SEMINAR HAS BEEN CANCELLED Outlier Robust Inference in the Instrumental Variable Model With Applications to Causal Effects

The instrumental variable model is one of the central tools for the

analysis of causal relationships in observational data. The Anderson and Rubin

(1949) test is an important method that allows for reliable inference in the

instrumental variable model when the instruments are weak. Yet, the robustness

properties of this test have not been formally studied. As it turns out that

the Anderson-Rubin (AR) test is not robust to outliers, we show how to

construct an outlier robust alternative - the robust AR test. We investigate

the robustness properties of the robust AR test and show that the robust AR

statistic asymptotically follows a chi-square distribution. The theoretical

results are illustrated by a simulation study. Finally, we apply the robust AR

test to three different case studies that are affected by different types of

outliers.

with Mikhail Zhelonkin

for the Zoom link, please send an email to: crutzen@ese.eur.nl or stolting@ese.eur.nl