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