Forecasting, Structural Time Series Models and the Kalman Filter

by Andrew C. Harvey

Overview

This book provides a synthesis of concepts and materials that ordinarily appear separately in time series and econometrics literature, presenting a comprehensive review of both theoretical and applied concepts. Perhaps the most novel feature of the book is its use of Kalman filtering together with econometric and time series methodology. From a technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. This technique was originally developed in control engineering but is becoming increasingly important in economics and operations research. The book is primarily concerned with modeling economic and social time series and with addressing the special problems that the treatment of such series pose.

Product Details

ISBN-13:	9780521405737
Publisher:	Cambridge University Press
Publication date:	02/28/1991
Edition description:	Reprint
Pages:	572
Product dimensions:	5.98(w) x 9.02(h) x 1.26(d)

Table of Contents

List of figures; Acknowledgement; Preface; Notation and conventions; List of abbreviations; 1. Introduction; 2. Univariate time series models; 3. State space models and the Kalman filter; 4. Estimation, prediction and smoothing for univariate structural time series models; 5. Testing and model selection; 6. Extensions of the univariate model; 7. Explanatory variables; 8. Multivariate models; 9. Continuous time; Appendices; Selected answers to exercises; References; Author index; Subject index.

Editorial Reviews

"A well-written book by an author who has made numerous important contributions to the literature of forecasting, time series, and Kalman filters. It is a practical book in the sense that it not only discusses the definitions, interpretations, and analyses of structural time series models, but also illustrates the techniques." Choice

"It is difficult to compare this well-written, practical book to other books on time series because it is unique and unconventional in its approach to the subject....It accomplishes the difficult task of making the subject accessible to students and practitioners having relatively modest preparation in mathematics and statistics. I recommend it for acquisition by any undergraduate/graduate sciences or mathematics library, and it would be an excellent choice for a wide variety of classroom uses." John E. Angus, Technometrics

From the Publisher