Malo, Pekka, Eskelinen, Juha, Zhou, Xun orcid.org/0000-0003-2093-4508 et al. (1 more author) (2023) Computing Synthetic Controls Using Bilevel Optimization. Computational Economics. ISSN 1572-9974
Abstract
The synthetic control method (SCM) represents a notable innovation in estimating the causal effects of policy interventions and programs in a comparative case study setting. In this paper, we demonstrate that the data-driven approach to SCM requires solving a bilevel optimization problem. We show how the original SCM problem can be solved to the global optimum through the introduction of an iterative algorithm rooted in Tykhonov regularization or Karush–Kuhn–Tucker approximations.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2023 |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Environment and Geography (York) |
Depositing User: | Pure (York) |
Date Deposited: | 26 Sep 2023 08:20 |
Last Modified: | 16 Oct 2024 19:27 |
Published Version: | https://doi.org/10.1007/s10614-023-10471-7 |
Status: | Published online |
Refereed: | Yes |
Identification Number: | 10.1007/s10614-023-10471-7 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:203668 |