Question

The results of the demand forecast of Pizza is presented to you for analysis. As a new manager of the company, you are required to provide an explanation for this forecast given your knowledge of managerial economics so that the company would know what to concentrate on.

          Y= 1.1 - 2.0P + 0.5S + 0.8X + 1.5T

                        (3.2)    (9.3)    (1.2)     (2.6)

R² is 0.78;      Probability value (F-statistic) is 0.02; t-statistics are the values in the bracket above

Whereby

Y is the Quantity demand for coffee

P is the price of Pizza (in dollar)

S is the demand for Soft drink (in number of quantity)

X is the income of people in the market surveyed (in 1,000 dollar).

T is the taste of the consumers for Pizza in that area

Answer 1

From the model, we can effectively see that following -

1. The quantity of pizza demanded is inversely proportional to the price of pizza, which means an increase in the price of pizza will lead to an decrease in the demand for pizza. The coefficient is 2, which means for a unit increase in the price, the quantity demanded will reduce by 2 units. This shows that pizza is very elastic in its demand.
2. The quantity of pizza demanded is directly proportional to the quantity demand of soft drinks. This shows that soft drinks and pizza are complementary to each other., and that people purchase soft drinks with their pizza. The coefficient is 0.5, which means for a unit increase in the quantity of soft drinks demanded, the quantity of pizza demanded will increase by half unit.
3. The demand for coffee is also directly linked to the income of the people which means that if the income increases, the demand for coffee also increases, and that makes coffee a normal good. The coefficient is 0.8, which means for a unit increase in the income, the quantity of pizza demanded will increase by 0.8 unit.
4. The demand for coffee also increases according to the tastes and preferences of the people around, which tells us that the more people like coffee, the more will they demand coffee in the region. The coefficient is 1.5, which means for a unit increase in the preference for pizza in the region, the quantity of pizza demanded will increase by one and half units.

The overall fit of the model is resonably good since the R2 value is 0.78, which means 78% of the variation in the demand for pizza can be explained by the independent variables model.