论文标题：Inference on Difference-in-Differences Average Treatment Effects: A Fixed-b Approach

　　发表时间：2019

　　论文所有作者：Yu Sun, Karen X.Yan

　　期刊名及所属分类：Journal of Econometrics(国际A)

　　英文摘要：This paper provides an analysis of the standard errors proposed by Driscoll and Kraay (1998) (DK) in linear Difference-in-Differences (DD) models with fixed effects and individual-specific time trends. The analysis is accomplished within the fixed- b asymptotic framework developed by Kiefer and Vogelsang (2005) for heteroskedasticity and autocorrelation consistent (HAC) covariance matrix estimator based tests. For both the fixed- N , large- T , and large- N , large- T cases, it is shown that fixed- b asymptotic distributions of test statistics constructed using the DD estimator and the DK standard errors are different from the results found by Kiefer and Vogelsang (2005) and Vogelsang (2012). The newly derived fixed- b asymptotic distributions depend on the date of policy change, individual-specific trend functions as well as the choice of kernel and bandwidth. Monte Carlo simulations illustrate the performance of the fixed- b approximations in practice.

　　中文摘要：本文分析了Driscoll和Kraay (1998) (DK)提出的具有固定效应和个体特定时间趋势的线性中差(DD)模型的标准误差。分析是在基弗和沃格桑(2005)开发的基于异方差和自相关一致协方差矩阵估计检验的固定b渐近框架内完成的。为固定N,大- T,和大- N - T大情况下,结果表明,固定- b测试数据构造使用DD估计量的渐近分布和DK标准错误结果发现不同基弗和Vogelsang(2005)和Vogelsang(2012)。新导出的定b渐近分布依赖于政策变化的日期、个体特定的趋势函数以及内核和带宽的选择。蒙特卡罗模拟演示了固定b近似在实践中的表现。