Recent macro-finance papers have documented the importance of adding information from macro variables in order to improve out-of-sample forecasting performance of bond yields. This paper aims at investigating the reasons for this success. We use Diebold and Li's dynamic version of the Nelson and Siegel exponential approximation of the yield curve to estimate the factors that govern its dynamics. Factors and macro variables are modeled simultaneously in a VAR framework, which is then used to forecast the factors. Our main conclusions are (i) this framework is useful in forecasting slope and curvature factors, but not the level factor; and (ii) to get good results in forecasting the level factor, one needs a macro model which incorporates variables related to long-run trends and expectations.

Objective: This study compared the mechanical behavior of nickel-titanium instruments with similar geometry, but manufactured by different methods.