IDEAS home Printed from https://ideas.repec.org/p/cge/wacage/184.html
   My bibliography  Save this paper

Fuzzy Changes-in Changes

Author

Listed:
  • de Chaisemartin, Clement

    (University of Warwick)

  • D'Haultfoeuille, Xavier

    (CREST)

Abstract

The changes-in-changes model extends the widely used difference-in-differences to situations where outcomes may evolve heterogeneously. Contrary to difference-in-differences, this model is invariant to the scaling of the outcome. This paper develops an instrumental variable changes-in-changes model, to allow for situations in which perfect control and treatment groups cannot be defined, so that some units may be treated in the "control group", while some units may remain untreated in the "treatment group". This is the case for instance with repeated cross sections, if the treatment is not tied to a strict rule. Under a mild strengthening of the changes-in-changes model, treatment effects in a population of compliers are point identified when the treatment rate does not change in the control group, and partially identified otherwise. Simple plug-in estimators of treatment effects are proposed. We show that they are asymptotically normal, and that the bootstrap is valid. Finally, we use our results to reanalyze findings in Field (2007) and Duo (2001).

Suggested Citation

  • de Chaisemartin, Clement & D'Haultfoeuille, Xavier, 2014. "Fuzzy Changes-in Changes," CAGE Online Working Paper Series 184, Competitive Advantage in the Global Economy (CAGE).
  • Handle: RePEc:cge:wacage:184
    as

    Download full text from publisher

    File URL: https://www2.warwick.ac.uk/fac/soc/economics/research/centres/cage/manage/publications/184-2014clement.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Anders Akerman & Ingvil Gaarder & Magne Mogstad, 2015. "The Skill Complementarity of Broadband Internet," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1781-1824.
    2. Robin Burgess & Rohini Pande, 2005. "Do Rural Banks Matter? Evidence from the Indian Social Banking Experiment," American Economic Review, American Economic Association, vol. 95(3), pages 780-795, June.
    3. Esther Duflo, 2001. "Schooling and Labor Market Consequences of School Construction in Indonesia: Evidence from an Unusual Policy Experiment," American Economic Review, American Economic Association, vol. 91(4), pages 795-813, September.
    4. Xavier d'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013. "Nonlinear difference-in-differences in repeated cross sections with continuous treatments," CeMMAP working papers CWP40/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Lance Lochner & Enrico Moretti, 2004. "The Effect of Education on Crime: Evidence from Prison Inmates, Arrests, and Self-Reports," American Economic Review, American Economic Association, vol. 94(1), pages 155-189, March.
    6. Guido W. Imbens & Donald B. Rubin, 1997. "Estimating Outcome Distributions for Compliers in Instrumental Variables Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 555-574.
    7. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
    8. Erica Field, 2007. "Entitled to Work: Urban Property Rights and Labor Supply in Peru," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(4), pages 1561-1602.
    9. Donald W. K. Andrews & Gustavo Soares, 2010. "Inference for Parameters Defined by Moment Inequalities Using Generalized Moment Selection," Econometrica, Econometric Society, vol. 78(1), pages 119-157, January.
    10. Edward Vytlacil, 2002. "Independence, Monotonicity, and Latent Index Models: An Equivalence Result," Econometrica, Econometric Society, vol. 70(1), pages 331-341, January.
    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. C de Chaisemartin & X D’HaultfŒuille, 2018. "Fuzzy Differences-in-Differences," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(2), pages 999-1028.
    2. de Chaisemartin, Clement & D'Haultfoeuille, Xavier, 2014. "Fuzzy Changes-in Changes," CAGE Online Working Paper Series 184, Competitive Advantage in the Global Economy (CAGE).
    3. Daniel Herrera‐Araujo, 2016. "Folic acid advisories: a public health challenge?," Health Economics, John Wiley & Sons, Ltd., vol. 25(9), pages 1104-1122, September.

    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. C de Chaisemartin & X D’HaultfŒuille, 2018. "Fuzzy Differences-in-Differences," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(2), pages 999-1028.
    2. 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.
    3. Sun, Zhenting, 2023. "Instrument validity for heterogeneous causal effects," Journal of Econometrics, Elsevier, vol. 237(2).
    4. Evan K. Rose & Yotam Shem-Tov, 2021. "On Recoding Ordered Treatments as Binary Indicators," Papers 2111.12258, arXiv.org, revised Mar 2024.
    5. Nikolov, Plamen & Jimi, Nusrat & Chang, Jerray, 2020. "The Importance of Cognitive Domains and the Returns to Schooling in South Africa: Evidence from Two Labor Surveys," Labour Economics, Elsevier, vol. 65(C).
    6. Patrick Kline & Christopher R. Walters, 2019. "On Heckits, LATE, and Numerical Equivalence," Econometrica, Econometric Society, vol. 87(2), pages 677-696, March.
    7. Susan Athey & Guido W. Imbens, 2006. "Identification and Inference in Nonlinear Difference-in-Differences Models," Econometrica, Econometric Society, vol. 74(2), pages 431-497, March.
    8. Michael R.M. Abrigo & Timothy J. Halliday & Teresa Molina, 2022. "Expanding health insurance for the elderly of the Philippines," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 500-520, April.
    9. Sho Miyaji, 2024. "Instrumented Difference-in-Differences with Heterogeneous Treatment Effects," Papers 2405.12083, arXiv.org, revised Jul 2024.
    10. Toru Kitagawa, 2013. "A bootstrap test for instrument validity in heterogeneous treatment effect models," CeMMAP working papers CWP53/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Abadie, Alberto, 2003. "Semiparametric instrumental variable estimation of treatment response models," Journal of Econometrics, Elsevier, vol. 113(2), pages 231-263, April.
    12. Carneiro, Pedro & Lee, Sokbae, 2009. "Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality," Journal of Econometrics, Elsevier, vol. 149(2), pages 191-208, April.
    13. Kaspar Wüthrich, 2020. "A Comparison of Two Quantile Models With Endogeneity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 443-456, April.
    14. Amanda E Kowalski, 2023. "Behaviour within a Clinical Trial and Implications for Mammography Guidelines," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(1), pages 432-462.
    15. Sho Miyaji, 2024. "Instrumented Difference-in-Differences with Heterogeneous Treatment Effects," Discussion Paper Series DP2024-22, Research Institute for Economics & Business Administration, Kobe University.
    16. Philip Marx, 2020. "Sharp Bounds in the Latent Index Selection Model," Papers 2012.02390, arXiv.org, revised Apr 2023.
    17. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    18. Machado, Cecilia & Shaikh, Azeem M. & Vytlacil, Edward J., 2019. "Instrumental variables and the sign of the average treatment effect," Journal of Econometrics, Elsevier, vol. 212(2), pages 522-555.
    19. Martin Huber & Giovanni Mellace, 2015. "Testing Instrument Validity for LATE Identification Based on Inequality Moment Constraints," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 398-411, May.
    20. Blaise Melly und Kaspar W thrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.

    More about this item

    Keywords

    differences in differences; changes in changes; imperfect compliance; instrumental variables; quantile treatment effects; partial identication.;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cge:wacage:184. 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: Jane Snape (email available below). General contact details of provider: https://edirc.repec.org/data/dewaruk.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.