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Cointegration and Transformed Series

A large and growing literature is concerned with the theory, estimation, and applications of cointegrating vectors and associated error correction models. A cointegrated system is a set of time series that individually follow difference-stationary linear processes, but one or more linear combinations of the series do not require differencing to appear stationary. The stationary linear combinations indicate stable long-run relationships. Engle and Granger (1987) demonstrate the correspondence between cointegrated time series and error correction models: generating processes for cointegrated systems have error correction representations, and error correction models generate cointegrated series.

Suggested citation: Hallman, Jeffrey, 1990. “Cointegration and Transformed Series,” Federal Reserve Bank of Cleveland, Working Paper no. 90-14.

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