Before revision:  When applied in panel settings our methods provide a novel approach to  identification with non-separable general heterogeneity and a fixed time dimension. In the panel case , observations from different periods serve as proxies for unobserved individual heterogeneity and our key identifying assumptions follow from restrictions on the serial dependence structure of the data and latent variables .
After revision:  When applied in panel settings our methods provide a novel approach to identification with non-separable general heterogeneity and fixed T. In panels , observations from different periods serve as proxies for unobserved individual heterogeneity and our key identifying assumptions follow from restrictions on the serial dependence structure of the data and latent variables .