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Errors in Variables and Cointegration

Published online by Cambridge University Press:  11 February 2009

Victor Solo
Victor Solo
Affiliation:
Macquarie University
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Abstract

In this article it is shown how the cointegration or joint trending behavior of economic time series helps to alleviate the errors in variables problem.

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Type
Articles
Information
Econometric Theory , Volume 11 , Issue 1 , February 1995 , pp. 60 - 80
Copyright
Copyright © Cambridge University Press 1995

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References

REFERENCES

Anderson, B.D.O. (1985) Identification of scalar errors-in-variables models with dynamics. Automatica 21, 709–716.CrossRefGoogle Scholar
Anderson, B.D.O. & Deistler, M. (1984) Identifiability in dynamic errors in variables models. Journal of Time Series Analysis 5, 1–13.CrossRefGoogle Scholar
Beveridge, S. & Nelson, C.R. (1981) A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the “Business Cycle.” Journal of Monetary Economics 7, 151–174.CrossRefGoogle Scholar
Bode, H.W. (1945) Network Analysis and Feedback Amplifier Design. Van Nostrand.Google Scholar
Dahlhaus, R. (1989) Small sample effects in time series analysis: A new asymptotic theory and a new estimate. Annals of Statistics 16, 808–841.Google Scholar
Deistler, M. & Anderson, B.D.O. (1989) Linear dynamic errors-in-variables models. Journal of Econometrics 41, 39–63.CrossRefGoogle Scholar
Engle, R.F. (1987) On the Theory of Cointegrated Economic Time Series. Unpublished manuscript.Google Scholar
Engle, R.F. & Granger, C.W.J. (1987) Co-integration and error correction representation, estimation and testing. Econometrica 55, 251–276.CrossRefGoogle Scholar
Hinich, M.J. (1983) Estimating the gain of a linear filter from noisy data. In Brillinger, D. & Krishnaiah, P.R. (eds.), Handbook of Statistics, vol. 3. Amsterdam: North-Holland.Google Scholar
Louis, T.A. (1982) Finding the observed information matrix when using the EM algorithm. Journal of the Royal Statistical Society B 44, 222–233.Google Scholar
Newton, H.J. (1988) Timeslab: A Time Series Laboratory. Wadsworth.Google Scholar
Phillips, P.C.B. (1989) Spectral Regression for Cointegrated Time Series. Discussion paper, Cowles Foundation, Yale University.Google Scholar
Phillips, P.C.B. & Durlauf, S.N. (1986) Multiple time series regression with integrated processes. Review of Economic Studies 8, 473–495.Google Scholar
Stock, J.H. (1987) Asymptotic properties of least squares estimators of cointegrating vectors. Econometrica 55, 1035–1056.CrossRefGoogle Scholar