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RSM2129H – Forecasting Models and Econometric Methods

General Information


Applicable Major(s):
(c) = Core, (r) = Recommended

  • Management Analytics (c)
  • Real Estate (r)


This course is intended for students interested in understanding and using regression-based forecasting techniques applicable to Finance, Marketing, Strategy and Business Economics. 


12 weekly sessions

Course Mission

The course provides an introduction to forecasting techniques based on time-series methods (ARIMA) and single-equation econometric (‘regression’) equations.  We will also touch more briefly on multiple-equation econometric models and volatility forecasting (‘ARCH’ techniques).  The forecasting applications considered span demand and price forecasting and financial variables.  The course is “hands-on”, requiring use of the toolkit of techniques in Econometric Views (EVIEWS) – an econometrics package widely used in the forecasting community.  Relatively little time is devoted to non-econometric forecasting techniques.

Evaluation and Grade Distribution

ComponentDue DateWeight
Midterm Test #1Week 6 (in class)30%
Midterm Test #2Week 11 (in class)30%
Term PaperEnd of term40%

Required Resources

  • RequiredEViews – Student Version 9.0 or 10.0, Quantitative Micro Software. Downloadable; the minimal student version is a free download.
  • Recommended:  R.S. Pindyck and D.L. Rubinfeld (PR), Econometric Models & Economic Forecasts (virtually any edition). New York: McGraw Hill (This or any equivalent econometrics text is recommended; PR and several other econometric/forecasting texts will be placed on reserve in the Rotman library)

Last Updated: 2021-05-31 @ 2:29 pm