IDEAS home Printed from https://ideas.repec.org/a/wly/empleg/v19y2022i4p1222-1252.html
   My bibliography  Save this article

Do data breach notification laws reduce medical identity theft? Evidence from consumer complaints data

Author

Listed:
  • Aniket Kesari

Abstract

As the number of data breaches in the United States grows each year, cybersecurity has become an increasingly important policy area. The primary mechanism for regulating and deterring data breaches is the “data breach notification law.” Every US state now has such a law that mandates that certain organizations disclose data breaches to their data subjects. Despite the popularity of these laws, there is relatively little evidence about their effectiveness at deterring breaches, and therefore reducing identity theft. Using medical identity theft panel data collected from the Consumer Financial Protection Bureau, this study implements an augmented synthetic control approach to analyze the effect of California's 2016 data breach notification standards on medical identity theft. This approach suggests that medical identity theft reports in California were reduced by 3.5 reports/100,000 people.

Suggested Citation

  • Aniket Kesari, 2022. "Do data breach notification laws reduce medical identity theft? Evidence from consumer complaints data," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 19(4), pages 1222-1252, December.
  • Handle: RePEc:wly:empleg:v:19:y:2022:i:4:p:1222-1252
    DOI: 10.1111/jels.12331
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/jels.12331
    Download Restriction: no

    File URL: https://libkey.io/10.1111/jels.12331?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
    ---><---

    References listed on IDEAS

    as
    1. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2021. "The Augmented Synthetic Control Method," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1789-1803, October.
    2. Alberto Abadie & Javier Gardeazabal, 2003. "The Economic Costs of Conflict: A Case Study of the Basque Country," American Economic Review, American Economic Association, vol. 93(1), pages 113-132, March.
    3. Alberto Abadie & Jaume Vives-i-Bastida, 2022. "Synthetic Controls in Action," Papers 2203.06279, arXiv.org.
    4. Sasha Romanosky & Rahul Telang & Alessandro Acquisti, 2011. "Do data breach disclosure laws reduce identity theft?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 30(2), pages 256-286, March.
    5. Guido W. Imbens, 2010. "Better LATE Than Nothing: Some Comments on Deaton (2009) and Heckman and Urzua (2009)," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 399-423, June.
    6. Oscar Engelbrektson, 2021. "Why Synthetic Control estimators are biased and what to do about it: Introducing Relaxed and Penalized Synthetic Controls," Papers 2111.10784, arXiv.org.
    7. Claudia Shi & Dhanya Sridhar & Vishal Misra & David M. Blei, 2021. "On the Assumptions of Synthetic Control Methods," Papers 2112.05671, arXiv.org, revised Dec 2021.
    8. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
    9. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    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. Dennis Shen & Peng Ding & Jasjeet Sekhon & Bin Yu, 2022. "Same Root Different Leaves: Time Series and Cross-Sectional Methods in Panel Data," Papers 2207.14481, arXiv.org, revised Oct 2022.
    2. Pekka Malo & Juha Eskelinen & Xun Zhou & Timo Kuosmanen, 2024. "Computing Synthetic Controls Using Bilevel Optimization," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1113-1136, August.
    3. Michael Funke & Kadri Männasoo & Helery Tasane, 2023. "Regional Economic Impacts of the Øresund Cross-Border Fixed Link: Cui Bono?," CESifo Working Paper Series 10557, CESifo.
    4. Robert Kraemer & Jonne Lehtimäki, 2024. "Government debt, European Institutions and fiscal rules: a synthetic control approach," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 31(4), pages 1112-1157, August.
    5. Andrii Melnychuk, 2024. "Synthetic Controls with spillover effects: A comparative study," Papers 2405.01645, arXiv.org.
    6. Guido W. Imbens, 2022. "Causality in Econometrics: Choice vs Chance," Econometrica, Econometric Society, vol. 90(6), pages 2541-2566, November.
    7. Stefano, Roberta di & Mellace, Giovanni, 2020. "The inclusive synthetic control method," Discussion Papers on Economics 14/2020, University of Southern Denmark, Department of Economics.
    8. Diego D'iaz & Pablo Paniagua & Cristi'an Larroulet, 2024. "Earthquakes and the wealth of nations: The cases of Chile and New Zealand," Papers 2405.12041, arXiv.org.
    9. David Gilchrist & Thomas Emery & Nuno Garoupa & Rok Spruk, 2023. "Synthetic Control Method: A tool for comparative case studies in economic history," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 409-445, April.
    10. Roy Cerqueti & Raffaella Coppier & Alessandro Girardi & Marco Ventura, 2022. "The sooner the better: lives saved by the lockdown during the COVID-19 outbreak. The case of Italy," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 46-70.
    11. Nadine McCloud & Ajornie Taylor, 2022. "Does inflation targeting matter for international trade? A synthetic control analysis," Empirical Economics, Springer, vol. 63(5), pages 2427-2478, November.
    12. Yiping Lu & Jiajin Li & Lexing Ying & Jose Blanchet, 2022. "Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls," Papers 2211.15241, arXiv.org.
    13. Hannes Wallimann & Kevin Blattler & Widar von Arx, 2021. "Do price reductions attract customers in urban public transport? A synthetic control approach," Papers 2111.14613, arXiv.org, revised Mar 2022.
    14. Bennett, Magdalena, 2021. "All things equal? Heterogeneity in policy effectiveness against COVID-19 spread in chile," World Development, Elsevier, vol. 137(C).
    15. Esaka, Taro & Fujii, Takao, 2022. "Quantifying the impact of the Tokyo Olympics on COVID-19 cases using synthetic control methods," Journal of the Japanese and International Economies, Elsevier, vol. 66(C).
    16. Zheng, Shanshan & Wang, Derek D., 2024. "The local economic impacts of mega nuclear accident: A synthetic control analysis of Fukushima," Economic Modelling, Elsevier, vol. 136(C).
    17. Hideki Shimada & Kenji Asano & Yu Nagai & Akito Ozawa, 2022. "Assessing the Impact of Offshore Wind Power Deployment on Fishery: A Synthetic Control Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(3), pages 791-829, November.
    18. Echevarría, Cruz A. & Hasancebi, Serhat & García-Enríquez, Javier, 2022. "Economic Effects of Macao’s Integration with Mainland China: A Causal Inference Study," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 37(2), pages 179-215.
    19. 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.
    20. Manuel Funke & Moritz Schularick & Christoph Trebesch, 2023. "Populist Leaders and the Economy," American Economic Review, American Economic Association, vol. 113(12), pages 3249-3288, December.

    More about this item

    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:wly:empleg:v:19:y:2022:i:4:p:1222-1252. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1740-1461 .

    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.