IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v184y2019ics0165176519303325.html
   My bibliography  Save this article

Nonparametric identification and estimation of dynamic treatment effects for survival data in a regression discontinuity design

Author

Listed:
  • Lv, Xiaofeng
  • Sun, Xu-Ran
  • Lu, Yue
  • Li, Rui

Abstract

Treatment assignment in the survival literature is often assumed to be allocated simultaneously and independently of prospective treatment gains. This paper relaxes these restrictions by introducing dynamic treatment assignment for survival data in a regression discontinuity design. Conditional on a pretreatment duration, we identify two survival functions of the remaining potential durations under treatment and no treatment. Conditional treatment effects can be identified by the difference between the integrals of the two functions, and we aggregate conditional treatment effects over pretreatment durations to identify unconditional ones. Accordingly, nonparametric estimates are proposed.

Suggested Citation

  • Lv, Xiaofeng & Sun, Xu-Ran & Lu, Yue & Li, Rui, 2019. "Nonparametric identification and estimation of dynamic treatment effects for survival data in a regression discontinuity design," Economics Letters, Elsevier, vol. 184(C).
    • Handle: RePEc:eee:ecolet:v:184:y:2019:i:c:s0165176519303325
    DOI: 10.1016/j.econlet.2019.108665
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176519303325
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2019.108665?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Besedes, Tibor & Prusa, Thomas J., 2006. "Product differentiation and duration of US import trade," Journal of International Economics, Elsevier, vol. 70(2), pages 339-358, December.
    2. Blundell, Richard & Powell, James L., 2007. "Censored regression quantiles with endogenous regressors," Journal of Econometrics, Elsevier, vol. 141(1), pages 65-83, November.
    3. Fredriksson, Peter & Johansson, Per, 2008. "Dynamic Treatment Assignment," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 435-445.
    4. Cook, Thomas D., 2008. ""Waiting for Life to Arrive": A history of the regression-discontinuity design in Psychology, Statistics and Economics," Journal of Econometrics, Elsevier, vol. 142(2), pages 636-654, February.
    5. Frolich, Markus, 2007. "Nonparametric IV estimation of local average treatment effects with covariates," Journal of Econometrics, Elsevier, vol. 139(1), pages 35-75, July.
    6. Yi Lu Jr. & Linhui Yu Jr., 2015. "Trade Liberalization and Markup Dispersion: Evidence from China's WTO Accession," American Economic Journal: Applied Economics, American Economic Association, vol. 7(4), pages 221-253, October.
    7. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    8. Choi, Jin-young & Lee, Myoung-jae, 2018. "Regression Discontinuity with Multiple Running Variables Allowing Partial Effects," Political Analysis, Cambridge University Press, vol. 26(3), pages 258-274, July.
    9. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-209, January.
    10. Brigham R. Frandsen, 2015. "Treatment Effects With Censoring and Endogeneity," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1745-1752, December.
    11. Choi, Jin-young & Lee, Myoung-jae, 2018. "Minimum distance estimator for sharp regression discontinuity with multiple running variables," Economics Letters, Elsevier, vol. 162(C), pages 10-14.
    12. Jaap H. Abbring & Gerard J. van den Berg, 2003. "The Nonparametric Identification of Treatment Effects in Duration Models," Econometrica, Econometric Society, vol. 71(5), pages 1491-1517, September.
    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. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.

    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. 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.
    2. Goeun Lee & Myoung-jae Lee, 2023. "Regression Discontinuity for Binary Response and Local Maximum Likelihood Estimator to Extrapolate Treatment," Evaluation Review, , vol. 47(2), pages 182-208, April.
    3. Choi, Jin-young & Lee, Myoung-jae, 2023. "Complier and monotonicity for Fuzzy Multi-score Regression Discontinuity with partial effects," Economics Letters, Elsevier, vol. 228(C).
    4. Frandsen, Brigham R. & Frölich, Markus & Melly, Blaise, 2012. "Quantile treatment effects in the regression discontinuity design," Journal of Econometrics, Elsevier, vol. 168(2), pages 382-395.
    5. Chad D. Meyerhoefer & Muzhe Yang, 2011. "The Relationship between Food Assistance and Health: A Review of the Literature and Empirical Strategies for Identifying Program Effects," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(3), pages 304-344.
    6. Frölich, Markus & Lechner, Michael, 2010. "Exploiting Regional Treatment Intensity for the Evaluation of Labor Market Policies," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1014-1029.
    7. Richard Blundell & Monica Costa Dias, 2009. "Alternative Approaches to Evaluation in Empirical Microeconomics," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
    8. Mazzutti, Caio Cícero Toledo Piza da Costa, 2016. "Three essays on the causal impacts of child labour laws in Brazil," Economics PhD Theses 0616, Department of Economics, University of Sussex Business School.
    9. Papay, John P. & Willett, John B. & Murnane, Richard J., 2011. "Extending the regression-discontinuity approach to multiple assignment variables," Journal of Econometrics, Elsevier, vol. 161(2), pages 203-207, April.
    10. Mauricio Villamizar‐Villegas & Freddy A. Pinzon‐Puerto & Maria Alejandra Ruiz‐Sanchez, 2022. "A comprehensive history of regression discontinuity designs: An empirical survey of the last 60 years," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1130-1178, September.
    11. Jin-young Choi & Myoung-jae Lee, 2017. "Regression discontinuity: review with extensions," Statistical Papers, Springer, vol. 58(4), pages 1217-1246, December.
    12. Tiantian Dai & Shenyi Jiang & Xiangbo Liu & Ang Sun, 2022. "The effects of a hypertension diagnosis on health behaviors: A two‐dimensional regression discontinuity analysis," Health Economics, John Wiley & Sons, Ltd., vol. 31(4), pages 574-596, April.
    13. Pedro H. C. Sant'Anna, 2016. "Program Evaluation with Right-Censored Data," Papers 1604.02642, arXiv.org.
    14. Marinho Bertanha & Guido W. Imbens, 2020. "External Validity in Fuzzy Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(3), pages 593-612, July.
    15. Martin Pereyra & Diego Aboal & Flavia Rovira, 2021. "How effective are training and mentorship programs for entrepreneurs at promoting entrepreneurial activity? An impact evaluation," SN Business & Economics, Springer, vol. 1(7), pages 1-21, July.
    16. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
    17. Nibbering, Didier & Oosterveen, Matthijs & Silva, Pedro Luís, 2022. "Clustered Local Average Treatment Effects: Fields of Study and Academic Student Progress," IZA Discussion Papers 15159, Institute of Labor Economics (IZA).
    18. German Blanco & Xuan Chen & Carlos A. Flores & Alfonso Flores-Lagunes, 2020. "Bounds on Average and Quantile Treatment Effects on Duration Outcomes Under Censoring, Selection, and Noncompliance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(4), pages 901-920, October.
    19. van der Klaauw, Bas, 2014. "From micro data to causality: Forty years of empirical labor economics," Labour Economics, Elsevier, vol. 30(C), pages 88-97.
    20. Giuseppe Francesco Gori & Patrizia Lattarulo & Marco Mariani, 2021. "The Expediting Effect of Monitoring on Infrastructural Works. A Regression-Discontinuity Approach with Multiple Assignment Variables," Papers 2102.09625, arXiv.org.

    More about this item

    Keywords

    Nonparametric identification; Treatment effects; Regression discontinuity; Survival analysis; Dynamic treatment assignment;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

    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:ecolet:v:184:y:2019:i:c:s0165176519303325. 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/ecolet .

    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.