Week 10: Multiple regression and forecasting

What you will learn this week

  • Useful predictors for time series forecasting using regression
  • Selecting predictors
  • Ex ante and ex post forecasting

Pre-class activities

Read Chapter 7 of the textbook and watch all embedded videos

Slides for seminar

Download pdf

Workshop activities

Seminar Code

Tutorial exercises

NoteTutorial Learning Objectives
  1. Fit and forecast with TSLM().
    • Able to build linear time series regression models for forecasting.
    • Understand how to use regression models for forecasting, including selecting predictors and evaluating forecasts.
  2. Evaluate regression forecasts.
    • Able to use residual diagnostics and information criteria to compare models.
    • Able to interpret relationships on transformed scales where used.
    • Able to write out the regression equation for a fitted model, including interpreting coefficients and using the equation to compute forecasts.

Assignments

  • IA4 is due on Friday 15 May.
  • GA4 is due on Tuesday 26 May.

Weekly quiz