[Statlist] Joint Event: ETH/UZH Research Seminar on Statistics and FDS Seminar talk by Zijian Guo, Rutgers University, USA, 22.09.2023

[Maurer Letizia]

We are pleased to announce and invite you to the following joint talk in our ETH/UZH Research Seminar on Statistics and FDS seminar series:

"Robust Causal Inference with Possibly Invalid Instruments: Post-selection Problems and A Solution Using Searching and Sampling "   

by Zijian Guo, Rutgers University, USA

Time: Friday,  22.09.2023 at 15.15 h
Place: ETH Zurich, HG G 19.1

Abstract: Instrumental variable methods are among the most commonly used causal inference approaches to deal with unmeasured confounders in observational studies. The presence of invalid instruments is the primary concern for practical applications, and a fast-growing area of research is inference for the causal effect with possibly invalid instruments. This paper illustrates that the existing confidence intervals may undercover when the valid and invalid instruments are hard to separate in a data-dependent way. To address this, we construct uniformly valid confidence intervals that are robust to the mistakes in separating valid and invalid instruments. We propose to search for a range of treatment effect values that lead to sufficiently many valid instruments. We further devise a novel sampling method, which, together with searching, leads to a more precise confidence interval. Our proposed searching and sampling confidence intervals are uniformly valid and achieve the parametric length under the finite-sample majority and plurality rules. We apply our proposal to examine the effect of education on earnings. The proposed method is implemented in the R package \texttt{RobustIV} available from CRAN.


Seminar website: 	https://math.ethz.ch/sfs/news-and-events/research-seminar.html
				https://math.ethz.ch/sfs/eth-foundations-of-data-science.html