Before revision:  We analyze the statistical properties of ] our estimator in a practically relevant case , where both cross-sectional and time-series dimensions are of similar size. Finally, to provide a causal interpretation for our estimator, we analyze a new causal model that allows taking into account both rich unobserved heterogeneity in potential outcomes and unobserved aggregate shocks .
After revision:  We analyze the statistical properties of ] our estimator in a practically relevant case , where both cross-sectional and time-series dimensions are large and show how to use it to conduct robust inference .