A1124
Title: Estimating quantile treatment effects for panel data
Authors: Zongwu Cai - University of Kansas (United States) [presenting]
Ying Fang - Xiamen University (China)
Ming Lin - Xiamen University (China)
Mingfeng Zhan - Xiamen University (China)
Abstract: Motivated by a previous work that proposed a factor-based model to estimate the average treatment effect with panel data, a quantile treatment effect model for panel data is suggested to characterize the distributional effect of a treatment. We utilize the relationship between conditional cumulative distributional function (CDF) and unconditional CDF to estimate the counterfactual quantile for the treated unit. Also, we derive the asymptotic properties for the proposed quantile treatment effect estimator, together with discussing the choice of control units and covariates. A simulation study is conducted to illustrate our method. Finally, the proposed method is applied to estimate the quantile treatment effects of introducing CSI 300 index futures trading on both the log-return and volatility of the stock market in China.
