Time Series Models for Business and Economic Forecasting

Review of the first edition: 'Reviews the more recent developments in modeling time series to focus on generating ex ante forecasts: seasonal unit roots, period models, aberrant observations, and common features. For each method, intuitive motivation and practical considerations are discussed in detail, making the book very readable should be beneficial for students and instructors of applications-oriented courses as well as for practitioners who wish to obtain a first, but not too technical, impression of time series forecasting using modern, recently developed methods.' Journal of the American Statistical Association

Auteur

Philip Hans Franses is Professor of Applied Econometrics and Professor of Marketing Research at the Erasmus School of Economics.

Texte du rabat

Taking a practical approach, this updated and classroom-tested textbook prepares students to create effective forecasting models for business and economics.

Résumé
With a new author team contributing decades of practical experience, this fully updated second edition textbook summarises the most critical decisions, techniques and steps in creating effective forecasting models. Includes all new theoretical and practical exercises geared at guiding students through the steps of creating forecasting models on their own.

Contenu

Preface; 1. Introduction and overview; 2. Key features of economic time series; 3. Useful concepts in univariate time series analysis; 4. Trends; 5. Seasonality; 6. Aberrant observations; 7. Conditional heteroskedasticity; 8. Non-linearity; 9. Multivariate time series; Index.