6. You are the manager of a firm that receives revenues of $40,000 per year from product X and $90,000 per year from product Y. The own price elasticity of demand for product X is 1.5, and the cross-price elasticity of demand between product Y and X is 1.8. How much will your firm's total revenues (revenues from both products) change if you increase the price of good X by 2 percent? 7. A quant jock from your firm used a linear demand specification to estimate the demand for its product and sent you a hard copy of the results. Unfortunately, some entries are missing because the toner was low in her printer. Use the information presented below to find the missing values labeled '1' through '7' (round your answer to the nearest hundredth). Then, answer the accompanying questions. a. Based on these estimates, write an equation that summarizes the demand for the firm's product. b. Which regression coefficients are statistically significant at the 5 percent level? c. Comment on how well the regression line fits the data.

SUMMARY OUTPUT Regression Statistics Multiple R 0.38 R-Square '1' Adjusted R-Square '2' Standard Error 20.77 Observations 150 Analysis of Variance

Degrees of Freedom Sum of Squares Mean Square F Significance F Regression 2 '3' 5199.43 12.05 0.00 Residual 147 63,408.62 431.35 Total '4' 73,807.49

Coefficients Standard Error t-Statistic P-Value Lower 95% Upper 95% Intercept 58.87 '5' 3.84 0.00 28.59 89.15 Price of X 1.64 0.85 '6' 0.06 3.31 0.04 Income '7' 0.24 4.64 0.00 0.63 1.56

8. Suppose the true inverse demand relation for good X is Qdx = a + bPx + cM + e,

and you estimated the parameters to be = 22, b = -1.8, s = 2.5, and sb = 0.7.

Find the approximate 95 percent confidence interval for the true values of a and b.

9. The demand function for good X is Qdx = a + bPx + cM + e, where Px is the price of good X and M is income. Least squares regression reveals that = 8.27, b = - 2.14, c = 0.36, sa = 5.32, sb = 0.41, and sc = 0.22. The

R-squared is 0.35. a. Compute the t-statistic for each of the estimated coefficients.

b. Determine which (if any) of the estimated coefficients are statistically different from zero.

c. Explain, in plain words, what the R-square in this regression indicates. 10. The demand function for good X is ln Qdx = a + b ln Px + c ln M + e, where Px is the price of good X and M is income. Least squares regression reveals that = 7.42, b = - 2.18, and c = 0.34. a. If M = 55,000 and Px = 4.39, compute the own price elasticity of demand based on these estimates. Determine whether demand is elastic or inelastic. b. If M = 55,000 and Px = 4.39, compute the income elasticity of demand based on these estimates. Determine whether X is a normal or inferior good.