Unbiased estimate of dynamic term structure models
Michael Bauer,
Glenn Rudebusch and
Jing Cynthia Wu
No 2011-12, Working Paper Series from Federal Reserve Bank of San Francisco
Abstract:
Affine dynamic term structure models (DTSMs) are the standard finance representation of the yield curve. However, the literature on DTSMs has ignored the coefficient bias that plagues estimated autoregressive models of persistent time series. We introduce new simulation-based methods for reducing or even eliminating small-sample bias in empirical affine Gaussian DTSMs. With these methods, we show that conventional estimates of DTSM coefficients are severely biased, which results in misleading estimates of expected future short-term interest rates and long-maturity term premia. Our unbiased DTSM estimates imply risk-neutral rates and term premia that are more plausible from a macro-finance perspective.
Keywords: Interest; rates (search for similar items in EconPapers)
Date: 2011
New Economics Papers: this item is included in nep-cba and nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://www.frbsf.org/publications/economics/papers/2011/wp11-12bk.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:fip:fedfwp:2011-12
Ordering information: This working paper can be ordered from
Access Statistics for this paper
More papers in Working Paper Series from Federal Reserve Bank of San Francisco Contact information at EDIRC.
Bibliographic data for series maintained by Federal Reserve Bank of San Francisco Research Library ().