Co-Integration, Error Correction, and the Econometric Analysis of Non-Stationary Data
By: Banerjee, Anindya | Dolado, Juan J | Galbraith, John W | Hendry, David F.
Material type: BookPublisher: Oxford et al. , Oxford University Press, 1993Description: 329 pages.ISBN: 0-19-828810-7.Subject(s): econometric model | econometrics | time series | equilibrium concepts | co‐integrationOnline resources: Publisher's website Summary: This book considers the econometric analysis of both stationary and non‐stationary processes, which may be linked by equilibrium relationships. It provides a wide‐ranging account of the main tools, techniques, models, concepts, and distributions involved in the modelling of integrated processes (i.e. those that accumulate the effects of past shocks). Since the focus is on equilibrium concepts, including co‐integration and error‐correction, the analysis begins with a discussion of the application of these concepts to stationary empirical models. Later chapters show how integrated processes can be reduced to this case by suitable transformations that take advantage of co‐integrating (equilibrium) relationships. The concepts of co‐integration and error‐correction models are shown to be fundamental in this modelling strategy. Practical modelling advice and empirical illustrations are provided.Item type | Current location | Call number | Status | Date due | Barcode |
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Monography | Library | C2 65 (Browse shelf) | Available | 41027 |
This book considers the econometric analysis of both stationary and non‐stationary processes, which may be linked by equilibrium relationships. It provides a wide‐ranging account of the main tools, techniques, models, concepts, and distributions involved in the modelling of integrated processes (i.e. those that accumulate the effects of past shocks). Since the focus is on equilibrium concepts, including co‐integration and error‐correction, the analysis begins with a discussion of the application of these concepts to stationary empirical models. Later chapters show how integrated processes can be reduced to this case by suitable transformations that take advantage of co‐integrating (equilibrium) relationships. The concepts of co‐integration and error‐correction models are shown to be fundamental in this modelling strategy. Practical modelling advice and empirical illustrations are provided.
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