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RNN-based counterfactual prediction, with an application to homestead policy and public schooling

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  • Jason Poulos
  • Shuxi Zeng

Abstract

This paper proposes a method for estimating the effect of a policy intervention on an outcome over time. We train recurrent neural networks (RNNs) on the history of control unit outcomes to learn a useful representation for predicting future outcomes. The learned representation of control units is then applied to the treated units for predicting counterfactual outcomes. RNNs are specifically structured to exploit temporal dependencies in panel data, and are able to learn negative and nonlinear interactions between control unit outcomes. We apply the method to the problem of estimating the long-run impact of U.S. homestead policy on public school spending.

Suggested Citation

  • Jason Poulos & Shuxi Zeng, 2017. "RNN-based counterfactual prediction, with an application to homestead policy and public schooling," Papers 1712.03553, arXiv.org, revised May 2021.
  • Handle: RePEc:arx:papers:1712.03553
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    References listed on IDEAS

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    6. Stefan Klößner & Ashok Kaul & Gregor Pfeifer & Manuel Schieler, 2018. "Comparative politics and the synthetic control method revisited: a note on Abadie et al. (2015)," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-11, December.
    7. 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.
    8. Kaul, Ashok & Klößner, Stefan & Pfeifer, Gregor & Schieler, Manuel, 2015. "Synthetic Control Methods: Never Use All Pre-Intervention Outcomes Together With Covariates," MPRA Paper 83790, University Library of Munich, Germany.
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    Cited by:

    1. Jacob Goldin & Julian Nyarko & Justin Young, 2022. "Forecasting Algorithms for Causal Inference with Panel Data," Papers 2208.03489, arXiv.org, revised Aug 2023.
    2. Amit Yaniv-Rosenfeld & Elizaveta Savchenko & Ariel Rosenfeld & Teddy Lazebnik, 2023. "Scheduling BCG and IL-2 Injections for Bladder Cancer Immunotherapy Treatment," Mathematics, MDPI, vol. 11(5), pages 1-13, February.

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