IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v24y2017i11p762-765.html
   My bibliography  Save this article

Estimating local average treatment effects in aggregate data

Author

Listed:
  • Nick Huntington-Klein

Abstract

In some contexts, the effect of a treatment can be estimated with easily accessible aggregate rather than individual data, using difference-in-difference estimation. However, under imperfect assignment within groups, this produces intent-to-treat estimates, which may not be the treatment effect of interest. This article provides a method for estimating local average treatment effects using aggregate data. I also suggest a data source that allows the method to be applied when treatment rates are not recorded.

Suggested Citation

  • Nick Huntington-Klein, 2017. "Estimating local average treatment effects in aggregate data," Applied Economics Letters, Taylor & Francis Journals, vol. 24(11), pages 762-765, June.
    • Handle: RePEc:taf:apeclt:v:24:y:2017:i:11:p:762-765
    DOI: 10.1080/13504851.2016.1226483
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13504851.2016.1226483
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13504851.2016.1226483?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. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    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. Arnaud Chevalier & Colm Harmon & Vincent O’ Sullivan & Ian Walker, 2013. "The impact of parental income and education on the schooling of their children," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 2(1), pages 1-22, December.
    2. González-Uribe, Juanita & Reyes, Santiago, 2021. "Identifying and boosting “Gazelles”: Evidence from business accelerators," Journal of Financial Economics, Elsevier, vol. 139(1), pages 260-287.
    3. Roxana Elena Manea, 2021. "School Feeding Programmes, Education and Food Security in Rural Malawi," CIES Research Paper series 63-2020, Centre for International Environmental Studies, The Graduate Institute.
    4. Clément de Chaisemartin & Luc Behaghel, 2020. "Estimating the Effect of Treatments Allocated by Randomized Waiting Lists," Econometrica, Econometric Society, vol. 88(4), pages 1453-1477, July.
    5. Giacomo De Giorgi & Michele Pellizzari & William Gui Woolston, 2012. "Class Size And Class Heterogeneity," Journal of the European Economic Association, European Economic Association, vol. 10(4), pages 795-830, August.
    6. Ron Diris, 2017. "Don't Hold Back? The Effect of Grade Retention on Student Achievement," Education Finance and Policy, MIT Press, vol. 12(3), pages 312-341, Summer.
    7. Angrist, Josh & Lavy, Victor, 2002. "The Effect of High School Matriculation Awards: Evidence from Randomized Trials," CEPR Discussion Papers 3827, C.E.P.R. Discussion Papers.
    8. María laura Alzúa & Guillermo Cruces & Carolina Lopez, 2016. "Long-Run Effects Of Youth Training Programs: Experimental Evidence From Argentina," Economic Inquiry, Western Economic Association International, vol. 54(4), pages 1839-1859, October.
    9. Milo Bianchi & Paolo Buonanno & Paolo Pinotti, 2012. "Do Immigrants Cause Crime?," Journal of the European Economic Association, European Economic Association, vol. 10(6), pages 1318-1347, December.
    10. Miguel Godinho de Matos & Pedro Ferreira, 2020. "The Effect of Binge-Watching on the Subscription of Video on Demand: Results from Randomized Experiments," Information Systems Research, INFORMS, vol. 31(4), pages 1337-1360, December.
    11. Kirill Borusyak & Peter Hull & Xavier Jaravel, 2023. "Design-Based Identification with Formula Instruments: A Review," NBER Working Papers 31393, National Bureau of Economic Research, Inc.
    12. Hoderlein, Stefan & White, Halbert, 2012. "Nonparametric identification in nonseparable panel data models with generalized fixed effects," Journal of Econometrics, Elsevier, vol. 168(2), pages 300-314.
    13. Song, Yang, 2019. "Sorting, school performance and quality: Evidence from China," Journal of Comparative Economics, Elsevier, vol. 47(1), pages 238-261.
    14. Russo, Antonio & Adler, Martin W. & Liberini, Federica & van Ommeren, Jos N., 2021. "Welfare losses of road congestion: Evidence from Rome," Regional Science and Urban Economics, Elsevier, vol. 89(C).
    15. Marco Caliendo & Stefan Tübbicke, 2020. "New evidence on long-term effects of start-up subsidies: matching estimates and their robustness," Empirical Economics, Springer, vol. 59(4), pages 1605-1631, October.
    16. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
    17. Manuel Arellano & Stéphane Bonhomme, 2017. "Quantile Selection Models With an Application to Understanding Changes in Wage Inequality," Econometrica, Econometric Society, vol. 85, pages 1-28, January.
    18. Troske, Kenneth R. & Voicu, Alexandru, 2010. "Joint estimation of sequential labor force participation and fertility decisions using Markov chain Monte Carlo techniques," Labour Economics, Elsevier, vol. 17(1), pages 150-169, January.
    19. Guillermo Cruces & Sebastian Galiani, 2003. "Generalizing the Causal Effect of Fertility on Female Labor Supply," Labor and Demography 0310002, University Library of Munich, Germany.
    20. Bruno Crépon & Esther Duflo & Marc Gurgand & Roland Rathelot & Philippe Zamora, 2013. "Do Labor Market Policies have Displacement Effects? Evidence from a Clustered Randomized Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(2), pages 531-580.

    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:taf:apeclt:v:24:y:2017:i:11:p:762-765. 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/RAEL20 .

    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.