Download 640 Week 2 Asignment 2

Running head: 640 WEEK 2 ASIGNMENT 2
Consumer Demand Analysis and Estimation Applied Problems
Name
Ashford University
Managerial economics
BUS 640
Dr. Sayim
January 14, 2013
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640 WEEK 2 ASIGNMENT 2
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640 Week 2 Assignment 2
Please, complete the following 3 applied problems in a Word or Excel document. Show all your calculations and explain your results. Submit
your assignment in the drop box by using the Assignment Submission button.
1. Roshima is researching universities where she could study for her MBA degree. She is considering 3 major attributes that she considers important in
her choice: ranking, price, and location. The value she places on each attribute, however, differs according to whether she remains full-time employed
during her studies or quits her job and focuses on her degree. If she continues to work full time and takes all her courses online, then ranking is the most
important attribute, twice as important as price and three times as important as location. If she quits her job and attends school full time, then location
becomes three times as important as ranking and twice as important as price. She is considering two universities, respectively, the MBA program at
Arizona State University (ASU) and the MBA program at University of Phoenix (UOP), both of which are priced at approximately $25,000. She has
rated each attribute on a scale of 1 to 100 for each of the two schools.
Attribute
Ranking
ASU
80
UOP
70
Location
50
70
Price
45
45
Problem 1
Attribute
Ranking = r
Location = l
Price = p
Keeps job (EU)
Quits job (EU)
ASU
80
50
45
119.17
51.17
UOP
70
70
45
115.83
115.83
Keeps job =
Quits job =
r=2p r=3l
l=3r l=2p
ASU
9533.333333
2558.333333
UOP
8108.33
8108.33
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a. Which of the two options should Roshima pursue of she wants to keep her full-time job? (Calculate the total expected utility from each school
option and compare. Graph is not required)
She should go to ASU its EU is 119.17 which is an EU that is better than the UOP EU by 3.36. UOP = 115.83 for UE
b. Which of the two options should she pick if she plans to quit her job and dedicate to her studies?
She should pick UOP with an EU of115.83 verses an ASU EU of 51.17
c. Which option should she pursue if the probability of being laid off and unable to find a new job is estimated as 0.6? Show your calculations
and explain your reasoning.
EU keep job with .6 probability of layoff and no job.
EU= .6*119.17*r+.6*297.5*r = .6*119.17*90+.6*297.5*90= 172,318,009.50
EU Quit job.
EU=.6*115.83*90+.6*347.5*90= 195,638,260.50
She should quit and go to the university of Phoenix
2. The demand function for Einstein Bagels has been estimated as follows:
Qx = -15.87 – 40.73Px + 84.17Py + 0.55Ax
where Qx represents thousands of bagels; Px is the price per bagel; Py is the average price per bagel of other brands of bagels; and Ax represents
thousands of dollars spent advertising Einstein Bagels. The current values of the independent variables are Ax=216, Px=0.85, and Py=0.79.
640 WEEK 2 ASIGNMENT 2
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Problem 2
original
Qx = bagels
Px = price per Einstein brand
Py = price per other brand
Ax = advertising dollars
(a)
Price elasticity
variable
-15.87
40.73
84.17
0.55
Einstein Brand
change in demand =
=
=
134.8038
0.256821395
26%
=
128.6943
32%
(b)
Price elasticity
change in price
( c)
Profit maximizing
total revenue
total cost
total profit
114.58323
13.48038
$
101.10
(d)
advertising
88%
a. Calculate the price elasticity of demand for Einstein’s Bagels and explain what it means.
% change Qdx/ % change Px = Price elasticity of demand
new
0.85
0.79
216
34.
66.
1
640 WEEK 2 ASIGNMENT 2
.2486 = .2925
5
Price elasticity of demand=.2925
.85
This is an inelastic price item. Any number < than 1 the price of demand is inelastic.
b. Derive an expression for the (inverse) demand curve for Einsteins’s Bagels.
As price for bagels rises, demand remains constant
c. If the cost of producing Einstein’s Bagels is constant at $0.10 per bagel, should they reduce price and thereafter, sell more bagels
(assume profit maximization is the company’s goal)?
No, this is an inelastic product the return would not justify the reduction.
d. Should Einstein Bagels spend more on advertising? No, their
Budget is adequate.
3. The consulting firm that you work for has been hired by the US Government to provide an independent analysis of the demand-side effects of a
contemplated increase in the tax on gasoline. They provide you with a data set relating to the period 1962-1987, which they say contains valuable historic
lessons relating to the impact of volatile pump prices due to the supply restrictions imposed by the Organization of Petroleum Exporting Countries
(OPEC), and the Corporate Average Fuel Economy (CAFE) regulations that required car manufacturers to increase the fuel efficiency of the cars they
sold, while at the same time Real Disposable Income (RDI) per capita was rising, the number of passenger cars (NPC) almost doubled, and inflation was
pushing up the Consumer Price Index (CPI).
a. Reconcile the fact that while the quantity demanded of gasoline and pump prices both rise over this period generally, they are inversely
related along a demand curve.
`It is true that normally the quantity demanded of gasoline is inversely proportional to pump prices. The reason that this is not true during this
period is that there were external variances that were so large that they could all be considered outliers compared to a normal demand curve.
Curves and graphs in economics show probability due to the collection and analyst rational of data and portray the continuance of the norm.
The numbers during this timeframe were just not normal.
640 WEEK 2 ASIGNMENT 2
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b.Conduct a multiple regression analysis to explain the quantity demanded of gasoline in terms of the other data provided. (Transpose this data
into an Excel spread-sheet and use the Excel regression tool, if loaded, or alternatively download an ‘add-in’ regression program such as
‘Statpro’ to find the regression statistics).
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.991823
R Square
0.983713
Adjusted R
Square
0.979426
Standard
Error
1544.571
Observations
25
ANOVA
df
Regression
Residual
Total
Intercept
X Variable 1
X Variable 2
X Variable 3
5
19
24
Coefficients
82547.14
-142.647
0.638322
-6224.56
SS
2.74E+09
45328310
2.78E+09
Significance
MS
F
F
5.48E+08 229.5094
2.67E-16
2385701
Standard
Error
t Stat
P-value
26132.28 3.158819 0.00517
46.47614 -3.06926 0.006313
0.243492 2.621533 0.016795
1743.79 -3.56956 0.002045
Upper
Lower
Upper
Lower 95%
95%
95.0%
95.0%
27851.65 137242.6 27851.65 137242.6
-239.923 -45.3716 -239.923 -45.3716
0.128688 1.147956 0.128688 1.147956
-9874.35 -2574.76 -9874.35 -2574.76
640 WEEK 2 ASIGNMENT 2
X Variable 4
X Variable 5
0.778334
53.13485
7
2.598568 0.299524 0.767792
76.26494 0.696714 0.494418
-4.66053
6.2172
-106.49 212.7592
-4.66053
6.2172
-106.49 212.7592
Upper 95%
#N/A
44.19799
1.603837
176.3975
5.504301
-143.256
Lower
95.0%
#N/A
-84.7854
0.678775
-1933.4
-7.27438
-221.996
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c What proportion of the variance in Qx is explained by these other variables? What missing variables might account for the remainder of the
variance in the quantity demanded of gasoline?
5%, extra miles driven or not driven due to price of gas rising and inflation
d. Use the regression equation to predict the quantity demanded of gasoline in 1988 for the values Px = 68.5; NPC = 145,885; MPG = 20.36; RDI
= 11,192; and CPI = 354.6.
1988 Qx= 83,245.14
e. What is the 95% confidence interval for your prediction?
The equation covers 95 % of variance the other 5% is mostly located in the x variables.