关键词: 处理效应, 非参数框架, 内生性, 高新技术企业认证政策

Abstract: The assumptions are quite restrictive in the treatment effect model used by current literature on policy evaluation but difficult to verify in practice. Once the assumptions are mistaken, parameter estimation will be inconsistent. Firstly, this paper proposes a semi-parametric estimation method for treatment effect model under a non-parametric framework. In our model, we don’t assume functional forms, and also allow the joint distribution of the error terms to be a general form of heteroscedasticity, which greatly reduces the risk of model misspecification. This paper considers treatment effect under endogeneity, and proposes a two-step approach. The first step uses a non-parametric estimator in the selection equation, and the second step uses an instrumental variables approach to estimate average treatment effect in the outcome equation. Secondly, the proposed estimator is shown to be consistent and asymptotically normally distributed. Furthermore, compared with the existing methods, the Monte Carlo simulation result shows our method is more robust. Finally, we apply our method to empirically estimate the impact of certification policy for high-tech enterprises on their profitability, and find this policy can help promote the profitability, and has a greater impact on private enterprises than state-owned enterprises.

Key words: Treatment Effect, Non-parametric Framework, Endogeneity, Certification Policy for High-tech Enterprises