Estimating the term structure with linear regressions: Getting to the roots of the problem

Research output: Contribution to journalArticlepeer-review

Published copy (DOI)



Publication details

JournalJournal of Financial Econometrics
DateAccepted/In press - 10 Sep 2019
DateE-pub ahead of print (current) - 3 Dec 2019
Number of pages25
Pages (from-to)1-25
Early online date3/12/19
Original languageEnglish


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.

Bibliographical note

The Author(s) 2019. Published by Oxford University Press. All rights reserved. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations