Giovanni Maria Giorgi, 2005. "Gini's scientific work: an evergreen," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 299-315.
    12. Shlomo Yitzhaki, 2003. "Gini’s Mean difference: a superior measure of variability for non-normal distributions," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 285-316.
    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. Ramskogler, Paul & Riedl, Aleksandra & Schoiswohl, Florian, 2020. "Swinging female labor demand – How the public sector influences gender wage gaps in Europe," Department of Economics Working Paper Series 302, WU Vienna University of Economics and Business.
    2. Shlomo Yitzhaki, 2015. "Gini’s mean difference offers a response to Leamer’s critique," METRON, Springer;Sapienza Università di Roma, vol. 73(1), pages 31-43, April.
    3. M. Costa, 2019. "The evaluation of gender income inequality by means of the Gini index decomposition," Working Papers wp1130, Dipartimento Scienze Economiche, Universita' di Bologna.

    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. Edna Schechtman & Shlomo Yitzhaki & Taina Pudalov, 2011. "Gini’s multiple regressions: two approaches and their interaction," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 67-99.
    2. Boris Hirsch & Marion König & Joachim Möller, 2013. "Is There a Gap in the Gap? Regional Differences in the Gender Pay Gap," Scottish Journal of Political Economy, Scottish Economic Society, vol. 60(4), pages 412-439, September.
    3. Pfeifer, Christian & Sohr, Tatjana, 2008. "Analysing the Gender Wage Gap Using Personnel Records of a Large German Company," IZA Discussion Papers 3533, Institute of Labor Economics (IZA).
    4. Iga Magda & Ewa Cukrowska-Torzewska, 2019. "Gender wage gap in the workplace: Does the age of the firm matter?," IBS Working Papers 01/2019, Instytut Badan Strukturalnych.
    5. M. Grazia Pittau & Shlomo Yitzhaki & Roberto Zelli, 2011. "The make-up of a regression coefficient: An application to gender," DSS Empirical Economics and Econometrics Working Papers Series 2011/3, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
    6. Carolina Castagnetti & Luisa Rosti & Marina Töpfer, 2020. "Discriminate me — If you can! The disappearance of the gender pay gap among public‐contest selected employees in Italy," Gender, Work and Organization, Wiley Blackwell, vol. 27(6), pages 1040-1076, November.
    7. Christian Pfeifer & Tatjana Sohr, 2009. "Analysing the Gender Wage Gap (GWG) Using Personnel Records," LABOUR, CEIS, vol. 23(2), pages 257-282, June.
    8. Hipólito Simón, 2012. "The gender gap in earnings: an international comparison with European matched employer--employee data," Applied Economics, Taylor & Francis Journals, vol. 44(15), pages 1985-1999, May.
    9. 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.
    10. Jellal, Mohamed & Nordman, Christophe, 2009. "A Theory of Gender Wage Gap," MPRA Paper 17409, University Library of Munich, Germany.
    11. Yitzhaki, Shlomo & Schechtman, Edna, 2012. "Identifying monotonic and non-monotonic relationships," Economics Letters, Elsevier, vol. 116(1), pages 23-25.
    12. Tugce, Cuhadaroglu, 2013. "My Group Beats Your Group: Evaluating Non-Income Inequalities," SIRE Discussion Papers 2013-49, Scottish Institute for Research in Economics (SIRE).
    13. Yann Algan & Christian Dustmann & Albrecht Glitz & Alan Manning, 2010. "The Economic Situation of First and Second-Generation Immigrants in France, Germany and the United Kingdom," Economic Journal, Royal Economic Society, vol. 120(542), pages 4-30, February.
    14. Bosquet, Clément & Combes, Pierre-Philippe & Garcia-Penalosa, Cecilia, 2013. "Gender and competition: evidence from academic promotions in France," LSE Research Online Documents on Economics 58350, London School of Economics and Political Science, LSE Library.
    15. Miguel Angel, 2023. "Differences in the labor market by gender and aggregate income," Sobre México. Revista de Economía, Sobre México. Temas en economía, vol. 1(7), pages 84-114.
    16. Jessen, Jonas & Jessen, Robin & Kluve, Jochen, 2019. "Punishing potential mothers? Evidence for statistical employer discrimination from a natural experiment," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 59, pages 164-172.
    17. Bognanno, Michael & Kambayashi, Ryo, 2013. "Trends in worker displacement penalties in Japan: 1991–2005," Japan and the World Economy, Elsevier, vol. 27(C), pages 41-57.
    18. Claudia Olivetti & Barbara Petrongolo, 2016. "The Evolution of Gender Gaps in Industrialized Countries," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 405-434, October.
    19. repec:hal:spmain:info:hdl:2441/9081 is not listed on IDEAS
    20. Ndéné Ka & Stéphane Mussard, 2016. "ℓ 1 regressions: Gini estimators for fixed effects panel data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(8), pages 1436-1446, June.
    21. Koumenta, Maria & Pagliero, Mario & Rostam-Afschar, Davud, 2020. "Occupational licensing and the gender wage gap," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2020, University of Hohenheim, Faculty of Business, Economics and Social Sciences.

    More about this item

    Keywords

    Gini; OLS; Concentration curves; Regression decomposition; European labor market.;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure

    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:sas:wpaper:20134. 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: Stefano Fachin (email available below). General contact details of provider: https://edirc.repec.org/data/ddrosit.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.