Robust Confidence Intervals for Average Treatment Effects under Limited Overlap

نویسنده

  • Christoph Rothe
چکیده

Robust Confidence Intervals for Average Treatment Effects under Limited Overlap Estimators of average treatment effects under unconfounded treatment assignment are known to become rather imprecise if there is limited overlap in the covariate distributions between the treatment groups. But such limited overlap can also have a detrimental effect on inference, and lead for example to highly distorted confidence intervals. This paper shows that this is because the coverage error of traditional confidence intervals is not so much driven by the total sample size, but by the number of observations in the areas of limited overlap. At least some of these “local sample sizes” are often very small in applications, up to the point where distributional approximation derived from the Central Limit Theorem become unreliable. Building on this observation, the paper proposes two new robust confidence intervals that are extensions of classical approaches to small sample inference. It shows that these approaches are easy to implement, and have superior theoretical and practical properties relative to standard methods in empirically relevant settings. They should thus be useful for practitioners. JEL Classification: C12, C14, C25, C31

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations

This paper concerns robust inference on average treatment effects following model selection. In the selection on observables framework, we show how to construct confidence intervals based on a doubly-robust estimator that are robust to model selection errors and prove that they are valid uniformly over a large class of treatment effect models. The class allows for multivalued treatments with he...

متن کامل

Area specific confidence intervals for a small area mean under the Fay-Herriot model

‎Small area estimates have received much attention from both private and public sectors due to the growing demand for effective planning of health services‎, ‎apportioning of government funds and policy and decision making‎. ‎Surveys are generally designed to give representative estimates at national or district level‎, ‎but estimates of variables of interest are oft...

متن کامل

Exact maximum coverage probabilities of confidence intervals with increasing bounds for Poisson distribution mean

 ‎A Poisson distribution is well used as a standard model for analyzing count data‎. ‎So the Poisson distribution parameter estimation is widely applied in practice‎. ‎Providing accurate confidence intervals for the discrete distribution parameters is very difficult‎. ‎So far‎, ‎many asymptotic confidence intervals for the mean of Poisson distribution is provided‎. ‎It is known that the coverag...

متن کامل

Estimating Average Causal Effects Under General Interference

This paper presents randomization-based methods for estimating average causal effects under arbitrary interference of known form. Conservative estimators of the randomization variance of the average treatment effects estimators are presented, as is justification for confidence intervals based on a normal approximation. Examples relevant to research in environmental protection, networks experime...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015