Trimmed Mean Group Estimation of Average Treatment Eﬀects in Ultra Short T Panels under Correlated Heterogeneity
Speaker: Hashem Pesaran (Southern California and Cambridge)
Abstract: Under correlated heterogeneity, the commonly used two-way ﬁxed eﬀects estimator is biased and can lead to misleading inference. This paper proposes a new trimmed mean group (TMG) estimator which is consistent at the irregular rate of n^(1/3) even if the time dimension of the panel is as small as the number of its regressors. Extensions to panels with time eﬀects are provided, and a Hausman-type test of correlated heterogeneity is proposed. Small sample properties of the TMG estimator (with and without time eﬀects) are investigated by Monte Carlo experiments and shown to be satisfactory and perform better than other trimmed estimators proposed in the literature. The proposed test of correlated heterogeneity is also shown to have the correct size and satisfactory power. The utility of the TMG approach is illustrated with an empirical application.
Co-author: Liying Yang
Host: Takashi Yamagata (York)