IDEAS home Printed from https://ideas.repec.org/a/wly/emetrp/v91y2023i3p1105-1117.html
   My bibliography  Save this article

Distributional Synthetic Controls

Author

Listed:
  • F. F. Gunsilius

Abstract

The method of synthetic controls is a fundamental tool for evaluating causal effects of policy changes in settings with observational data. In many settings where it is applicable, researchers want to identify causal effects of policy changes on a treated unit at an aggregate level while having access to data at a finer granularity. This article proposes an extension of the synthetic controls estimator that takes advantage of this additional structure and provides nonparametric estimates of the heterogeneity within the aggregate unit. The idea is to replicate the quantile function associated with the treated unit by a weighted average of quantile functions of the control units. This estimator relies on the same mathematical theory as the changes‐in‐changes estimator and can be applied in both repeated cross‐sections and panel data with as little as a single pre‐treatment period. It also provides a unique counterfactual quantile function for any type of distribution.

Suggested Citation

  • F. F. Gunsilius, 2023. "Distributional Synthetic Controls," Econometrica, Econometric Society, vol. 91(3), pages 1105-1117, May.
    • Handle: RePEc:wly:emetrp:v:91:y:2023:i:3:p:1105-1117
    DOI: 10.3982/ECTA18260
    as

    Download full text from publisher

    File URL: https://doi.org/10.3982/ECTA18260
    Download Restriction: no
    File URL: https://libkey.io/10.3982/ECTA18260?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
    ---><---

    References listed on IDEAS

    as
    1. Arindrajit Dube, 2019. "Minimum Wages and the Distribution of Family Incomes," American Economic Journal: Applied Economics, American Economic Association, vol. 11(4), pages 268-304, October.
    2. Olli Ropponen, 2011. "Reconciling the evidence of Card and Krueger (1994) and Neumark and Wascher (2000)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 1051-1057, September.
    3. Card, David & Krueger, Alan B, 1994. "Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania," American Economic Review, American Economic Association, vol. 84(4), pages 772-793, September.
    4. Alberto Abadie & Alexis Diamond & Jens Hainmueller, 2015. "Comparative Politics and the Synthetic Control Method," American Journal of Political Science, John Wiley & Sons, vol. 59(2), pages 495-510, February.
    5. Alberto Abadie & Javier Gardeazabal, 2003. "The Economic Costs of Conflict: A Case Study of the Basque Country," American Economic Review, American Economic Association, vol. 93(1), pages 113-132, March.
    6. 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.
    7. Alan B. Krueger & David Card, 2000. "Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania: Reply," American Economic Review, American Economic Association, vol. 90(5), pages 1397-1420, December.
    8. Alberto Abadie, 2021. "Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects," Journal of Economic Literature, American Economic Association, vol. 59(2), pages 391-425, June.
    9. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    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. Masahiro Kato & Akari Ohda & Masaaki Imaizumi, 2023. "Asymptotically Unbiased Synthetic Control Methods by Distribution Matching," Papers 2307.11127, arXiv.org, revised May 2024.
    2. Tadao Hoshino, 2024. "Functional Spatial Autoregressive Models," Papers 2402.14763, arXiv.org, revised Oct 2024.
    3. Maciej Berk{e}sewicz, 2023. "Survey calibration for causal inference: a simple method to balance covariate distributions," Papers 2310.11969, arXiv.org, revised Mar 2024.
    4. Songnian Chen & Junlong Feng, 2023. "Group-Heterogeneous Changes-in-Changes and Distributional Synthetic Controls," Papers 2307.15313, arXiv.org.
    5. Lu Zhang & Xiaomeng Zhang & Xinyu Zhang, 2024. "Asymptotic Properties of the Distributional Synthetic Controls," Papers 2405.00953, arXiv.org, revised Aug 2024.
    6. Christian Alemán & Christopher Busch & Alexander Ludwig & Raül Santaeulàlia-Llopis, 2022. "A Stage-Based Identification of Policy Effects," Working Papers 1369, Barcelona School of Economics.
    7. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.
    8. Lihua Lei & Timothy Sudijono, 2024. "Inference for Synthetic Controls via Refined Placebo Tests," Papers 2401.07152, arXiv.org, revised Apr 2024.

    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. Masahiro Kato & Akari Ohda & Masaaki Imaizumi, 2023. "Asymptotically Unbiased Synthetic Control Methods by Distribution Matching," Papers 2307.11127, arXiv.org, revised May 2024.
    2. Lu Zhang & Xiaomeng Zhang & Xinyu Zhang, 2024. "Asymptotic Properties of the Distributional Synthetic Controls," Papers 2405.00953, arXiv.org, revised Aug 2024.
    3. Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2019. "Distributional conformal prediction," Papers 1909.07889, arXiv.org, revised Aug 2021.
    4. Ayala, Luis & Martín-Román, Javier & Navarro, Carolina, 2023. "Unemployment shocks and material deprivation in the European Union: A synthetic control approach," Economic Systems, Elsevier, vol. 47(1).
    5. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2021. "An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1849-1864, October.
    6. Gharehgozli, Orkideh, 2021. "An empirical comparison between a regression framework and the Synthetic Control Method," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 70-81.
    7. Campos Vázquez, Raymundo Miguel & Rodas Milián, James Alexis, 2020. "El efecto faro del salario mínimo en la estructura salarial: evidencias para México," El Trimestre Económico, Fondo de Cultura Económica, vol. 87(345), pages 51-97, enero-mar.
    8. David Gilchrist & Thomas Emery & Nuno Garoupa & Rok Spruk, 2023. "Synthetic Control Method: A tool for comparative case studies in economic history," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 409-445, April.
    9. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.
    10. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2019. "Inference on average treatment effects in aggregate panel data settings," CeMMAP working papers CWP32/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2018. "A $t$-test for synthetic controls," Papers 1812.10820, arXiv.org, revised Jan 2024.
    12. Songnian Chen & Junlong Feng, 2023. "Group-Heterogeneous Changes-in-Changes and Distributional Synthetic Controls," Papers 2307.15313, arXiv.org.
    13. Nuno Garoupa & Rok Spruk, 2024. "Populist Constitutional Backsliding and Judicial Independence: Evidence from Turkiye," Papers 2410.02439, arXiv.org.
    14. Echevarría, Cruz A. & Hasancebi, Serhat & García-Enríquez, Javier, 2022. "Economic Effects of Macao’s Integration with Mainland China: A Causal Inference Study," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 37(2), pages 179-215.
    15. Manuel Funke & Moritz Schularick & Christoph Trebesch, 2023. "Populist Leaders and the Economy," American Economic Review, American Economic Association, vol. 113(12), pages 3249-3288, December.
    16. Maximiliano Marzetti & Rok Spruk, 2023. "Long-Term Economic Effects of Populist Legal Reforms: Evidence from Argentina," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 65(1), pages 60-95, March.
    17. Brett Parker, 2021. "Death Penalty Statutes and Murder Rates: Evidence From Synthetic Controls," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 18(3), pages 488-533, September.
    18. Chuku Chuku & Mustafa Yasin Yenice, 2021. "Working Paper 356 - Eurobonds, debt sustainability and macroeconomic performance in Africa: Synthetic controlled experiments," Working Paper Series 2482, African Development Bank.
    19. Sadeghi, Ali & Kibler, Ewald, 2022. "Do bankruptcy laws matter for entrepreneurship? A Synthetic Control Method analysis of a bankruptcy reform in Finland," Journal of Business Venturing Insights, Elsevier, vol. 18(C).
    20. Denti, Daria & Iammarino, Simona, 2022. "Coming Out of the Woods. Do local support services influence the propensity to report sexual violence?," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 334-352.

    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:emetrp:v:91:y:2023:i:3:p:1105-1117. 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: 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.