IDEAS home Printed from https://ideas.repec.org/a/wly/quante/v6y2015i1p49-83.html
   My bibliography  Save this article

Treatment response with social interactions: Partial identification via monotone comparative statics

Author

Listed:
  • Natalia Lazzati

Abstract

This paper studies (nonparametric) partial identification of treatment response with social interactions. It imposes conditions motivated by economic theory on the primitives of the model, that is, the structural equations, and shows that they imply shape restrictions on the distribution of potential outcomes via monotone comparative statics. The econometric framework is tractable and allows for counterfactual predictions in models with multiple equilibria. Under three sets of assumptions, we identify sharp distributional bounds on the potential outcomes given observable data. We illustrate our results by studying the effect of police per capita on crime rates in New York state.

Suggested Citation

  • Natalia Lazzati, 2015. "Treatment response with social interactions: Partial identification via monotone comparative statics," Quantitative Economics, Econometric Society, vol. 6(1), pages 49-83, March.
    • Handle: RePEc:wly:quante:v:6:y:2015:i:1:p:49-83
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Matthew A. Masten & Alexandre Poirier, 2018. "Interpreting Quantile Independence," Papers 1804.10957, arXiv.org.
    2. Natalia Lazzati & John K.-H. Quah & Koji Shirai, 2015. "A revealed preference theory of monotone choice and strategic complementarity," Discussion Paper Series 138, School of Economics, Kwansei Gakuin University, revised Dec 2015.
    3. Áureo de Paula, 2015. "Econometrics of network models," CeMMAP working papers 52/15, Institute for Fiscal Studies.
    4. Michael P. Leung, 2022. "Causal Inference Under Approximate Neighborhood Interference," Econometrica, Econometric Society, vol. 90(1), pages 267-293, January.
    5. Kline, Brendan, 2015. "Identification of complete information games," Journal of Econometrics, Elsevier, vol. 189(1), pages 117-131.
    6. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
    7. Rainone, Edoardo, 2020. "The network nature of over-the-counter interest rates," Journal of Financial Markets, Elsevier, vol. 47(C).
    8. Bora Kim, 2020. "Analysis of Randomized Experiments with Network Interference and Noncompliance," Papers 2012.13710, arXiv.org.
    9. Arthur Lewbel, 2019. "The Identification Zoo: Meanings of Identification in Econometrics," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 835-903, December.
    10. Natalia Lazzati & Amilcar A. Menichini, 2016. "Hot Spot Policing: A Study of Place‐Based Strategies for Crime Prevention," Southern Economic Journal, John Wiley & Sons, vol. 82(3), pages 893-913, January.
    11. Sobel, Joel, 2019. "Iterated weak dominance and interval-dominance supermodular games," Theoretical Economics, Econometric Society, vol. 14(1), January.
    12. Hidano, Noboru & Hoshino, Tadao & Sugiura, Ayako, 2015. "The effect of seismic hazard risk information on property prices: Evidence from a spatial regression discontinuity design," Regional Science and Urban Economics, Elsevier, vol. 53(C), pages 113-122.
    13. Michael P. Leung, 2020. "Treatment and Spillover Effects Under Network Interference," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 368-380, May.
    14. Koch, Caleb M., 2019. "Index-wise comparative statics," Mathematical Social Sciences, Elsevier, vol. 102(C), pages 35-41.

    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:quante:v:6:y:2015:i:1:p:49-83. 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.

    We have no bibliographic references for this item. You can help adding them by using 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://edirc.repec.org/data/essssea.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.