A Simple MLE of Cointegrating Vectors in Higher Order Integrated Systems /
Stock, James H.
A Simple MLE of Cointegrating Vectors in Higher Order Integrated Systems / James H. Stock, Mark W. Watson. - Cambridge, Mass. National Bureau of Economic Research 1989. - 1 online resource: illustrations (black and white); - NBER technical working paper series no. t0083 . - Technical Working Paper Series (National Bureau of Economic Research) no. t0083. .
December 1989.
An MLE of the unknown parameters of co integrating vectors is presented for systems in which some variables exhibit higher orders of integration, in which there might be deterministic components, and in which the co integrating vector itself might involve variables of differing orders of integration. The estimator is simple to compute: it can be calculated by running GLS for standard regression equations with serially correlated errors. Alternatively, an asymptotically equivalent estimator can be computed using OLS. Usual Wald test statistics based on these MLE's (constructed using an autocorrelation robust covariance matrix in the case of the OLS estimator) have asymptotic x2 distributions.
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Mode of access: World Wide Web.
A Simple MLE of Cointegrating Vectors in Higher Order Integrated Systems / James H. Stock, Mark W. Watson. - Cambridge, Mass. National Bureau of Economic Research 1989. - 1 online resource: illustrations (black and white); - NBER technical working paper series no. t0083 . - Technical Working Paper Series (National Bureau of Economic Research) no. t0083. .
December 1989.
An MLE of the unknown parameters of co integrating vectors is presented for systems in which some variables exhibit higher orders of integration, in which there might be deterministic components, and in which the co integrating vector itself might involve variables of differing orders of integration. The estimator is simple to compute: it can be calculated by running GLS for standard regression equations with serially correlated errors. Alternatively, an asymptotically equivalent estimator can be computed using OLS. Usual Wald test statistics based on these MLE's (constructed using an autocorrelation robust covariance matrix in the case of the OLS estimator) have asymptotic x2 distributions.
System requirements: Adobe [Acrobat] Reader required for PDF files.
Mode of access: World Wide Web.