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The SR Approach: a new Estimation Method for Non-Linear and Non-Gaussian Dynamic Term Structure Models

Author

Listed:
  • Martin M. Andreasen

    (Bank of England and CREATES)

  • Bent Jesper Christensen

    (School of Economics and Management, Aarhus University, Denmark)

Abstract

This paper suggests a new and easy approach to estimate linear and non-linear dynamic term structure models with latent factors. We impose no distributional assumptions on the factors and they may therefore be non-Gaussian. The novelty of our approach is to use many observables (yields or bonds prices) in the cross-section dimension. An important benefit of using many observables in each time period is that the latent factors can be estimated quite accurately using standard regressions, and that parameters can be estimated by standard moment matching methods.

Suggested Citation

  • Martin M. Andreasen & Bent Jesper Christensen, "undated". "The SR Approach: a new Estimation Method for Non-Linear and Non-Gaussian Dynamic Term Structure Models," CREATES Research Papers 2010-12, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2010-12
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    File URL: https://repec.econ.au.dk/repec/creates/rp/10/rp10_12.pdf
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    Citations

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    Cited by:

    1. 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.
    2. 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.

    More about this item

    Keywords

    Bond data; GMM; Non-linear filtering; Non-linear least squares; Missing observations; 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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