PART I: Forecasting with the Linear Regression Model
Chapter 1 The Baseline Linear Regression Model
Chapter 2 Model Mis-Specification
Chapter 3 The Dynamic Linear Regression Model
Chapter 4 Forecast Evaluation and Combination

PART II: Forecasting with Time Series Models
Chapter 5 Univariate Time Series Models
Chapter 6 VAR Models
Chapter 7 Error Correction Models
Chapter 8 Bayesian VAR Models

PART III: TAR, Markov Switching and State Space Models
Chapter 9 TAR and STAR Models
Chapter 10 Markov Switching Models
Chapter 11 State Space Models and the Kalman Filter

PART IV: Mixed Frequency, Large Datasets and Volatility
Chapter 12 Models for Mixed Frequency Data
Chapter 13 Models for Large Datasets
Chapter 14 Forecasting Volatility