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Salvatore Chapter 4: (See uploaded Excel sheet and complete)
a. Discussion Questions: 8 and 11.
b. Problems: 3(a) and (b), 7, 9, and 15.
Note:
1. DQ8: Calculate the percentage decrease in quantity due to 10% increase in price.
2. DQ11: Change ?between apples and cheese is 0.4? to ?between apples and cheese is negative 0.4.?
The relationship between two commodities could be substitutes, complements, or independent.
3. P3(a): Substitute the given value of independent variables into the equation in problem 2 and show the new equation as Qc= a ? 100Pc, a is a number. See equation (4-5) as the example (p. 130).
For N, enter 225 not 225,000,000
4. P3(b): Do not plot the demand curve, but find the value of Qc, if Pc is $10,000.
5. P7(a) is asking whether the transportation authority should increase or decrease the price per ride based upon the price elasticity of demand.
6. P7(b): Suggestion ? increase the price of a ride from $1 to be $1.50, a 50% increase in price. Given the price elasticity of demand of -0.4, calculate the percentage change in the ride and the total new rides (the original rides are 100 million = $100 million/$1) using equation (4-7). Then use the total new rides time the new price of $1.50 to obtain the new total revenue.
Froeb et al. Chapter 6:
a. Individual problems: 6-1, 6-3, and 6-5.
Note:
1. P6-1: Use price elasticity estimator on page 74. The desired markup is 1/?e?=1/the absolute value of the price elasticity. The initial actual markup is (P-MC)/P, P=$8.50.
2. P6-3: What would happen to the elasticity of demand in the long run (p. 75)?
3. P6-5: Use (P-MC)/P = 1/?e? to calculate MC, and then use the same equation to find out the new price.
?
Salvatore Chapter 5: (See uploaded Excel sheet and complete)
a. Problems: 8, 15(b) and (c), and appendix problem 2 (p. 218).
Note:
1. P8(b)?s answer is based upon the income elasticity (p. 141).
2. P15(b) is to evaluate the above regression results in terms of the signs of the coefficients, the statistical significance of the coefficients, and the explanatory power of the regression (R2). The number in parentheses below the estimated slope coefficients refer to the estimated t values. The rule of thumb for testing the significance of the coefficients is if the absolute t value is greater than 2, the coefficient is significant, which means the coefficient is significantly different from 0. For example, the absolute t value for Px is 5.12, which is greater than 2; therefore, the coefficient of Px, (-9.50) is significant. In order words, Px does affect Qx. If the price of the commodity X increases by $1, the quantity demanded (Qx) will decrease by 9.50 units.
3. P15(c): Are X and Z complements or substitutes?
4. For appendix problem 2, use the table under the problem on page 218, not Table 5-6, for the regression analysis. Enter the data in columns like table 5-11.
