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A vector stochastic process zt is said to be wide-sense stationary if the vector of means Ez, is a constant vector independent of time t and if the matrix covariogram Eztz's depends on only the difference (t~s) and not only t and 5 separately. Wide-sense stationarity is also referred to as second-order stationarity and covariance stationarity.
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Thomas J. Sargent (1979) studied this question.
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