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A New Linear Estimator for Gaussian Dynamic Term Structure Models

Listed author(s):
  • Antonio Diez de los Rios

This paper proposes a novel regression-based approach to the estimation of Gaussian dynamic term structure models that avoids numerical optimization. This new estimator is an asymptotic least squares estimator defined by the no-arbitrage conditions upon which these models are built. We discuss some efficiency considerations of this estimator, and show that it is asymptotically equivalent to maximum likelihood estimation. Further, we note that our estimator remains easy-to-compute and asymptotically efficient in a variety of situations in which other recently proposed approaches lose their tractability. We provide an empirical application in the context of the Canadian bond market.

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File URL: http://www.bankofcanada.ca/wp-content/uploads/2013/04/wp2013-10.pdf
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Paper provided by Bank of Canada in its series Staff Working Papers with number 13-10.

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Length: 63 pages
Date of creation: 2013
Handle: RePEc:bca:bocawp:13-10
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Web page: http://www.bank-banque-canada.ca/

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  17. Antonio Diez de los Rios & Enrique Sentana, 2011. "Testing Uncovered Interest Parity: A Continuous‐Time Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 1215-1251, November.
  18. Kodde, D A & Palm, Franz C & Pfann, G A, 1990. "Asymptotic Least-Squares Estimation Efficiency Considerations and Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(3), pages 229-243, July-Sept.
  19. Leandro M. Magnusson & Sophocles Mavroeidis, 2010. "Identification-Robust Minimum Distance Estimation of the New Keynesian Phillips Curve," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(2-3), pages 465-481, 03.
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