We consider the dynamic factor model where the loading matrix, the dynamic factors, and the disturbances are treated as latent stochastic processes. We present empirical Bayes methods that enable the shrinkagebased estimation of the loadings and factors. We investigate the methods in a large Monte Carlo study where we evaluate the finite sample properties of the empirical Bayes methods for quadratic loss functions. Finally, we present and discuss the results of an empirical study concerning the forecasting of U.S. macroeconomic time series using our empirical Bayes methods.

We investigate how urban railroad and highway configurations have influenced urban form in Chinese cities since 1990. Each radial highway displaces 4% of central city population to surrounding regions, and ring roads displace about an additional 20%, with stronger effects in the richer coastal and central regions. Each radial railroad reduces central city industrial GDP by about 20%, with ring roads displacing an additional 50%. We provide evidence that radial highways decentralize service sector activity, radial railroads decentralize industrial activity, and ring roads decentralize both. Historical transportation infrastructure provides identifying variation in more recent measures of infrastructure.

We present the results of a field experiment conducted at Harvard Medical School to understand the extent to which search costs affect matching among scientific collaborators. We generated exogenous variation in search costs for pairs of potential collaborators by randomly assigning individuals to 90-minute structured information-sharing sessions as part of a grant funding opportunity. We estimate that the treatment increases the probability of grant co-application of a given pair of researchers by 75%. The findings suggest that matching between scientists is subject to considerable frictions, even in the case of geographically-proximate scientists working in the same institutional context.