Abstract
Viewing a yield curve as a sparse collection of measurements on a latent continuous random function allows us to model it statistically as a sparsely observed functional time series. Doing so, we use the state-of-the-art methods in non-parametric statistical inference for sparsely observed functional time series to analyse the lagged regression dependence of the US Treasury yield curve on US macroeconomic variables. Our non-parametric analysis confirms previous findings established under parametric assumptions, namely a strong impact of the federal funds rate on the short end of the yield curve and a moderate effect of the annual inflation on the longer end of the yield curve.
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