A Quasi Synthetic Control Method for Nonlinear Models With High-Dimensional Covariates

Zongwu Cai, Ying Fang, Ming Lin and Zixuan Wu
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Zongwu Cai: Department of Economics, The University of Kansas, Lawrence, KS 66045, USA
Ying Fang: The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, Fujian 361005, China and Department of Statistics & Data Science, School of Economics, Xiamen University, Xiamen, Fujian 361005, China
Ming Lin: The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, Fujian 361005, China and Department of Statistics and Data Science, School of Economics, Xiamen University, Xiamen, Fujian 361005, China
Zixuan Wu: Department of Statistics and Data Science, School of Economics, Xiamen University, Xiamen, Fujian 361005, China

No 202305, WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS from University of Kansas, Department of Economics

Abstract: To make the conventional synthetic control method more flexible to estimate the average treatment effect, this article proposes a quasi synthesis control method for nonlinear models under the index model framework with possible high-dimensional covariates, together with a suggestion of using the minimum average variance estimation method to estimate parameters and the LASSO type procedure to choose covariates. Also, we derive the asymptotic distribution of the proposed estimators. A properly designed Bootstrap method is proposed to obtain confidence intervals and its theoretical justification is provided. Finally, Monte Carlo simulation studies are conducted to illustrate the finite sample performance and an empirical application to re-analyze the data from the National Supported Work Demonstration is also considered to demonstrate the proposed model to be practically useful.

Keywords: Average treatment effect; Bootstrap inference; Index model; Minimum average variance estimation method; Semiparametric estimation; Synthetic control method (search for similar items in EconPapers)
JEL-codes: C01 C14 C54 (search for similar items in EconPapers)
Date: 2023-02, Revised 2023-08
New Economics Papers: this item is included in nep-ecm and nep-sea
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