Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper suggests a new approach for estimating linear and non-linear dynamic term structure models with latent factors. We impose no distributional assumptions on the factors which therefore may be non-Gaussian. The novelty of our approach is to use many observables (yields or bond prices) in the cross-section dimension. This implies that the latent factors can be determined quite accurately by a sequence of cross-section regressions. We also show how output from these regressions can be used to obtain model parameters by a two- or three-step moment-based estimation procedure.