Correcting Estimation Bias in Dynamic Term Structure Models |
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Authors: | Michael D Bauer Glenn D Rudebusch Jing Cynthia Wu |
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Institution: | 1. Federal Reserve Bank of San Francisco , San Francisco , CA , 94105;2. Booth School of Business , University of Chicago , Chicago , IL , 60637 |
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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, for both maximally flexible and overidentified specifications. Our estimates imply interest rate expectations and term premia that are more plausible from a macrofinance perspective. This article has supplementary material online. |
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Keywords: | Small-sample bias correction Term premium Vector autoregression |
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