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Estimating the Term Structure with Linear Regressions: Getting to the Roots of the Problem

Term Structure Persistence

Adam Golinski and Peter Spencer

Journal of Financial Econometrics, 2021, vol. 19, issue 5, 960-984

Abstract: Linear estimators of the affine term structure model are inconsistent since they cannot reproduce the factors used in estimation. This is a serious handicap empirically, giving a worse fit than the conventional ML estimator that ensures consistency. We show that a simple self-consistent estimator can be constructed using the eigenvalue decomposition of a regression estimator. The remaining parameters of the model follow analytically. Estimates from this model are virtually indistinguishable from that of the ML estimator. We apply the method to estimate various models of U.S. Treasury yields. These exercises greatly extend the range of models that can be estimated.

Keywords: estimation methods; linear regression estimators; self-consistent model; term structure; VAR(p) dynamics (search for similar items in EconPapers)
JEL-codes: C13 G12 (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)

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Working Paper: Estimating the term structure with linear regressions: Getting to the roots of the problem (2019) Downloads
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Journal of Financial Econometrics is currently edited by Allan Timmermann and Fabio Trojani

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