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The SR approach: A new estimation procedure for non-linear and non-Gaussian dynamic term structure models

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  • Andreasen, Martin M.
  • Christensen, Bent Jesper

Abstract

This paper suggests a new approach for estimating linear and non-linear dynamic term structure models with latent factors. We impose no distributional assumptions on the factors which therefore may be non-Gaussian. The novelty of our approach is to use many observables (yields or bond prices) in the cross-section dimension. This implies that the latent factors can be determined quite accurately by a sequence of cross-section regressions. We also show how output from these regressions can be used to obtain model parameters by a two- or three-step moment-based estimation procedure.

Suggested Citation

  • Andreasen, Martin M. & Christensen, Bent Jesper, 2015. "The SR approach: A new estimation procedure for non-linear and non-Gaussian dynamic term structure models," Journal of Econometrics, Elsevier, vol. 184(2), pages 420-451.
    • Handle: RePEc:eee:econom:v:184:y:2015:i:2:p:420-451
    DOI: 10.1016/j.jeconom.2014.10.002
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    Cited by:

    1. Salman Huseynov, 2021. "Long and short memory in dynamic term structure models," CREATES Research Papers 2021-15, Department of Economics and Business Economics, Aarhus University.
    2. Martin M. Andreasen & Jens H. E. Christensen & Glenn D. Rudebusch, 2017. "Term Structure Analysis with Big Data," Working Paper Series 2017-21, Federal Reserve Bank of San Francisco.
    3. 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.
    4. Bruno Feunou & Jean-Sébastien Fontaine & Anh Le & Christian Lundblad, 2022. "Tractable Term Structure Models," Management Science, INFORMS, vol. 68(11), pages 8411-8429, November.
    5. Martin M. Andreasen & Tom Engsted & Stig V. Møller & Magnus Sander, 2016. "Bond Market Asymmetries across Recessions and Expansions: New Evidence on Risk Premia," CREATES Research Papers 2016-26, Department of Economics and Business Economics, Aarhus University.
    6. Christensen, Bent Jesper & Kjær, Mads Markvart & Veliyev, Bezirgen, 2023. "The incremental information in the yield curve about future interest rate risk," Journal of Banking & Finance, Elsevier, vol. 155(C).
    7. 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.
    8. Andreasen, Martin M. & Christensen, Jens H.E. & Rudebusch, Glenn D., 2019. "Term Structure Analysis with Big Data: One-Step Estimation Using Bond Prices," Journal of Econometrics, Elsevier, vol. 212(1), pages 26-46.
    9. Martin Møller Andreasen & Kasper Jørgensen & Andrew Meldrum, 2019. "Bond Risk Premiums at the Zero Lower Bound," CREATES Research Papers 2019-10, Department of Economics and Business Economics, Aarhus University.
    10. Nyholm, Ken, 2016. "US-euro area term structure spillovers, implications for central banks," Working Paper Series 1980, European Central Bank.
    11. Andreasen, Martin M & Meldrum, Andrew, 2015. "Dynamic term structure models: the best way to enforce the zero lower bound in the United States," Bank of England working papers 550, Bank of England.
    12. Martin M. Andreasen & Andrew C. Meldrum, 2018. "A Shadow Rate or a Quadratic Policy Rule? The Best Way to Enforce the Zero Lower Bound in the United States," Finance and Economics Discussion Series 2018-056, Board of Governors of the Federal Reserve System (U.S.).
    13. Stefania D’Amico & N Aaron Pancost, 2022. "Special Repo Rates and the Cross-Section of Bond Prices: The Role of the Special Collateral Risk Premium [Pr icing the term structure with linear regressions]," Review of Finance, European Finance Association, vol. 26(1), pages 117-162.
    14. Martin M. Andreasen & Kasper Joergensen & Andrew C. Meldrum, 2019. "Bond Risk Premiums at the Zero Lower Bound," Finance and Economics Discussion Series 2019-040, Board of Governors of the Federal Reserve System (U.S.).
    15. Christensen, Bent Jesper & Posch, Olaf & van der Wel, Michel, 2016. "Estimating dynamic equilibrium models using mixed frequency macro and financial data," Journal of Econometrics, Elsevier, vol. 194(1), pages 116-137.

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    More about this item

    Keywords

    Bond data; GMM; Non-linear filtering; Non-linear least squares; SMM;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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