Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

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Bibliographic Details

Title: Likelihood-Based Inference in Cointegrated Vector Autoregressive Models
Publisher: Oxford University Press, Incorporated
Publication Date: 1996
Language: English
ISBN 10: 0198774508
ISBN 13: 9780198774501
Binding: Soft cover
Condition: Very Good
Weight: 0.937 pounds

About this title

Synopsis

In this book, Professor Johansen, a leading statistician working in econometrics, gives a detailed mathematical and statistical analysis of the cointegrated vector autoregressive model, which has been gaining in popularity. The book is a self-contained presentation for graduate students and researchers with a good knowledge of multivariate regression analysis and likelihood methods. The theory is treated in detail to give the reader a working knowledge of the techniques involved, and many exercises are provided. The theoretical analysis is illustrated with the empirical analysis of two sets of economic data. The theory has been developed in close contact with the application and the methods have been implemented in the computer package CATS in RATS.

About the Series
Advanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.

About the Author

Soren Johansen is at the Institute of Mathematical Statistics, University of Copenhagen.

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