Time Series Models for Business and Economic Forecasting

With a new author team contributing decades of practical experience, this fully updated and thoroughly classroom-tested second edition textbook prepares students and practitioners to create effective forecasting models and master the techniques of time series analysis. Taking a practical and example-driven approach, this textbook summarises the most critical decisions, techniques and steps involved in creating forecasting models for business and economics. Students are led through the process with an entirely new set of carefully developed theoretical and practical exercises. Chapters examine the key features of economic time series, univariate time series analysis, trends, seasonality, aberrant observations, conditional heteroskedasticity and ARCH models, non-linearity and multivariate time series, making this a complete practical guide. A companion website with downloadable datasets, exercises and lecture slides rounds out the full learning package. 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 AssociationPreface; 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.