IDEAS home Printed from https://ideas.repec.org/p/wrk/warwec/1466.html
   My bibliography  Save this paper

Synthetic Decomposition for Counterfactual Predictions

Author

Listed:
  • Canen, Nathan

    (University of Houston, University of Warwick & NBER)

  • Song, Kyungchul

    (University of British Columbia)

Abstract

Counterfactual predictions are challenging when the policy variable goes beyond its pre-policy support. However, in many cases, information about the policy of interest is available from different (“source”) regions where a similar policy has already been implemented. In this paper, we propose a novel method of using such data from source regions to predict a new policy in a target region. Instead of relying on extrapolation of a structural relationship using a parametric specification, we formulate a transferability condition and construct a synthetic outcome-policy relationship such that it is as close as possible to meeting the condition. The synthetic relationship weighs both the similarity in distributions of observables and in structural relationships. We develop a general procedure to construct asymptotic confidence intervals for counterfactual predictions and prove its asymptotic validity. We then apply our proposal to predict average teenage employment in Texas following a counterfactual increase in the minimum wage.

Suggested Citation

  • Canen, Nathan & Song, Kyungchul, 2023. "Synthetic Decomposition for Counterfactual Predictions," The Warwick Economics Research Paper Series (TWERPS) 1466, University of Warwick, Department of Economics.
    • Handle: RePEc:wrk:warwec:1466
    as

    Download full text from publisher

    File URL: https://warwick.ac.uk/fac/soc/economics/research/workingpapers/2023/twerp_1466_-_canen.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Diaa Al Mohamad & Erik W Van Zwet & Eric Cator & Jelle J Goeman, 2020. "Adaptive critical value for constrained likelihood ratio testing," Biometrika, Biometrika Trust, vol. 107(3), pages 677-688.
    2. Honore, Bo E. & Powell, James L., 1994. "Pairwise difference estimators of censored and truncated regression models," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 241-278.
    3. Canen, Nathan & Song, Kyungchul, 2023. "Synthetic Decomposition for Counterfactual Predictions," The Warwick Economics Research Paper Series (TWERPS) 1466, University of Warwick, Department of Economics.
    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. Canen, Nathan & Song, Kyungchul, 2023. "Synthetic Decomposition for Counterfactual Predictions," The Warwick Economics Research Paper Series (TWERPS) 1466, University of Warwick, Department of Economics.

    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. Zhang, Xuelin, 2007. "Gender Differences in Quits and Absenteeism in Canada," Analytical Studies Branch Research Paper Series 2007296e, Statistics Canada, Analytical Studies Branch.
    2. Charlier, Erwin & Melenberg, Bertrand & van Soest, Arthur, 2000. "Estimation of a censored regression panel data model using conditional moment restrictions efficiently," Journal of Econometrics, Elsevier, vol. 95(1), pages 25-56, March.
    3. Alejandro Cid & Daniel Ferres & Máximo Rossi, 2008. "Subjective Well-Being in the Southern Cone: Health, Income and Family," Documentos de Trabajo (working papers) 1308, Department of Economics - dECON.
    4. Emmanuel Selorm Tsyawo, 2023. "Feasible IV regression without excluded instruments," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 235-256.
    5. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    6. Isaiah Andrews & Maximilian Kasy, 2019. "Identification of and Correction for Publication Bias," American Economic Review, American Economic Association, vol. 109(8), pages 2766-2794, August.
    7. P. Čížek & S. Sadikoglu, 2018. "Bias-corrected quantile regression estimation of censored regression models," Statistical Papers, Springer, vol. 59(1), pages 215-247, March.
    8. Di Addario, Sabrina & Kline, Patrick & Saggio, Raffaele & Sølvsten, Mikkel, 2023. "It ain’t where you’re from, it’s where you’re at: Hiring origins, firm heterogeneity, and wages," Journal of Econometrics, Elsevier, vol. 233(2), pages 340-374.
    9. Khan, Shakeeb & Powell, James L., 2001. "Two-step estimation of semiparametric censored regression models," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 73-110, July.
    10. Orazio P. Attanasio & Pinelopi Koujianou Goldberg & Ekaterini Kyriazidou, 2008. "Credit Constraints In The Market For Consumer Durables: Evidence From Micro Data On Car Loans," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 49(2), pages 401-436, May.
    11. Khan, Shakeeb & Lewbel, Arthur, 2007. "Weighted And Two-Stage Least Squares Estimation Of Semiparametric Truncated Regression Models," Econometric Theory, Cambridge University Press, vol. 23(2), pages 309-347, April.
    12. Aradillas-Lopez, Andres, 2012. "Pairwise-difference estimation of incomplete information games," Journal of Econometrics, Elsevier, vol. 168(1), pages 120-140.
    13. Steven Caudill, 2012. "A partially adaptive estimator for the censored regression model based on a mixture of normal distributions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(2), pages 121-137, June.
    14. Tianxi Cai & Lu Tian & L. J. Wei, 2004. "Semi-parametric Box-Cox Power Transformation Models for Censored Survival Observations," Harvard University Biostatistics Working Paper Series 1006, Berkeley Electronic Press.
    15. Khan, Shakeeb & Ponomareva, Maria & Tamer, Elie, 2016. "Identification of panel data models with endogenous censoring," Journal of Econometrics, Elsevier, vol. 194(1), pages 57-75.
    16. Wojciech Kopczuk, 2007. "Bequest and Tax Planning: Evidence from Estate Tax Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(4), pages 1801-1854.
    17. Koen Jochmans, 2013. "Pairwise‐comparison estimation with non‐parametric controls," Econometrics Journal, Royal Economic Society, vol. 16(3), pages 340-372, October.
    18. Alan Sule & Honoré Bo E. & Hu Luojia & Leth-Petersen Søren, 2014. "Estimation of Panel Data Regression Models with Two-Sided Censoring or Truncation," Journal of Econometric Methods, De Gruyter, vol. 3(1), pages 1-20, January.
    19. Marcel Fafchamps & Agnes R. Quisumbing, 2003. "Social roles, human capital, and the intrahousehold division of labor: evidence from Pakistan," Oxford Economic Papers, Oxford University Press, vol. 55(1), pages 36-80, January.
    20. Timothy J. Classen & Richard A. Dunn, 2012. "The effect of job loss and unemployment duration on suicide risk in the United States: a new look using mass‐layoffs and unemployment duration," Health Economics, John Wiley & Sons, Ltd., vol. 21(3), pages 338-350, March.

    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:wrk:warwec:1466. 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: Margaret Nash (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.