Time Series Models for Business and Economic Forecasting [Hardcover]

Taking a practical approach, this updated and classroom-tested textbook prepares students to create effective forecasting models for business and economics.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.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.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. Downloadable datasets are available online.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-linearlÃ9