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Please answer the following problems with the work shown. Please and thank you


style="color:rgb(192,0,0);">DBA 8355 Problem Set 2:

Problem 1

The "cars" data include demand for passenger cars in the United States from 1971 to 1986.  Estimate the following model using the "cars" data attached:

ln Yt =B0+B1lnX1t+B2lnX2t+B3lnX3t+B4lnX4t+B5lnX5t+t

where

Yt = the demand for passenger cars (years ranging from 1971 to 1986)

X1t = new cars consumer price index

X2t = consumer price index

X3t = personal disposable income (measured in billions of dollars)

X4t = interest rate

X5t = employed civilian labor force (measured in thousands of individuals)

First, please estimate, examine, and interpret the model.  Put emphasis on the model's coefficient of determination, mean squared error, and parameter coefficients.  Finally, is there multicollinearity in this problem? How do you know?


Problem 2

Explore the "grade" data using attached.  Estimate a model that examines the relationship between grade and drinks consumed per week (drinks) and hours studied per week (hours).  Please interpret your results w/ emphasis on the model's coefficient of determination, mean squared error, and parameter coefficients.  

Problem 3

qa_attachment_1570039337099.jpgqa_attachment_1570039380572.jpg

What are the main sources of bias in regression analysis as it relates to model estimation and specification?  What can be done to address each form of bias w/ an emphasis on the advantages and disadvantages of each approach, if applicable?

qa_attachment_1570039337099.jpg

qa_attachment_1570039380572.jpg

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Table 8 5
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A
B
C
D
E
F
G
1
2 Demand for New Passenger Cars in the United States, 1971 to 1986
888888
6 Year
Y
X2
X3
X4
X5
X6
7
1971
10227
112
121.3
776.8
4.89
79367
8
1972
10872
111
125.3
839.6
4.55
82153
9
1973
11350
111.1
133.1
949.8
7.38
85064
10
1974
8775
117.5
147.7
1038.4
8.61
86794
11
1975
8539
127.6
161.2
1142.8
6. 16
85846
12
1976
9994
135.7
170.5
1252.6
5.22
88752
13
1977
11046
142.9
181.5
1379.3
5.5
92017
14
1978
11164
153.8
195.4
1551.2
7.78
96048
15
1979
10559
166
217.4
1729.3
10.25
98824
16
1980
8979
179.3
246.8
1918
11.28
99303
17
1981
8535
190.2
272.4
2127.6
13.73
100397
18
1982
7980
197.6
289.1
2261.4
11.2
99526
19
1983
9179
202.6
298.4
2428.1
8.69
100834
20
1984
10394
208.5
311.1
2670.6
9.65
105005
21
1985
11039
215.2
322.2
2841.1
7.75
107150
22
1986
11450
224.4
328.4
3022.1
6.31
109597
23
24
25 Notes: Y = New passenger cars sold (thousands), seasonally unadjusted
26 X2 = New cars Consumer Price Index (1967 = 100), seasonally
27 unadjusted
28 X3 = Consumer Price Index, all items, all urban consumers (1967 = 100),
29 seasonally unadjusted
30 X4 = Personal disposable income (PDI) ($, in billions), unadjusted for
31 seasonal variation
32 X5 = Interest rate (percent), finance company paper placed directly
33 X6 = Employed civilian labor force (thousands), unadjusted for seasonal
34 variation
35 Source: Business Statistics, 1986, a Supplement to the Current Survey of
36 Business, U.S. Department of Commerce.
37
38
39
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45
46
47

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