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Long-run priors for term structure models

Author

Listed:
  • Meldrum, Andrew

    (Bank of England)

  • Roberts-Sklar, Matt

    (Bank of England)

Abstract
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.

Suggested Citation

  • Meldrum, Andrew & Roberts-Sklar, Matt, 2015. "Long-run priors for term structure models," Bank of England working papers 575, Bank of England.
  • Handle: RePEc:boe:boeewp:0575
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    References listed on IDEAS

    as
    1. Malik, Sheheryar & Meldrum, Andrew, 2016. "Evaluating the robustness of UK term structure decompositions using linear regression methods," Journal of Banking & Finance, Elsevier, vol. 67(C), pages 85-102.
    2. Michael D. Bauer, 2018. "Restrictions on Risk Prices in Dynamic Term Structure Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(2), pages 196-211, April.
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    12. Andreasen, Martin M & Meldrum, Andrew, 2015. "Market beliefs about the UK monetary policy life-off horizon: a no-arbitrage shadow rate term structure model approach," Bank of England working papers 541, Bank of England.
    13. Joyce, Michael & Kaminska, Iryna & Lildholdt, Peter, 2008. "Understanding the real rate conundrum: an application of no-arbitrage finance models to the UK real yield curve," Bank of England working papers 358, Bank of England.
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    15. Martin M. Andreasen & Andrew Meldrum, 2014. "Dynamic term structure models: The best way to enforce the zero lower bound," CREATES Research Papers 2014-47, Department of Economics and Business Economics, Aarhus University.
    16. Hamilton, James D. & Wu, Jing Cynthia, 2012. "Identification and estimation of Gaussian affine term structure models," Journal of Econometrics, Elsevier, vol. 168(2), pages 315-331.
    17. Marcet, Albert & Jarociński, Marek, 2010. "Autoregressions in small samples, priors about observables and initial conditions," Working Paper Series 1263, European Central Bank.
    18. Abrahams, Michael & Adrian, Tobias & Crump, Richard K. & Moench, Emanuel & Yu, Rui, 2016. "Decomposing real and nominal yield curves," Journal of Monetary Economics, Elsevier, vol. 84(C), pages 182-200.
    19. Mattias Villani, 2009. "Steady-state priors for vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 630-650.
    20. Andreasen, Martin & Meldrum, Andrew, 2013. "Likelihood inference in non-linear term structure models: the importance of the lower bound," Bank of England working papers 481, Bank of England.
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    Cited by:

    1. Lloyd, Simon P., 2020. "Estimating nominal interest rate expectations: Overnight indexed swaps and the term structure," Journal of Banking & Finance, Elsevier, vol. 119(C).

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    More about this item

    Keywords

    Affine term structure model; shadow rate term structure model; Gibbs sampler;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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