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. Key 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 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 * 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