Before revision:  Motivated by these studies, we construct a new IV estimator, which is based on the time-series model for the aggregate shock. 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.
After revision:  Motivated by these studies, we construct a new IV estimator, which is based on the time-series model to extract the quasi-random variation from the observed shock. We examine our algorithm's performance in a realistic simulation based on Nakamura and Steinsson ] our estimator in a practically relevant case , where both cross-sectional and time-series dimensions are of similar size.