This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension is finite and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and shown to be...

This paper considers the cross-sectional aggregation of nonlinear decision rules derived from intertemporal optimization problems under uncertainty, examining in particular (i) the role of aggregation across decision rules of heterogeneous decision makers as a source of variation and persistence...