This book is student-friendly approach to understanding forecasting. Knowledge of forecasting methods is among the most demanded qualifications for professional economists, and business people working in either the private or public sectors of the economy. The general aim of Forecasting for Economics & Business is to carefully develop sophisticated professionals, who are able to critically analyze time series data and forecasting reports because they have experienced the merits and shortcomings of forecasting practice.
For junior/senior undergraduates in a variety of fields such as economics, business administration, applied mathematics and statistics, and for graduate students in quantitative masters programs such as MBA and MA/MS in economics.
Key Features
- Visualization. Pictures, graphs, and plots engage students’ in the material and are useful tools to motivate and develop forecasting intuition in anticipation of formal, more technical, concepts.
- Engagement with real-life data and simulated data. All chapters in the textbook are motivated by real-life data. The same data sets that professional forecasters examine are also provided. Examining these data sets provides an immediate immersion in the practice of forecasting. In all chapters, the introduction of a new concept, model, or procedure is immediately followed by a real data exercise.
- A modern hands-on approach. Short computer programs are provided in all chapters to simulate the models under study. These programs and all real-life data exercises bring a hands-on experience to the understanding of forecasting.
- Accessible to students who have a basic background in algebra, statistics, and linear regression. In a few instances, some introductory calculus is used to facilitate the exposition, but it is not absolutely necessary for the comprehension of the material. A brief review of fundamental statistical concepts is provided in the book appendix.
- Student-friendly organization. This text contains sixteen chapters grouped into three modules:
- Module I (Chapters 1 to 3) is introductory.
- Module II (Chapters 4 to 12) introduces the modeling methodology and the construction of optimal forecasts for univariate and multivariate stationary linear models.
- Module III (Chapters 13 to 16) introduces more complex dependence.
Contents
- Chapter 1: Introduction and Context
- Chapter 2: A Review of Basic Statistics Concepts and the Linear Regression Model
- Chapter 3: Statistics and Time Series
- Chapter 4: Tools of the Forecaster
- Chapter 5: Understanding Linear Dependence: A Link to Economic Models
- Chapter 6: Forecasting with Moving Average (MA) Processes
- Chapter 7: Forecasting with AutoRegressive (AR) Processes
- Chapter 8: Forecasting Practice: Modeling San Diego House Price Index
- Chapter 9: Assessment of Forecasts and Combination of Forecasts
- Chapter 10: Forecasting the Long Run: Deterministic and Stochastic Trends
- Chapter 11: Forecasting with a System of Equations: Vector AutoRegression
- Chapter 12: Forecasting the Long Run and the Short Run Jointly: Cointegration and Error Correction Models
- Chapter 13: Forecasting Volatility I
- Chapter 14: Forecasting Volatility II
- Chapter 15: Financial Applications of Time-varying Volatility
- Chapter 16: Forecasting with Nonlinear Models
Book Details
- Hardcover: 512 pages
- Publisher: Prentice Hall; 1 edition (©2013)
- Language: English
- ISBN-10: 0131474936
- ISBN-13: 978-0131474932
- Product Dimensions: 7.6 x 0.9 x 9.4 inches
- List price: 156.33