Analysis of Economic Time Series : A Synthesis
In this edition which has been reprinted with corrections, Nerlove and his co-authors illustrate techniques of spectral analysis and methods based on parametric models in the analysis of economic time series. The book provides a means and a method for incorporating economic intuition and theory in the formulation of time-series models useful in forecasting, in the formulation and estimation of distributed lag models, and in other applications, such as seasonal adjustment. "Analysis of Economic Time Series" is a useful primary text for graduate students and an attractive reference for researchers. It presents a self-contained treatment of Fourier Analysis and complex variables, as well as Spectral Analysis of time series. It includes a detailed treatment of unobserved-components (UC) models and their time-series properties by means of covariance-generating transforms. It provides the formulation and maximum-likelihood estimation of ARMA and UC models in both time and frequency domains. It integrates several topics in time-series analysis: The formulation and estimation of distributed-lag models of dynamic economic behavior; The application of the techniques of spectral analysis in the study of behavior of economic time series; Unobserved-components models for economic time series and the closely related problem of seasonal adjustment; The complimentarities between time-domain and frequency-domain approaches to the analysis of economic time series; and historical contributions extending from the time of Charles Babbage and the Edinburgh Review to the present. It treats spectral analysis and Box-Jenkins models for an intuitive but rigorous point of view. It shows how these two types of analysis may be synthesized so that they complement one another. It describes a new type of model, based on a superposition of Box-Jenkins models, that captures the essential idea of the unobserved-components models long used in the analysis of economic time series. It applies multiple time-series techniques to the estimation of a novel dynamic model of the US cattle industry.
- Paperback | 468 pages
- 154.2 x 228.6 x 25.9mm | 781.31g
- 12 Sep 1995
- Emerald Publishing Limited
- Academic Press Inc
- Bingley, United Kingdom
- 2nd edition
Other books in this series
11 Oct 2000
"The authors clearly reveal their mastery of the area." --TECHNOMETRICS "Besides offering the convenience of a one-volume collection, the books format provides the authors with the opportunity to engage in discursive essays, which are often insightful and stimulating... The balance between theory and examples makes it an attractive book for use in a special topics course." --JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
Table of contents
A History of the Idea of Unobserved Components in the Analysis of Economic Time Series. Introduction to the Theory of Stationary Time Series. The Spectral Representation and Its Estimation. Formulation and Analysis of Unobserved-Components Models. Elements of the Theory of Prediction and Extraction. Formulation of Unobserved-Components Models and Canonical Forms. Estimation of Unobserved-Components and Canonical Models. Appraisal of Seasonal Adjustment Techniques. On the Comparative Structure of Serial Dependence in Some U.S. Price Series. Formulation and Estimation of Mixed Moving-Average Autoregressive Models for Single Time Series: Examples. Formulation and Estimation of Multivariate Mixed Moving-Average Autoregressive Time-Series Models. Formulation and Estimation of Unobserved-Components Models: Examples. Application to the Formulation of Distributed-Lag Models. A Time-Series Model of the U.S. Cattle Industry. Appendices: The Work of Buys Ballot. Some Requisite Theory of Functions of a Complex Variable. Fourier Series and Analysis. Whittle's Theorem. Inversion of Tridiagonal Matrices and a Method for Inverting Toeplitz Matrices. Spectral Densities, Actual and Theoretical, Eight Series. Derivation of a Distributed-Lag Relation between Sales and Production: A Simple Example. References. Author Index. Subject Index.