Computing Synthetic Controls Using Bilevel Optimization

被引：0

作者：

Malo, Pekka ^{[1
]}

Eskelinen, Juha ^{[1
]}

Zhou, Xun ^{[2
]}

Kuosmanen, Timo ^{[3
]}

机构：

[1] Aalto Univ, Sch Business, Dept Informat & Serv Management, Espoo, Finland

[2] Univ York, Dept Environm & Geog, York, England

[3] Univ Turku, Turku Sch Econ, Dept Econ, Turku, Finland

来源：

COMPUTATIONAL ECONOMICS | 2024年 / 64卷 / 02期

关键词：

Causal effects; Comparative case studies; Policy impact assessment; Bilevel optimization; C31; C54; C61; ECONOMIC COSTS;

D O I：

10.1007/s10614-023-10471-7

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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.

引用

页码：1113 / 1136

页数：24

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