Summary 175Discussion QuestionThere is an ongoing debate about the roles of quantitative
and qualitative inputs in demand estimation and forecasting. Those in the qual-
itative camp argue that statistical analysis can only go so far. Demand estimates
can be further improved by incorporating purely qualitative factors. Quantita-
tive advocates insist that qualitative, intuitive, holistic approaches only serve to
introduce errors, biases, and extraneous factors into the estimation task.
Suppose the executive for the theater chain is convinced that any number of
bits of qualitative information (the identity of the director, the film’s terrific script
and rock-music sound track, the Hollywood “buzz” about the film during produc-
tion, even the easing of his ulcer) influence the film’s ultimate box-office revenue.
How might one test which approach—purely qualitative or statistical—
provides better demand or revenue estimates? Are there ways to combine the
two approaches? Provide concrete suggestions.Spreadsheet Problems
S1. To help settle the scientific debate in Problem 7, an expert has provided
annual data on the water table and rainfall over the last decade.Year
12345678910
Water Table 17.6 19.2 14.8 18.1 13.2 15.1 20 14.6 13.9 13.5
Rainfall 36523444264856453942a. Using the 10 years of data, estimate the equation, W a bt, where
W is the water table and t is time in years. Comment on the statistical
validity of your equation. Can you conclude that the water table level
is dropping over time?
b. Did the region have greater yearly rainfall in the first five years or the
last five years of the decade? Should rainfall be added as an
explanatory variable in your regression equation? If it were, what
would be the effect on the estimate of b? Explain.
c. Now estimate the equation, W a bt cR, where R denotes
annual rainfall. Answer the questions posed in part (a) above. Is this
equation scientifically superior to the equation in part (a)?
S2. A soft-drink bottler collected the following monthly data on its sales of
12-ounce cans at different prices.Month
123456789101112
Price .45 .50 .45 .40 .35 .35 .50 .55 .45 .50 .40 .40
Quantity 98 80 95 123 163 168 82 68 96 77 130 125c04EstimatingandForecastingDemand.qxd 9/5/11 5:49 PM Page 175