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Non‐Parametric Regression Models of Deviations from Othogonality in the Expectations Theory of the Term Structure
Author(s) -
Campbell Bryan,
Galbraith John W.
Publication year - 1997
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/1468-0084.00064
Subject(s) - econometrics , term (time) , mathematics , regression , parametric statistics , orthogonality , economics , contrast (vision) , statistics , regression analysis , liquidity premium , risk premium , market liquidity , liquidity risk , computer science , physics , geometry , finance , quantum mechanics , artificial intelligence
Regression tests of the expectations theory of the term structure typically reject the null hypothesis of orthogonality between implied forecast errors and the yield spreads. In the statistical literature on the term structure, these rejections are sometimes attributed to time‐varying liquidity premia, and Engle et al . (1987) suggest that the ARCH‐M model of time‐variation in the liquidity premium may be sufficient to account for rejections of the expectations theory. We use non‐parametric (kernel) regression to explore the regression test results on a number of data sets, and find some evidence of a persistent deviation from orthogonality for large absolute values of the spread. Incorporating ARCH‐in‐mean into models of the term premium indicates that this specification does explain significant time variation in liquidity premia, but the effect does not apepar to be sufficient to account for all of the deviations from orthogonality of forecast errors and spreads.