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These are econometrician Clive W. J. Granger's major essays in spectral analysis, seasonality, nonlinearity, methodology, and forecasting.
This is a volume of readings for graduate students, especially those taking courses in applied econometrics, who need to learn how to evaluate the validity of present theories and techniques. The aim of the text is to aid readers in the difficult task of actually constructing models. The essays vary in the degree of technical sophistication used, but each paper intends to provide students with a sound knowledge of the practical difficulties of model specification, evaluation and interpretation, as well as advice on tackling these difficulties.
Forecasting in Business and Economics presents a variety of forecasting techniques and problems. This book discusses the importance of the selection of a relevant information set. Organized into 12 chapters, this book begins with an overview of the forecasting techniques that are useful in decision making. This text then discusses the difficulties in interpreting an apparent trend and discusses its implications. Other chapters consider how a time series is analyzed and forecast by discussing the methods by which a series can be generated. This book discusses as well the views of most academic time series analysts regarding the usefulness of searches for cycles in most economic and business series. The final chapter deals with the techniques developed for forecasting. This book is a valuable resource for senior undergraduates in business, economics, commerce, and management. Graduate students in operations research and production engineering will also find this book extremely useful.
Economic Theory, Econometrics, and Mathematical Economics, Second Edition: Forecasting Economic Time Series presents the developments in time series analysis and forecasting theory and practice. This book discusses the application of time series procedures in mainstream economic theory and econometric model building. Organized into 10 chapters, this edition begins with an overview of the problem of dealing with time series possessing a deterministic seasonal component. This text then provides a description of time series in terms of models known as the time-domain approach. Other chapters consider an alternative approach, known as spectral or frequency-domain analysis, that often provides useful insights into the properties of a series. This book discusses as well a unified approach to the fitting of linear models to a given time series. The final chapter deals with the main advantage of having a Gaussian series wherein the optimal single series, least-squares forecast will be a linear forecast. This book is a valuable resource for economists.
Lucid account of the process of constructing and evaluating an empirical model.
Section headings in this handbook include: 'Forecasting Methodology; 'Forecasting Models'; 'Forecasting with Different Data Structures'; and 'Applications of Forecasting Methods.'.
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