A food-products company has recently introduced a new line of fruit drinks in Lusaka and Copperbelt towns. Based on the drink’s apparent success, the company is considering a nationwide launch. Before doing so, it has decided to use data collected during a two-year market test to guide it in setting prices and forecasting future demand. The firm has collected data for a total of 48 observations through various stores. Each observation consists of data on quantity demanded (number of drinks purchased per week), price per drink, competitors’ average price per drink, income, and population. A company forecaster has run a regression on the data, obtaining the results displayed in the accompanying table.
A food-products company has recently introduced a new line of fruit drinks in Lusaka and Copperbelt towns. Based on the drink’s apparent success, the company is considering a nationwide launch. Before doing so, it has decided to use data collected during a two-year market test to guide it in setting prices and
|
Variable |
Coefficient |
Standard Error of Coefficient |
Mean Value of Variable |
|
|
Constant |
-4516.3 |
4988.2 |
- |
|
|
Own Price (Kwacha) |
-3590.6 |
702.8 |
7.50 |
|
|
Competitors’ Price (Kwacha) |
4226.5 |
851.0 |
6.50 |
|
|
Income (ZMW 000) |
777.1 |
66.4 |
40 |
|
|
Population |
0.40 |
0.31 |
2300 |
|
|
|
|
|
|
|
|
N=48 |
R2=0.93 |
Standard error of regression=1442 |
i. Interpret the value of the constant.
ii. How much of the total variation in drink sales does the regression model explain and interprete?
iii. Compute the
iv. Compute the cross-price elasticity of demand for drinks at the competitor’s mean price of K6.50 and mean weekly sales quantity of 20,000 drinks.
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