Long-run priors for term structure models

Working papers set out research in progress by our staff, with the aim of encouraging comments and debate.
Published on 18 December 2015

Working Paper No. 575
By Andrew Meldrum and Matt Roberts-Sklar 

Dynamic no-arbitrage term structure models are popular tools for decomposing bond yields into expectations of future short-term interest rates and term premia. But there is insufficient information in the time series of observed yields to estimate the unconditional mean of yields in maximally flexible models. This can result in implausibly low estimates of long-term expected future short-term interest rates, as well as considerable uncertainty around those estimates. This paper proposes a tractable Bayesian approach for incorporating prior information about the unconditional means of yields. We apply it to UK data and find that with reasonable priors it results in more plausible estimates of the long-run average of yields, lower estimates of term premia in long-term bonds and substantially reduced uncertainty around these decompositions in both affine and shadow rate term structure models.

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