Correcting Estimation Bias in Dynamic Term Structure Models

32 Pages Posted: 6 Sep 2013

See all articles by Michael Bauer

Michael Bauer

Universit├Ąt Hamburg

Glenn D. Rudebusch

Federal Reserve Bank of San Francisco

Jing Cynthia Wu

University of Notre Dame - Department of Economics; National Bureau of Economic Research (NBER)

Date Written: May 4, 2012

Abstract

The affine dynamic term structure model (DTSM) is the canonical empirical finance representation of the yield curve. However, the possibility that DTSM estimates may be distorted by small-sample bias has been largely ignored. We show that conventional estimates of DTSM coefficients are indeed severely biased, and this bias results in misleading estimates of expected future short-term interest rates and of long-maturity term premia. We provide a variety of bias-corrected estimates of affine DTSMs, both for maximally flexible and over-identified specifications. Our estimates imply short rate expectations and term premia that are more plausible from a macro-finance perspective.

Keywords: small-sample bias correction, vector auto-regression, dynamic term structure models, term premium

JEL Classification: C53, E43, E47

Suggested Citation

Bauer, Michael and Rudebusch, Glenn D. and Wu, Jing Cynthia, Correcting Estimation Bias in Dynamic Term Structure Models (May 4, 2012). Journal of Business and Economic Statistics, Vol. 30, No.3, pp. 454-467, 2012, Available at SSRN: https://ssrn.com/abstract=2321273

Michael Bauer

Universit├Ąt Hamburg ( email )

Von-Melle-Park 5
Hamburg, 20146
Germany

HOME PAGE: http://www.michaeldbauer.com

Glenn D. Rudebusch

Federal Reserve Bank of San Francisco ( email )

101 Market Street
San Francisco, CA 94105
United States

Jing Cynthia Wu (Contact Author)

University of Notre Dame - Department of Economics ( email )

Notre Dame, IN 46556
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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