Journal of Financial and Quantitative Analysis

Research Articles

Term Structure Estimation with Survey Data on Interest Rate Forecasts

Don H. Kima1 and Athanasios Orphanidesa2

a1 School of Business, Yonsei University, 262 Seongsanno, Seodaemun-gu, Seoul 120-749, Korea, donhkim@yonsei.ac.kr

a2 Central Bank of Cyprus, 80 Kennedy Ave., Nicosia 1076, Cyprus. athanasios.orphanides@centralbank.gov.cy

Abstract

The estimation of dynamic no-arbitrage term structure models with a flexible specification of the market price of risk is beset by severe small-sample problems arising from the highly persistent nature of interest rates. We propose using survey forecasts of a short-term interest rate as an additional input to the estimation to overcome the problem. To illustrate the methodology, we estimate the 3-factor affine-Gaussian model with U.S. Treasury yields data and demonstrate that incorporating information from survey forecasts mitigates the small-sample problem. The model thus estimated for the 1990–2003 sample generates a stable and sensible estimate of the expected path of the short rate, reproduces the well-known stylized patterns in the expectations hypothesis tests, and captures some of the short-run variations in the survey forecast of the changes in longer-term interest rates.

(Online publication December 16 2011)

Footnotes

We thank Jim Clouse, Brian Sack, and Jonathan Wright for helpful input and encouragement, and Hendrik Bessembinder (the editor), Mikhail Chernov, Jefferson Duarte (associate editor and referee), Greg Duffee, Antti Ilmanen, Monika Piazzesi, Peter Tinsley, and participants of presentations at the Bank for International Settlements (BIS), Bank of England, University of Frankfurt, Universite Libre de Bruxelles, University of Basel, the 11th International Conference on Computing in Economics and Finance (Washington, DC, 2005), the Annual Conference of the German Economic Association (Bayreuth, 2006), and the 2007 American Finance Association (AFA) Chicago meetings, for useful comments.

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