IDEAS home Printed from https://ideas.repec.org/a/taf/jnlasa/v108y2013i502p504-513.html
   My bibliography  Save this article

Partially Identified Treatment Effects Under Imperfect Compliance: The Case of Domestic Violence

Author

Listed:
  • Zahra Siddique

Abstract

The Minneapolis Domestic Violence Experiment (MDVE) is a randomized social experiment with imperfect compliance that has been extremely influential in how police officers respond to misdemeanor domestic violence. This article reexamines data from the MDVE, using recent literature on partial identification to find recidivism associated with a policy that arrests misdemeanor domestic violence suspects rather than not arresting them. Using partially identified bounds on the average treatment effect, I find that arresting rather than not arresting suspects can potentially reduce recidivism by more than two-and-a-half times the corresponding intent-to-treat estimate and more than two times the corresponding local average treatment effect, even when making minimal assumptions on counterfactuals.

Suggested Citation

  • Zahra Siddique, 2013. "Partially Identified Treatment Effects Under Imperfect Compliance: The Case of Domestic Violence," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(502), pages 504-513, June.
    • Handle: RePEc:taf:jnlasa:v:108:y:2013:i:502:p:504-513
    DOI: 10.1080/01621459.2013.779836
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01621459.2013.779836
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/01621459.2013.779836?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. Joshua Angrist, 2005. "Instrumental Variables Methods in Experimental Criminological Research: What, Why, and How?," NBER Technical Working Papers 0314, National Bureau of Economic Research, Inc.
    2. Guido W. Imbens & Charles F. Manski, 2004. "Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 72(6), pages 1845-1857, November.
    3. Robert A. Pollak, 2004. "An intergenerational model of domestic violence," Journal of Population Economics, Springer;European Society for Population Economics, vol. 17(2), pages 311-329, June.
    4. Betsey Stevenson & Justin Wolfers, 2006. "Bargaining in the Shadow of the Law: Divorce Laws and Family Distress," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(1), pages 267-288.
    5. Binder, Arnold & Meeker, James W., 1988. "Experiments as reforms," Journal of Criminal Justice, Elsevier, vol. 16(4), pages 347-358.
    6. Jorg Stoye, 2009. "More on Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 77(4), pages 1299-1315, July.
    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. Ho, Kate & Rosen, Adam M., 2015. "Partial Identification in Applied Research: Benefits and Challenges," CEPR Discussion Papers 10883, C.E.P.R. Discussion Papers.
    2. Lukáš Lafférs, 2019. "Bounding average treatment effects using linear programming," Empirical Economics, Springer, vol. 57(3), pages 727-767, September.
    3. Charles F. Manski & John V. Pepper, 2018. "How Do Right-to-Carry Laws Affect Crime Rates? Coping with Ambiguity Using Bounded-Variation Assumptions," The Review of Economics and Statistics, MIT Press, vol. 100(2), pages 232-244, May.
    4. Mechoulan, Stéphane, 2020. "Civil unrest, emergency powers, and spillover effects: A mixed methods analysis of the 2005 French riots," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 305-326.
    5. Hongming Pu & Bo Zhang, 2021. "Estimating optimal treatment rules with an instrumental variable: A partial identification learning approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(2), pages 318-345, April.
    6. Ting Ye & Luke Keele & Raiden Hasegawa & Dylan S. Small, 2020. "A Negative Correlation Strategy for Bracketing in Difference-in-Differences," Papers 2006.02423, arXiv.org, revised Jun 2022.
    7. Zahra Siddique, 2014. "Randomized control trials in an imperfect world," IZA World of Labor, Institute of Labor Economics (IZA), pages 110-110, December.

    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. Christian Bontemps & Thierry Magnac & Eric Maurin, 2012. "Set Identified Linear Models," Econometrica, Econometric Society, vol. 80(3), pages 1129-1155, May.
    2. Xintong Wang & Carlos A. Flores & Alfonso Flores-Lagunes, 2020. "The Effects of Vietnam-Era Military Service on the Long-Term Health of Veterans: A Bounds Analysis," Center for Policy Research Working Papers 234, Center for Policy Research, Maxwell School, Syracuse University.
    3. Ana Tur-Prats, 2019. "Family Types and Intimate Partner Violence: A Historical Perspective," The Review of Economics and Statistics, MIT Press, vol. 101(5), pages 878-891, December.
    4. Joachim Freyberger & Joel L. Horowitz, 2012. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers CWP15/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Angelucci Manuela, 2008. "Love on the Rocks: Domestic Violence and Alcohol Abuse in Rural Mexico," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 8(1), pages 1-43, October.
    6. Yuichi Kitamura & Jörg Stoye, 2018. "Nonparametric Analysis of Random Utility Models," Econometrica, Econometric Society, vol. 86(6), pages 1883-1909, November.
    7. Hiroaki Kaido & Francesca Molinari & Jörg Stoye, 2019. "Confidence Intervals for Projections of Partially Identified Parameters," Econometrica, Econometric Society, vol. 87(4), pages 1397-1432, July.
    8. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
    9. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    10. Aibo Gong, 2021. "Bounds for Treatment Effects in the Presence of Anticipatory Behavior," Papers 2111.06573, arXiv.org, revised Dec 2022.
    11. Raffaella Giacomini & Toru Kitagawa, 2021. "Robust Bayesian Inference for Set‐Identified Models," Econometrica, Econometric Society, vol. 89(4), pages 1519-1556, July.
    12. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    13. Yuan Liao & Anna Simoni, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," Papers 1212.3267, arXiv.org, revised Nov 2013.
    14. García-Ramos, Aixa, 2021. "Divorce laws and intimate partner violence: Evidence from Mexico," Journal of Development Economics, Elsevier, vol. 150(C).
    15. Trinidad Beleche, 2019. "Domestic violence laws and suicide in Mexico," Review of Economics of the Household, Springer, vol. 17(1), pages 229-248, March.
    16. Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2021. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," Papers 2112.13398, arXiv.org, revised May 2024.
    17. Xiaohong Chen & Timothy M. Christensen & Elie Tamer, 2018. "Monte Carlo Confidence Sets for Identified Sets," Econometrica, Econometric Society, vol. 86(6), pages 1965-2018, November.
    18. Cherchye, Laurens & Demuynck, Thomas & Rock, Bram De, 2019. "Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures," Journal of Econometrics, Elsevier, vol. 211(2), pages 483-506.
    19. Sungwon Lee, 2024. "Partial identification and inference for conditional distributions of treatment effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 107-127, January.
    20. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Inference for functions of partially identified parameters in moment inequality models," CeMMAP working papers 22/14, Institute for Fiscal Studies.

    More about this item

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

    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:jnlasa:v:108:y:2013:i:502:p:504-513. 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/UASA20 .

    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.