Computing Synthetic Controls Using Bilevel Optimization

Pekka Malo, Juha Eskelinen, Xun Zhou and Timo Kuosmanen

MPRA Paper from University Library of Munich, Germany

Abstract: The synthetic control method (SCM) is a major innovation in the estimation of 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 SCM problem can be solved using iterative algorithms based on Tykhonov descent or KKT approximations.

Keywords: Causal effects; Comparative case studies; Policy impact assessment (search for similar items in EconPapers)
JEL-codes: C54 C63 (search for similar items in EconPapers)
Date: 2020-11
New Economics Papers: this item is included in nep-cmp and nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Related works:
Journal Article: Computing Synthetic Controls Using Bilevel Optimization (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:104085

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