IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v130y2006i2p253-272.html
   My bibliography  Save this article

Identification and estimation with contaminated data: When do covariate data sharpen inference?

Author

Listed:
  • Mullin, Charles H.

Abstract

No abstract is available for this item.

Suggested Citation

  • Mullin, Charles H., 2006. "Identification and estimation with contaminated data: When do covariate data sharpen inference?," Journal of Econometrics, Elsevier, vol. 130(2), pages 253-272, February.
  • Handle: RePEc:eee:econom:v:130:y:2006:i:2:p:253-272
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4076(05)00054-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, vol. 63(2), pages 281-302, March.
    2. V. Joseph Hotz & Charles H. Mullin & Seth G. Sanders, 1997. "Bounding Causal Effects Using Data from a Contaminated Natural Experiment: Analysing the Effects of Teenage Childbearing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 575-603.
    3. Philip J. Cross & Charles F. Manski, 2002. "Regressions, Short and Long," Econometrica, Econometric Society, vol. 70(1), pages 357-368, January.
    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. Charles F. Manski, 2003. "Identification Problems in the Social Sciences and Everyday Life," Southern Economic Journal, John Wiley & Sons, vol. 70(1), pages 11-21, July.
    2. Molinari, Francesca, 2010. "Missing Treatments," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 82-95.
    3. Guido W. Imbens & Charles F. Manski, 2004. "Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 72(6), pages 1845-1857, November.
    4. Philip A. Haile & Elie Tamer, 2003. "Inference with an Incomplete Model of English Auctions," Journal of Political Economy, University of Chicago Press, vol. 111(1), pages 1-51, February.
    5. Francesca Molinari, 2020. "Microeconometrics with Partial Identi?cation," CeMMAP working papers CWP15/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Kaplan, Greg & Goodman, Alissa & Walker, Ian, 2004. "Understanding the Effects of Early Motherhood in Britain: The Effects on Mothers," IZA Discussion Papers 1131, Institute of Labor Economics (IZA).
    7. Tatiana Komarova & Denis Nekipelov & Evgeny Yakovlev, 2018. "Identification, data combination, and the risk of disclosure," Quantitative Economics, Econometric Society, vol. 9(1), pages 395-440, March.
    8. Matthew A. Masten & Alexandre Poirier, 2018. "Identification of Treatment Effects Under Conditional Partial Independence," Econometrica, Econometric Society, vol. 86(1), pages 317-351, January.
    9. V. Joseph Hotz & Susan Williams McElroy & Seth G. Sanders, 2005. "Teenage Childbearing and Its Life Cycle Consequences: Exploiting a Natural Experiment," Journal of Human Resources, University of Wisconsin Press, vol. 40(3).
    10. Matthew Masten & Alexandre Poirier, 2016. "Partial independence in nonseparable models," CeMMAP working papers CWP26/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Molinari, Francesca, 2008. "Partial identification of probability distributions with misclassified data," Journal of Econometrics, Elsevier, vol. 144(1), pages 81-117, May.
    12. Kreider, Brent & Pepper, John V., 2011. "Identification of Expected Outcomes in a Data Error Mixing Model With Multiplicative Mean Independence," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 49-60.
    13. Charles Mullin, 2000. "Bounding Causal Effects with Contaminated and Censored Data: Reassessing the Impact of Early Childbearing on Children," Vanderbilt University Department of Economics Working Papers 0039, Vanderbilt University Department of Economics.
    14. Tanya Byker & Italo A. Gutierrez, 2016. "Treatment Effects Using Inverse Probability Weighting and Contaminated Treatment Data An Application to the Evaluation of a Government Female Sterilization Campaign in Peru," Working Papers WR-1118-1, RAND Corporation.
    15. Yanqin Fan & Carlos A. Manzanares, 2017. "Partial identification of average treatment effects on the treated through difference-in-differences," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 1057-1080, October.
    16. Magnac, Thierry, 2013. "Identification partielle : méthodes et conséquences pour les applications empiriques," L'Actualité Economique, Société Canadienne de Science Economique, vol. 89(4), pages 233-258, Décembre.
    17. Cheti Nicoletti, 2010. "Poverty analysis with missing data: alternative estimators compared," Empirical Economics, Springer, vol. 38(1), pages 1-22, February.
    18. Bhalotra, Sonia & Clarke, Damian & Walther, Selma, 2022. "Women's Careers and Family Formation," GLO Discussion Paper Series 1120, Global Labor Organization (GLO).
    19. Ian Walker & Yu Zhu, 2009. "The Causal Effect of Teen Motherhood on Worklessness," Studies in Economics 0917, School of Economics, University of Kent.
    20. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    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:eee:econom:v:130:y:2006:i:2:p:253-272. 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/jeconom .

    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.