IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v28y2021i10p817-828.html
   My bibliography  Save this article

Decomposition of the gender wage gap using the LASSO estimator

Author

Listed:
  • René Böheim
  • Philipp Stöllinger

Abstract

We use the LASSO estimator to select among a large number of explanatory variables in wage regressions for a decomposition of the gender wage gap. The LASSO selection with a one standard error rule removes about a quarter of the regressors. We use the LASSO-selected regressors for OLS-based gender wage decompositions. This approach results in a smaller error variance than in OLS without LASSO-selection. The explained gender wage gap is 1%-point greater than in the conventional OLS model.

Suggested Citation

  • René Böheim & Philipp Stöllinger, 2021. "Decomposition of the gender wage gap using the LASSO estimator," Applied Economics Letters, Taylor & Francis Journals, vol. 28(10), pages 817-828, June.
    • Handle: RePEc:taf:apeclt:v:28:y:2021:i:10:p:817-828
    DOI: 10.1080/13504851.2020.1782332
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13504851.2020.1782332
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13504851.2020.1782332?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Doris Weichselbaumer & Rudolf Winter‐Ebmer, 2005. "A Meta‐Analysis of the International Gender Wage Gap," Journal of Economic Surveys, Wiley Blackwell, vol. 19(3), pages 479-511, July.
    3. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    4. A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012. "Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain," Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.
    5. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "Inference on Treatment Effects after Selection among High-Dimensional Controlsâ€," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(2), pages 608-650.
    6. Matteo Barigozzi & Christian Brownlees, 2019. "NETS: Network estimation for time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 347-364, April.
    7. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    8. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    9. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
    10. Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
    11. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    12. Smith, James P & Welch, Finis R, 1989. "Black Economic Progress after Myrdal," Journal of Economic Literature, American Economic Association, vol. 27(2), pages 519-564, June.
    13. T.D. Stanley & Stephen B. Jarrell, 1998. "Gender Wage Discrimination Bias? A Meta-Regression Analysis," Journal of Human Resources, University of Wisconsin Press, vol. 33(4), pages 947-973.
    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. Szabó-Morvai Ágnes & Hubert János Kiss, 2020. "Locus of control and Human Capital Investment Decisions: The Role of Effort, Parental Preferences and Financial Constraints," CERS-IE WORKING PAPERS 2055, Institute of Economics, Centre for Economic and Regional Studies.
    2. Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E & Wiemann, Thomas, 2024. "Model Averaging and Double Machine Learning," IZA Discussion Papers 16714, Institute of Labor Economics (IZA).
    3. Olga Takács & János Vincze, 2023. "Where is the pain the most acute? The market segments particularly affected by gender wage discrimination in Hungary," CERS-IE WORKING PAPERS 2304, Institute of Economics, Centre for Economic and Regional Studies.

    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. Bonaccolto-Töpfer, Marina & Briel, Stephanie, 2022. "The gender pay gap revisited: Does machine learning offer new insights?," Labour Economics, Elsevier, vol. 78(C).
    2. Sandeep Mohapatra & Bruno Wichmann & Philippe Marcoul, 2018. "Removing The “Veil Of Ignorance”: Nonlinearities In Education Effects On Gender Wage Inequalities," Contemporary Economic Policy, Western Economic Association International, vol. 36(4), pages 644-666, October.
    3. Marina Bonaccolto-Töpfer & Carolina Castagnetti & Luisa Rosti, 2023. "Changes in the gender pay gap over time: the case of West Germany," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 57(1), pages 1-17, December.
    4. Brieland, Stephanie & Töpfer, Marina, 2020. "The gender pay gap revisited: Does machine learning offer new insights?," Discussion Papers 111, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Labour and Regional Economics.
    5. Thomas Grandner & Dieter Gstach, 2015. "Decomposing wage discrimination in Germany and Austria with counterfactual densities," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(1), pages 49-76, February.
    6. Karolina Goraus & Joanna Tyrowicz & Lucas Velde, 2017. "Which Gender Wage Gap Estimates to Trust? A Comparative Analysis," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(1), pages 118-146, March.
    7. Sergio Longobardi & Margherita Maria Pagliuca & Andrea Regoli, 2018. "Can problem-solving attitudes explain the gender gap in financial literacy? Evidence from Italian students’ data," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1677-1705, July.
    8. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    9. Luis Ayala & Javier Martín-Román & Juan Vicente, 2023. "What Contributes to Rising Inequality in Large Cities?," LIS Working papers 850, LIS Cross-National Data Center in Luxembourg.
    10. Astrid Kunze, 2008. "Gender wage gap studies: consistency and decomposition," Empirical Economics, Springer, vol. 35(1), pages 63-76, August.
    11. Ina GANGULI & Ricardo HAUSMANN & Martina VIARENGO, 2014. "Closing the gender gap in education: What is the state of gaps in labour force participation for women, wives and mothers?," International Labour Review, International Labour Organization, vol. 153(2), pages 173-207, June.
    12. Zhu, Rong, 2016. "Wage differentials between urban residents and rural migrants in urban China during 2002–2007: A distributional analysis," China Economic Review, Elsevier, vol. 37(C), pages 2-14.
    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. Trinh Thi, Huong & Simioni, Michel & Thomas-Agnan, Christine, 2018. "Decomposition of changes in the consumption of macronutrients in Vietnam between 2004 and 2014," Economics & Human Biology, Elsevier, vol. 31(C), pages 259-275.
    15. Domenico Depalo & Raffaela Giordano & Evangelia Papapetrou, 2015. "Public–private wage differentials in euro-area countries: evidence from quantile decomposition analysis," Empirical Economics, Springer, vol. 49(3), pages 985-1015, November.
    16. Mathä, Thomas Y. & Porpiglia, Alessandro & Ziegelmeyer, Michael, 2017. "Household wealth in the euro area: The importance of intergenerational transfers, homeownership and house price dynamics," Journal of Housing Economics, Elsevier, vol. 35(C), pages 1-12.
    17. Aurora Galego & João Pereira, 2014. "Decomposition of Regional Wage Differences Along the Wage Distribution in Portugal: The Importance of Covariates," Environment and Planning A, , vol. 46(10), pages 2514-2532, October.
    18. Arceo-Gómez, Eva O. & Campos-Vázquez, Raymundo M., 2014. "Evolución de la brecha salarial de género en México," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(323), pages .619-653, julio-sep.
    19. Caliendo, Marco & Lee, Wang-Sheng & Mahlstedt, Robert, 2017. "The gender wage gap and the role of reservation wages: New evidence for unemployed workers," Journal of Economic Behavior & Organization, Elsevier, vol. 136(C), pages 161-173.
    20. Rosalia Castellano & Gaetano Musella & Gennaro Punzo, 2019. "Exploring changes in the employment structure and wage inequality in Western Europe using the unconditional quantile regression," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 249-304, May.

    More about this item

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

    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:taf:apeclt:v:28:y:2021:i:10:p:817-828. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEL20 .

    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.