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Canonical Correlation in Multivariate Time Series Analysis with an Application to One-Year-Ahead and Multiyear-Ahead Macroeconomic Forecasting

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  • Otter, Pieter W

Abstract

A simple one-period-ahead and multiperiod-ahead prediction procedure for multivariate time series is suggested, based on the canonical correlation technique. The prediction procedure is direct in the sense that no lag orders and parameters have to be estimated first, as in the usual ARMAX or VAR parameterizations of multivariate stationary stochastic processes. A best (in the mean squared error sense) predictor can be obtained directly using singular-value decompositions of covariance matrices. The procedure is used to forecast one-year-ahead and multiyear-ahead national growth rates of 14 countries for the years 1974-84.

Suggested Citation

  • Otter, Pieter W, 1990. "Canonical Correlation in Multivariate Time Series Analysis with an Application to One-Year-Ahead and Multiyear-Ahead Macroeconomic Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(4), pages 453-457, October.
    • Handle: RePEc:bes:jnlbes:v:8:y:1990:i:4:p:453-57
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    Cited by:

    1. Al-Sadoon, Majid M., 2014. "Geometric and long run aspects of Granger causality," Journal of Econometrics, Elsevier, vol. 178(P3), pages 558-568.
    2. Otter, Pieter W. & Jacobs, Jan P.A.M., 2006. "On information in static and dynamic factor models," CCSO Working Papers 200605, University of Groningen, CCSO Centre for Economic Research.
    3. Al-Sadoon, M.M., 2009. "Causality Along Subspaces: Theory," Cambridge Working Papers in Economics 0919, Faculty of Economics, University of Cambridge.
    4. Otter, Pieter W., 1995. "On model reduction and multiperiod ahead prediction in vector autoregressive models," Economic Modelling, Elsevier, vol. 12(4), pages 339-341, October.
    5. Wai-Sum Chan, 1999. "Exact joint forecast regions for vector autoregressive models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(1), pages 35-44.

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