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Analysis of Economic Time Series (Revised Edition)

Marc Nerlove, University of Maryland, College Park, David M. Grether, California Institute of Technology, Pasadena and Jose L. Carvalho, Universidad Santa Ursala, Rio de Janeiro, Brazil

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 will be a useful primary text for graduate students and an attractive reference for researchers.

Features

• Presents a self-contained treatment of Fourier Analysis and complex variables, as well as Spectral Analysis of time series
• Includes a detailed treatment of unobserved-components (UC) models and their time-series properties by means of covariance-generating transforms
• Provides the formulation and maximum-likelihood estimation of ARMA and UC models in both time and frequency domains
• Integrates several topics in time-series analysis:

• The formulation and estimation of distributed-lag models of dynamic economic behaviour

• The application of the techniques of spectral analysis in the study of behaviour 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
• Historical contributions extending from the time of Charles Babbage and the Edinburgh Review to the present
• Treats spectral analysis and Box-Jenkins models for an intuitive but rigorous point of view

• Shows how these two types of analysis may be synthesized so that they complement one another.
• 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.
• Applies multiple time-series techniques to the estimation of a novel dynamic model of the US cattle industry.
  
  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. Formulation and Estimation of Multivariate Mixed Moving-Average Autoregressive Time-Series Models. Formulation and Estimation of Unobserved-Components Models. Application to the Formulation of Distributed-Lag Models. A Time-Series Model of the U.S. Cattle Industry. Appendices.

489 pages