A Simple MLE of Cointegrating Vectors in Higher Order Integrated Systems / James H. Stock, Mark W. Watson.

By:

Stock, James H

Contributor(s):

Material type: Text

TextSeries: Technical Working Paper Series (National Bureau of Economic Research) ; no. t0083.Publication details: Cambridge, Mass. National Bureau of Economic Research 1989.Description: 1 online resource: illustrations (black and white)Subject(s):

C - Mathematical and Quantitative Methods

Online resources:

Available additional physical forms:

Hardcopy version available to institutional subscribers

Abstract: 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.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber t0083 (Browse shelf(Opens below))	Not For Loan

Total holds: 0

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.