Abstract
The regression theory of Chapter 6 and the VAR models discussed in the previous chapter are appropriate for modeling I(0) data, like asset returns or growth rates of macroeconomic time series. Economic theory often implies equilibrium relationships between the levels of time series variables that are best described as being I(1). Similarly, arbitrage arguments imply that the I(1) prices of certain financial time series are linked. This chapter introduces the statistical concept of cointegration that is required to make sense of regression models and VAR models with I(1) data.
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References
Alexander, C. (2001). Market Models: A Guide to Financial Data Analysis, John Wiley and Sons.
Cochrane, J. (2001). Asset Pricing. Princeton University Press, New Jersey.
Engle, R.F. and C.W.J. Granger (1987). āCo-Integration and Error Correction: Representation, Estimation and Testing,ā Econometrica, 55, 251ā276.
Granger, C.W.J. and P.E. Newbold (1974). āSpurious Regression in Econometrics,ā Journal of Econometrics, 2, 111ā120.
Hamilton, J.D. (1994). Time Series Analysis, Princeton Unversity Press, New Jersey.
Hansen, B.E. (1992). āEfficient Estimation and Testing of Cointe-grating Vectors in the Presence of Deterministic Trends,ā Journal of Econometrics, 53, 87ā121.
Hayashi, F. (2000). Econometrics, Princeton University Press, New Jersey.
Johansen, S. (1988). āStatistical Analysis of Cointegration Vectors,ā Journal of Economic Dynamics and Control, 12, 231ā254.
Johansen, S. (1995). Likelihood Based Inference in Cointegrated Vector Error Correction Models, Oxford University Press, Oxford.
MacKinnon, J. (1996). āNumerical Distribution Functions for Unit Root and Cointegration Tests,ā Journal of Applied Econometrics, 11, 601ā618.
Mills, T. (1999). The Econometric Analysis of Financial Time Series, Cambridge University Press, Cambridge.
Osterwald-Lenum, M. (1992). āA Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Statistics,ā Oxford Bulletin of Economics and Statistics, 54, 461ā472.
Phillips, P.C.B. (1986). āUnderstanding Spurious Regression in Econometrics,ā Journal of Econometrics, 33, 311ā340.
Phillips, P.C.B. (1991). āOptimal Inference in Cointegrated Systems,ā Econometrica, 59, 283ā306.
Phillips, P.C.B. and S. Ouliaris (1990). āAsymptotic Properties of Residual Based Tests for Cointegration,ā Econometrica, 58, 73ā93.
Reimars, H.-E. (1992). āComparisons of Tests for Multivariate Cointegration,ā Statistical Papers, 33, 335ā359.
Reinsel, G.C. and S.K. Ahn (1992). āVector Autoregression Models with Unit Roots and Reduced Rank Structure: Estimation, Likelihood Ratio Test, and Forecasting,ā Journal of Time Series Analysis, 13, 353ā375.
Sims, CA., J.H. Stock and M.W. Watson (1990). āInference in Linear Time Series Models with Some Unit Roots,ā Econometrica, 58, 113ā144.
Stock, J.H. (1987). āAsymptotic Properties of Least Squares Estimation of Cointegrating Vectors,ā Econometrica, 55, 1035ā1056.
Stock, J.H. and M.W. Watson (1989). āVariable Trends in Economic Time Series,ā Journal of Economic Perspectives, Vol. 2(3), 147ā174.
Stock, J.H. and M.W. Watson (1993). āA Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems,ā Econometrica, 61, 783ā820.
Tsay, R. (2001). The Analysis of Financial Time Series, John Wiley & Sons, New York.
Zivot, E. (2000). āCointegration and Forward and Spot Exchange Rate Regressions,ā Journal of International Money and Finance, 19, 785ā812.
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Zivot, E., Wang, J. (2003). Cointegration. In: Modeling Financial Time Series with S-PlusĀ®. Springer, New York, NY. https://doi.org/10.1007/978-0-387-21763-5_12
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DOI: https://doi.org/10.1007/978-0-387-21763-5_12
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