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The following is an estimated demand function:

Q = 875 + 6XA + 15Y − 5P (125) (2) (−1.2)

Where Q is quantity sold, XA is advertising expenditure (in thousands of dollars), Y is income (in thousands of dollars), and P is the good's price. The standard errors for each estimate are in parentheses. The equation has been estimated from 10 years of quarterly data. The R2 was 0.92; the F-statistic was 57; the Standard Error of the Estimate (SEE) is 25. Suppose the values of the explanatory variables next period are: Advertising = $100,000; Income = $10,000; and Price = $100.

Required:
Using the above fitted regression, what is the predicted value of sales?

Sagot :

Answer:

The predicted value of sales is $75,037,500.

Explanation:

Given:

Q = 875 + 6XA + 15Y - 5P ……………………..(1)

Where:

Q = quantity sold = ?

XA = Advertising = $100,000

Y = Income = $10,000

P = Price = $100

Substituting the values into equation (1), we have:

Q = 875 + (6 * 100,000) + (15 * 10,000) - (5 * 100)

Q = 750,375

Therefore, we have:

Predicted value of sales = Q * P = 750,375 * $100 = $75,037,500

Therefore, the predicted value of sales is $75,037,500.

From the fitted regression, the predicted value of sales will be 1125.

The estimated demand function is given as:

Q = 875 + 6XA + 15Y − 5P

The explanatory variables will be:

Advertising = $100,000 = 100

Income = $10,000 = 10

Price = $100

The values will be put in the estimated equation and this will be:

Q = 875 + 6XA + 15Y − 5P

Q = 875 + (6 × 100) + (15 × 10) - (5 × 100)

Q = 875 + 600 + 150 - 500

Q = 1125

Learn more about demand on:

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