IDEAS home Printed from https://ideas.repec.org/p/ulp/sbbeta/2026-08.html

Norms Behind Closed Doors: A Field Experiment on Gender Norm Misperceptions and Maternal Employment Decisions in Couples

Author

Listed:
  • Marie Boltz
  • Monserrat Bustelo
  • Ana María Díaz
  • Agustina Suaya

Abstract

We study whether pluralistic ignorance about societal and spousal support for maternal employment sustains gender gaps in women’s labour-market outcomes. Using a representative sample of 1,732 cohabiting couples with young children in Bogotá, we document near-universal first-order support for working mothers but substantial underestimation of others’ support, especially that of fathers, and frequent misperceptions of the partner’s views. We then implement a randomised information intervention that delivers personalised feedback on prevailing local attitudes toward maternal employment. The intervention narrows key second-order belief gaps about community and spousal support, while leaving first-order attitudes essentially unchanged. Treated men are more likely than control men to nominate their wife rather than themselves for a career-building course. One to two months later, treated women report more intensive job search and treated men place greater weight on work–family balance. Effects are concentrated among women who are already active in the labour market, underscoring both the potential and the limits of norm-correcting information in a context with high support for women’s work but large misperceptions

Suggested Citation

  • Marie Boltz & Monserrat Bustelo & Ana María Díaz & Agustina Suaya, 2026. "Norms Behind Closed Doors: A Field Experiment on Gender Norm Misperceptions and Maternal Employment Decisions in Couples," Working Papers of BETA 2026-08, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
  • Handle: RePEc:ulp:sbbeta:2026-08
    as

    Download full text from publisher

    File URL: http://beta.u-strasbg.fr/WP/2026/2026-08.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Elisabeth Cudeville & Magali Recoules, 2014. "Household Behaviour and Social Norms: A Conjugal Contract Model with Conformism," PSE-Ecole d'économie de Paris (Postprint) hal-00976933, HAL.
    2. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, Enero-Abr.
    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. Sven Resnjanskij & Jens Ruhose & Simon Wiederhold & Ludger Wößmann, 2021. "Mentoring verbessert die Arbeitsmarktchancen von stark benachteiligten Jugendlichen," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 74(02), pages 31-38, February.
    2. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-dimensional econometrics and regularized GMM," CeMMAP working papers CWP35/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Dimitris Bertsimas & Agni Orfanoudaki & Rory B. Weiner, 2020. "Personalized treatment for coronary artery disease patients: a machine learning approach," Health Care Management Science, Springer, vol. 23(4), pages 482-506, December.
    4. Bruno Ferman & Cristine Pinto & Vitor Possebom, 2020. "Cherry Picking with Synthetic Controls," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(2), pages 510-532, March.
    5. Bonesrønning, Hans & Finseraas, Henning & Hardoy, Ines & Iversen, Jon Marius Vaag & Nyhus, Ole Henning & Opheim, Vibeke & Salvanes, Kari Vea & Sandsør, Astrid Marie Jorde & Schøne, Pål, 2022. "Small-group instruction to improve student performance in mathematics in early grades: Results from a randomized field experiment," Journal of Public Economics, Elsevier, vol. 216(C).
    6. Peydró, José-Luis & Jiménez, Gabriel & Kenan, Huremovic & Moral-Benito, Enrique & Vega-Redondo, Fernando, 2020. "Production and financial networks in interplay: Crisis evidence from supplier-customer and credit registers," CEPR Discussion Papers 15277, Centre for Economic Policy Research.
    7. Ruoxuan Xiong & Allison Koenecke & Michael Powell & Zhu Shen & Joshua T. Vogelstein & Susan Athey, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Papers 2107.11732, arXiv.org, revised Apr 2023.
    8. Hairu Wang & Yukun Liu & Haiying Zhou, 2025. "Score test for unconfoundedness under a logistic treatment assignment model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 77(4), pages 517-533, August.
    9. Satarupa Bhattacharjee & Bing Li & Xiao Wu & Lingzhou Xue, 2025. "Doubly robust estimation of causal effects for random object outcomes with continuous treatments," Papers 2506.22754, arXiv.org.
    10. Konrad Menzel, 2021. "Structural Sieves," Papers 2112.01377, arXiv.org, revised Apr 2022.
    11. Jonne Y. Guyt & Arjen van Lin & Kristopher O. Keller, 2025. "Banning Unsolicited Store Flyers: Does Helping the Environment Hurt Retailing?," Marketing Science, INFORMS, vol. 44(5), pages 1104-1124, September.
    12. Alberto Abadie & Susan Athey & Guido W. Imbens & Jeffrey M. Wooldridge, 2020. "Sampling‐Based versus Design‐Based Uncertainty in Regression Analysis," Econometrica, Econometric Society, vol. 88(1), pages 265-296, January.
    13. Andrés Elberg & Pedro M. Gardete & Rosario Macera & Carlos Noton, 2019. "Dynamic effects of price promotions: field evidence, consumer search, and supply-side implications," Quantitative Marketing and Economics (QME), Springer, vol. 17(1), pages 1-58, March.
    14. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    15. Chenchuan (Mark) Li & Ulrich K. Müller, 2021. "Linear regression with many controls of limited explanatory power," Quantitative Economics, Econometric Society, vol. 12(2), pages 405-442, May.
    16. Jeon, Sung-Hee & Pohl, R. Vincent, 2019. "Medical innovation, education, and labor market outcomes of cancer patients," Journal of Health Economics, Elsevier, vol. 68(C).
    17. Johnsen, Åshild A. & Kvaløy, Ola, 2021. "Conspiracy against the public - An experiment on collusion11“People of the same trade seldom meet together, even for merriment and diversion, but the conversation ends in a conspiracy against the public, or in some contrivance to raise prices.” (Adam," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 94(C).
    18. Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
    19. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
    20. Steffen Andersen & Philippe d'Astous & Jimmy Martínez-Correa & Stephen H. Shore, 2018. "Responses to Savings Commitments: Evidence from Mortgage Run-offs," Cahiers de recherche / Working Papers 1, Institut sur la retraite et l'épargne / Retirement and Savings Institute.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • 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
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

    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:ulp:sbbeta:2026-08. 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: the person in charge The email address of this maintainer does not seem to be valid anymore. Please ask the person in charge to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/bestrfr.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.