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Identification and estimation of Gaussian affine term structure models

  • Hamilton, James D.
  • Wu, Jing Cynthia

This paper develops new results for identification and estimation of Gaussian affine term structure models. We establish that three popular canonical representations are unidentified, and demonstrate how unidentified regions can complicate numerical optimization. A separate contribution of the paper is the proposal of minimum-chi-square estimation as an alternative to MLE. We show that, although it is asymptotically equivalent to MLE, it can be much easier to compute. In some cases, MCSE allows researchers to recognize with certainty whether a given estimate represents a global maximum of the likelihood function and makes feasible the computation of small-sample standard errors.

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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 168 (2012)
Issue (Month): 2 ()
Pages: 315-331

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Handle: RePEc:eee:econom:v:168:y:2012:i:2:p:315-331
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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