ABSTRACT

The predictive content of dynamic factor models in term structure modeling is evaluated and validated. Under a purely statistical data-driven approach, different sets of variables, estimation and forecasting methods are compared. In this way, central assumptions of standard term structure factor models are tested. We find that the inclusion of macroeconomic variables is useful to improve forecasts. Furthermore, a combination of static representation for factor estimation and autoregressive factor forecasts produces superior forecasts. These results confirm the statistical assumptions of term structure models made in prior research.