In: Statistics and Probability
Copy and paste the following data into Excel:
P |
Q |
$210.00 |
4280 |
$201.60 |
4335 |
$199.50 |
4513 |
$195.30 |
4655 |
$191.10 |
4696 |
$182.70 |
4949 |
$172.20 |
5142 |
$163.80 |
5313 |
a. Run OLS to determine the demand function as P = f(Q); how much confidence do you have in this estimated equation? Use algebra to invert the demand function to Q = f(P).
b. Using calculus to determine dQ/dP, construct a column which calculates the point-price elasticity for each (P,Q) combination.
c. What is the point price elasticity of demand when P=$210.00? What is the point price elasticity of demand when P=$185.50?
d. To maximize total revenue, what would you recommend if the company was currently charging P=$201.60? If it was charging P=$185.50?
e. Use your first demand function to determine an equation for TR and MR as a function of Q, and create a graph of P and MR on the vertical and Q on the horizontal axis.
f. What is the total-revenue maximizing price and quantity, and how much revenue is earned there? (Round your price to the nearest cent, your quantity to the nearest whole unit, and your TR to the nearest dollar.) Compare that to the TR when P = $210.00 and P = $185.50.
Answer:-
Given That:-
a. Run OLS to determine the demand function as P = f(Q); how much confidence do you have in this estimated equation? Use algebra to invert the demand function to Q = f(P).
Based on the data, the regression result from Microsoft Excel is as follows:
Regression Statistics | |
Multiple R | 0.989 |
R Square | 0.978 |
Adjusted R Square | 0.975 |
Standard Error | 2.485 |
Observations | 8 |
ANOVA
df | SS | MS | F | Significance F | |
Regression | 1 | 1671.820 | 1671.820 | 270.700 | 0.000 |
Residual | 6 | 37.055 | 6.176 | ||
Total | 7 | 1708.875 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
Intercept | 386.140 | 11.982 | 32.226 | 0.000 | 356.820 | 415.460 |
Q | -0.042 | 0.003 | -16.453 | 0.000 | -0.048 | -0.035 |
Hence, the estimated equation is P = 386.140 - 0.042 Q (up to 3 decimal places).
Since the coefficients are highly significant (low p-value), confidence is high on this estimated regression. Also, R-square is very high.
From the above inverse demand function, using algbra, we can derive the demand function as follows:
0.042 Q = 386.140 - P => Q = (386.140/0.042) - (P/0.042) =
9299.983 - 24.084 P
b. Using calculus to determine dQ/dP, construct a column which calculates the point-price elasticity for each (P,Q) combination.
Since Q = 9299.983 - 24.084 P, we get dQ/dP = -24.084. Using the formula for point price elasticity of demand [elasticity = (dQ/dP)(P/Q)], for each price and quantity combinations, elasticity has been calculated as follows.
A | B | C | |
1 | P | Q | Elasticity |
2 | 210 | 4280 | -1.182 |
3 | 201.6 | 4335 | -1.120 |
4 | 199.5 | 4513 | -1.065 |
5 | 195.3 | 4655 | -1.010 |
6 | 191.1 | 4696 | -0.980 |
7 | 182.7 | 4949 | -0.889 |
8 | 172.2 | 5142 | -0.807 |
9 | 163.8 | 5313 | -0.743 |
c. What is the point price elasticity of demand when P=$210.00? What is the point price elasticity of demand when P=$185.50?
At price $210, Q = 9299.983 - 24.084 (210) = 4242.246 and elasticity = -24.084 * 210 / 4242.246 = -1.192
At price $185.5, Q = 9299.983 - 24.084 (185.5) = 4832.315 and
elasticity = -24.084 * 185.5 / 4832.315 = -0.925
d. To maximize total revenue, what would you recommend if the company was currently charging P=$201.60? If it was charging P=$185.50?
At price $201.6, Q = 9299.983 - 24.084 (201.6) = 4444.555 and elasticity = -24.084 * 201.6 / 4444.555 = -1.092
Since the demand is elastic at price $201.6, revenue can be increased by decreasing the price since quantity will increase more proportionately as compared to fall in price.
However, at price $185.5, elasticity = -0.925, i.e., demand is
inelastic. Hence, to increase revenue, price needs to be increased
because the change in quantity (decrease) will be less
proportionate than the change (increase) in price in this
case.
e. Use your first demand function to determine an equation for TR and MR as a function of Q, and create a graph of P and MR on the vertical and Q on the horizontal axis
.
Since P = 386.140 - 0.042 Q,
TR = PQ = (P = 386.140 - 0.042 Q) Q = 386.140Q - 0.042 Q2
MR = d(TR)/dQ = 386.140 - 0.042 (2) Q = 386.140 - 0.082 Q
Using the above functions, the P and MR can be drawn as follows:
f. What is the total-revenue maximizing price and quantity, and how much revenue is earned there? (Round your price to the nearest cent, your quantity to the nearest whole unit, and your TR to the nearest dollar.) Compare that to the TR when P = $210.00 and P = $185.50.
At maximum revenue, MR = 0 =>386.140 = 0.082 Q => Q = 386.140 / 0.082 = 4650 (up to 0 decimal place)
and P = 386.140 - 0.042 (4650) = 193.07
Hence, the revenue maximizing price is less than $210 and more than $185.5. Therefore, it is consistent with answer in (d) that price needs to be reduced from $210 and increased from $185.5 so as to maximize profit. Because profit is maximized at price = $193.07 where MR = 0 and elasticity = 1.
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