IDEAS home Printed from https://ideas.repec.org/a/eee/cysrev/v156y2024ics0190740923005388.html
   My bibliography  Save this article

Underreporting child maltreatment during the pandemic: Evidence from Colorado

Author

Listed:
  • Prettyman, Alexa

Abstract

As a result of the COVID-19 pandemic, schools closed abruptly in March 2020, and Colorado issued a stay-at-home order during the month of April. Subsequently, child maltreatment reporting dropped by 31 percent. This article documents the decline in referrals and reports during 2020 and 2021 in Colorado and predicts counterfactual estimates using two strategies. One strategy assumes the underlying behavior for child maltreatment was unchanged from 2019 to 2020 and 2021, while the second strategy assumes the economic distress and protective factors brought about by the pandemic altered the underlying prevalence of child maltreatment. Consequently, these two approaches yield similar results when investigating referrals, but they differ when investigating screened-in referrals and substantiated reports. I find that the largest reduction in reporting comes from the stay-at-home order, followed by school closings. Lastly, counterfactual estimates suggest that these missed children were suffering from neglect and not abuse. These findings quantify another hardship brought about by the pandemic, underreporting child maltreatment, and underscore the role mandatory reporters play in detecting child maltreatment.

Suggested Citation

  • Prettyman, Alexa, 2024. "Underreporting child maltreatment during the pandemic: Evidence from Colorado," Children and Youth Services Review, Elsevier, vol. 156(C).
    • Handle: RePEc:eee:cysrev:v:156:y:2024:i:c:s0190740923005388
    DOI: 10.1016/j.childyouth.2023.107342
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0190740923005388
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.childyouth.2023.107342?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. Leslie, Emily & Wilson, Riley, 2020. "Sheltering in place and domestic violence: Evidence from calls for service during COVID-19," Journal of Public Economics, Elsevier, vol. 189(C).
    2. James G. MacKinnon & Matthew D. Webb, 2018. "The wild bootstrap for few (treated) clusters," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 114-135, June.
    3. Bruno Ferman & Cristine Pinto, 2019. "Inference in Differences-in-Differences with Few Treated Groups and Heteroskedasticity," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 452-467, July.
    4. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    5. Raj Chetty & Adam Looney & Kory Kroft, 2009. "Salience and Taxation: Theory and Evidence," American Economic Review, American Economic Association, vol. 99(4), pages 1145-1177, September.
    6. Baron, E. Jason & Goldstein, Ezra G. & Wallace, Cullen T., 2020. "Suffering in silence: How COVID-19 school closures inhibit the reporting of child maltreatment," Journal of Public Economics, Elsevier, vol. 190(C).
    7. Slade, Eric P. & Wissow, Lawrence S., 2007. "The influence of childhood maltreatment on adolescents' academic performance," Economics of Education Review, Elsevier, vol. 26(5), pages 604-614, October.
    8. James G. MacKinnon & Matthew D. Webb, 2017. "Wild Bootstrap Inference for Wildly Different Cluster Sizes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 233-254, March.
    9. Wilson, Samita & Hean, Sarah & Abebe, Tatek & Heaslip, Vanessa, 2020. "Children’s experiences with Child Protection Services: A synthesis of qualitative evidence," Children and Youth Services Review, Elsevier, vol. 113(C).
    10. James G. MacKinnon & Matthew D. Webb, 2019. "Wild Bootstrap Randomization Inference for Few Treated Clusters," Advances in Econometrics, in: The Econometrics of Complex Survey Data, volume 39, pages 61-85, Emerald Group Publishing Limited.
    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. Baron, E. Jason & Goldstein, Ezra G. & Wallace, Cullen T., 2020. "Suffering in silence: How COVID-19 school closures inhibit the reporting of child maltreatment," Journal of Public Economics, Elsevier, vol. 190(C).
    2. E. Jason Baron & Ezra G. Goldstein & Joseph Ryan, 2023. "The Push for Racial Equity in Child Welfare: Can Blind Removals Reduce Disproportionality?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(2), pages 456-487, March.
    3. MacKinnon, James G. & Nielsen, Morten Ørregaard & Webb, Matthew D., 2023. "Cluster-robust inference: A guide to empirical practice," Journal of Econometrics, Elsevier, vol. 232(2), pages 272-299.
    4. MacKinnon, James G. & Webb, Matthew D., 2020. "Randomization inference for difference-in-differences with few treated clusters," Journal of Econometrics, Elsevier, vol. 218(2), pages 435-450.
    5. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Fast and reliable jackknife and bootstrap methods for cluster‐robust inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 671-694, August.
    6. Damian Clarke & Kathya Tapia-Schythe, 2021. "Implementing the panel event study," Stata Journal, StataCorp LP, vol. 21(4), pages 853-884, December.
    7. MacKinnon, James G., 2023. "Fast cluster bootstrap methods for linear regression models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 52-71.
    8. Hansen, Bruce E. & Lee, Seojeong, 2019. "Asymptotic theory for clustered samples," Journal of Econometrics, Elsevier, vol. 210(2), pages 268-290.
    9. Dorner, Matthias & Görlitz, Katja, 2020. "Training, wages and a missing school graduation cohort," IAB-Discussion Paper 202028, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    10. Roth, Jonathan & Sant’Anna, Pedro H.C. & Bilinski, Alyssa & Poe, John, 2023. "What’s trending in difference-in-differences? A synthesis of the recent econometrics literature," Journal of Econometrics, Elsevier, vol. 235(2), pages 2218-2244.
    11. MacKinnon, James G. & Nielsen, Morten Ørregaard & Webb, Matthew D., 2023. "Testing for the appropriate level of clustering in linear regression models," Journal of Econometrics, Elsevier, vol. 235(2), pages 2027-2056.
    12. Alexander James & Nathaly Rivera & Brock Smith, 2022. "Cash Transfers and Voter Turnout," Working Papers 2022-01, University of Alaska Anchorage, Department of Economics.
    13. Ban, Radu & Gilligan, Michael J. & Rieger, Matthias, 2020. "Self-help groups, savings and social capital: Evidence from a field experiment in Cambodia," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 174-200.
    14. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Leverage, influence, and the jackknife in clustered regression models: Reliable inference using summclust," Stata Journal, StataCorp LP, vol. 23(4), pages 942-982, December.
    15. Friedman, Willa & Keats, Anthony & Mutua, Martin Kavao, 2022. "Disruptions to healthcare quality and early child health outcomes: Evidence from health-worker strikes in Kenya," Journal of Health Economics, Elsevier, vol. 86(C).
    16. Goussé, Marion & Leturcq, Marion, 2022. "More or less unmarried. The impact of legal settings of cohabitation on labour market outcomes," European Economic Review, Elsevier, vol. 149(C).
    17. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2021. "Wild Bootstrap and Asymptotic Inference With Multiway Clustering," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 505-519, March.
    18. Gerling, Lena & Kellermann, Kim Leonie, 2022. "Contagious populists: The impact of election information shocks on populist party preferences in Germany," European Journal of Political Economy, Elsevier, vol. 72(C).
    19. Burbano, Vanessa C. & Ostler, James, 2021. "Differences in consumer-benefiting misconduct by nonprofit, for-profit, and public organizations," Organizational Behavior and Human Decision Processes, Elsevier, vol. 166(C), pages 117-136.
    20. MacKinnon, James G., 2023. "Using large samples in econometrics," Journal of Econometrics, Elsevier, vol. 235(2), pages 922-926.

    More about this item

    Keywords

    Child maltreatment; COVID-19; Underreporting; Colorado; Stay-at-home order;
    All these keywords.

    JEL classification:

    • H12 - Public Economics - - Structure and Scope of Government - - - Crisis Management
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • J12 - Labor and Demographic Economics - - Demographic Economics - - - Marriage; Marital Dissolution; Family Structure

    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:eee:cysrev:v:156:y:2024:i:c:s0190740923005388. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/childyouth .

    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.