Statistics Department Hosts Weekly Colloquiums where reputed researchers and scholars in the field of statistics give presentations highlighting their work from academia, industry, and government agencies.

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.