IDEAS home Printed from https://ideas.repec.org/p/boc/scon21/15.html

allsynth: Synthetic control bias-corrections utilities for Stata

Author

Listed:
  • Justin Wiltshire

    (University of California, Davis)

Abstract

The synthetic control method has become a widely adopted empirical approach for estimating counterfactuals and treatment effects. The synth module written for Stata (Abadie, Diamond, and Hainmueller 2010) is widely used by practitioners and serves as the foundation for the synth_runner utilities package (Galiani and Quistorff 2018), which enhances functionality. An active literature has proposed numerous modifications to the "classic" approach, including a bias-correction procedure (Abadie and L'Hour 2020), analogous to that in Abadie and Imbens (2011) for matching estimators, to remove bias that results from differences in the predictor variables between a treated unit and its synthetic control donors. allsynth adds functionality to the synth module, which implements this bias-correction procedure and automates extension of the procedure to placebo runs for in-space randomization inference and graphing.

Suggested Citation

  • Justin Wiltshire, 2021. "allsynth: Synthetic control bias-corrections utilities for Stata," 2021 Stata Conference 15, Stata Users Group.
    • Handle: RePEc:boc:scon21:15
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/scon2021/US21_Wiltshire.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Firpo Sergio & Possebom Vitor, 2018. "Synthetic Control Method: Inference, Sensitivity Analysis and Confidence Sets," Journal of Causal Inference, De Gruyter, vol. 6(2), pages 1-26, September.
    2. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2021. "The Augmented Synthetic Control Method," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1789-1803, October.
    3. Alberto Abadie & Guido W. Imbens, 2011. "Bias-Corrected Matching Estimators for Average Treatment Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 1-11, January.
    4. 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.
    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. Eduardo Cavallo & Sebastian Galiani & Ilan Noy & Juan Pantano, 2013. "Catastrophic Natural Disasters and Economic Growth," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1549-1561, December.
    7. 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.
    8. Nikolay Doudchenko & Guido W. Imbens, 2016. "Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis," NBER Working Papers 22791, National Bureau of Economic Research, Inc.
    9. Sebastian Galiani & Brian Quistorff, 2017. "The synth runner package: Utilities to automate synthetic control estimation using synth," Stata Journal, StataCorp LLC, vol. 17(4), pages 834-849, December.
    10. Dube, Arindrajit & Zipperer, Ben, 2015. "Pooling Multiple Case Studies Using Synthetic Controls: An Application to Minimum Wage Policies," IZA Discussion Papers 8944, IZA Network @ LISER.
    11. Ferman, Bruno & Pinto, Cristine, 2017. "Placebo Tests for Synthetic Controls," MPRA Paper 78079, University Library of Munich, Germany.
    12. Jinyong Hahn & Ruoyao Shi, 2017. "Synthetic Control and Inference," Econometrics, MDPI, vol. 5(4), pages 1-12, November.
    13. 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.
    14. Alberto Abadie & Jérémy L’Hour, 2021. "A Penalized Synthetic Control Estimator for Disaggregated Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1817-1834, October.
    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. Justin C. Wiltshire, 2023. "Walmart Supercenters and Monopsony Power: How A Large, Low-Wage Employer Impacts Local Labor Markets," Department Discussion Papers 2304, Department of Economics, University of Victoria.
    2. 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.
    3. 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.
    4. Dennis Shen & Peng Ding & Jasjeet Sekhon & Bin Yu, 2022. "Same Root Different Leaves: Time Series and Cross-Sectional Methods in Panel Data," Papers 2207.14481, arXiv.org, revised Oct 2022.
    5. Taehyeon Koo & Zijian Guo, 2025. "Distributionally Robust Synthetic Control: Ensuring Robustness Against Highly Correlated Controls and Weight Shifts," Papers 2511.02632, arXiv.org, revised Jan 2026.
    6. Giovanni Peri & Derek Rury & Justin C. Wiltshire, 2024. "The Economic Impact of Migrants from Hurricane Maria," Journal of Human Resources, University of Wisconsin Press, vol. 59(6), pages 1795-1829.
    7. Garoupa, Nuno & Spruk, Rok, 2025. "Populist constitutional backsliding and judicial independence: Evidence from Türkiye," International Review of Law and Economics, Elsevier, vol. 84(C).
    8. Alberto Abadie & Jinglong Zhao, 2021. "Synthetic Controls for Experimental Design," Papers 2108.02196, arXiv.org, revised Apr 2025.
    9. Chen, Qiang & Xiao, Zhijie & Yao, Qingsong, 2025. "Quantile control via random forest," Journal of Econometrics, Elsevier, vol. 249(PA).
    10. Bruno Ferman & Cristine Pinto & Vitor Possebom, 2020. "Cherry Picking with Synthetic Controls," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(2), pages 510-532, March.
    11. Michael Funke & Helery Tasane, 2025. "Regional economic impacts of the Øresund cross-border fixed link: Cui Bono?," Regional Studies, Taylor & Francis Journals, vol. 59(1), pages 2573115-257, December.
    12. Andrii Melnychuk, 2024. "Synthetic Controls with spillover effects: A comparative study," Papers 2405.01645, arXiv.org.
    13. Saeyoung Rho & Cyrus Illick & Samhitha Narasipura & Alberto Abadie & Daniel Hsu & Vishal Misra, 2026. "Time-Aware Synthetic Control," Papers 2601.03099, arXiv.org.
    14. McCloud, Nadine & Ivey, Wendel & Taylor, Ajornie, 2026. "The workforce paradox: Do extreme natural disasters accelerate or undermine labour productivity?," Economic Modelling, Elsevier, vol. 154(C).
    15. Clair, Travis St., 2024. "The fiscal effects of immigration on local governments: Revisiting the Mariel Boatlift," Regional Science and Urban Economics, Elsevier, vol. 109(C).
    16. Natalia Orlova & Derek Rury & Justin C. Wiltshire, 2026. "Lifting the cap on non-resident university enrollment: evidence from Wisconsin," Empirical Economics, Springer, vol. 70(3), pages 1-29, March.
    17. Guillaume Allaire Pouliot & Zhen Xie & Ziyi Liu, 2022. "Degrees of Freedom and Information Criteria for the Synthetic Control Method," Papers 2207.02943, arXiv.org, revised Mar 2026.
    18. Pier Basaglia & Sophie M. Behr & Moritz A. Drupp & Piero Basaglia, 2023. "De-Fueling Externalities: Causal Effects of Fuel Taxation and Mediating Mechanisms for Reducing Climate and Pollution Costs," CESifo Working Paper Series 10508, CESifo.
    19. Tomasz Serwach, 2023. "The European Union and within‐country income inequalities. The case of the new member states," The World Economy, Wiley Blackwell, vol. 46(7), pages 1890-1939, July.
    20. Giulio Grossi, 2023. "The policy is always greener: impact heterogeneity of Covid-19 vaccination lotteries in the US," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(4), pages 1351-1375, October.

    More about this item

    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:boc:scon21:15. 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: Christopher F Baum (email available below). General contact details of provider: https://edirc.repec.org/data/stataea.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.