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Readings in Unobserved Components Models
Contributor(s): Harvey, Andrew C. (Editor), Proietti, Tommaso (Editor)

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 ISBN: 0199278695     ISBN-13: 9780199278695
Publisher: OUP Oxford
OUR PRICE: $78.85  

Binding Type: Paperback - See All Available Formats & Editions
Published: June 2005
Qty:

Annotation: This volume presents a collection of readings which give the reader an idea of the nature and scope of unobserved components (UC) models and the methods used to deal with them. The book is intended to give a self-contained presentation of the methods and applicative issues. Harvey has made
major contributions to this field and provides substantial introductions throughout the book to form a unified view of the literature.

Click for more in this series: Advanced Texts in Econometrics (Paperback)
Additional Information
BISAC Categories:
- Business & Economics | Econometrics
Dewey: 330.015
LCCN: 2004027318
Series: Advanced Texts in Econometrics (Paperback)
Physical Information: 1.03" H x 6.12" W x 9.22" L (1.62 lbs) 474 pages
Features: Bibliography, Illustrated, Index, Table of Contents
 
Descriptions, Reviews, Etc.
Publisher Description:
This volume presents a collection of readings which give the reader an idea of the nature and scope of unobserved components (UC) models and the methods used to deal with them. The book is intended to give a self-contained presentation of the methods and applicative issues. Harvey has made
major contributions to this field and provides substantial introductions throughout the book to form a unified view of the literature.

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.
 
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