In 2012, the board of regents responsible for all public higher- education funding in a major Canadian city hired a consultant to develop a series of enrollment forecasting models, one for each college. These models used historical data and exponential smoothing to forecast the following year’s enrollments. Based on the model, which included a smoothing constant (α) for each school, each college’s budget was set by the board. The head of the board personally selected each smoothing constant based on what she called her “gut reactions and political acumen.”
What do you think the advantages and disadvantages of this sys- tem are? Answer from the perspective of
(a) The board of regents and
(b) The president of each college.
How can this model be abused and what can be done to remove any biases? How can a regression model be used to produce results that favour one forecast over another?