Computing Synthetic Controls Using Bilevel Optimization

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dc.contributor.authorMalo Pekka
dc.contributor.authorEskelinen Juha
dc.contributor.authorZhou Xun
dc.contributor.authorKuosmanen Timo
dc.contributor.organizationfi=taloustiede|en=Economics|
dc.contributor.organization-code1.2.246.10.2458963.20.17691981389
dc.converis.publication-id181479863
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/181479863
dc.date.accessioned2025-08-27T22:07:44Z
dc.date.available2025-08-27T22:07:44Z
dc.description.abstractThe 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.
dc.identifier.eissn1572-9974
dc.identifier.jour-issn0927-7099
dc.identifier.olddbid201690
dc.identifier.oldhandle10024/184717
dc.identifier.urihttps://www.utupub.fi/handle/11111/48804
dc.identifier.urlhttps://link.springer.com/article/10.1007/s10614-023-10471-7
dc.identifier.urnURN:NBN:fi-fe2025082789536
dc.language.isoen
dc.okm.affiliatedauthorKuosmanen, Timo
dc.okm.discipline111 Mathematicsen_GB
dc.okm.discipline512 Business and managementen_GB
dc.okm.discipline111 Matematiikkafi_FI
dc.okm.discipline512 Liiketaloustiedefi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherSpringer
dc.publisher.countryNetherlandsen_GB
dc.publisher.countryAlankomaatfi_FI
dc.publisher.country-codeNL
dc.relation.doi10.1007/s10614-023-10471-7
dc.relation.ispartofjournalComputational Economics
dc.source.identifierhttps://www.utupub.fi/handle/10024/184717
dc.titleComputing Synthetic Controls Using Bilevel Optimization
dc.year.issued2023

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