Posted: February 26th, 2023

ECONOMICS

<h

>Data

V

U

2

7

.7

3

2

9

87724

2

942

9

2006
3

751293191

2006
4

07

19

4.7

927067122

2006
5

2006
6

4.6

2006
7

4.7

2006
8

4.7

2006
9

880300466

2006
10

533070826

2006
11

4.5

84632363

2006
12

4.4

268367442

1

4.6

880321283

2007
2

5

4.5

833385914

2007
3

4.4

2007
4

4.5

7427

2007
5

4.4

484065556

2007
6

4.6

460894206

2007
7

4.7

2007
8

4.6

2007
9

4.7

2007
10

4.7

68

991273

2007
11

4.7

35320343

2007
12

5

280938476

1

8

5

2008
2

2008
3

2008
4

21

5

2008
5

2008
6

89

5.6

2008
7

5.8

.3938878231

2008
8

6.1

2008
9

6.1

2008
10

3.01

2008
11

786698017

2008
12

7.3

1

2009
2

2009
3

2009
4

9

27

2009
5

2.24

69

2009
6

2009
7

9.5

2009
8

2009
9

2009
10

2
10

2009
11

2009
12

9.9

1

9.8

2010
2

9.8

2010
3

9.9

2010
4

9.9

2010
5

9.6

2010
6

9.4

3

2010
7

9.4

2010
8

9.5

2010
9

2.678
9.5

2010
10

9.4

2010
11

9.8

2010
12

89

1

9.1

2011
2

9

51

2011
3

9

2011
4

9.1

2011
5

9

2011
6

9.1

2011
7

9

2011
8

9

2011
9

9

2011
10

3.4
8.8

2011
11

2011
12

8.5

1

3.33
8.3

2012
2

8.3

2012
3

4

8.2

2012
4

8.2

2012
5

8.2

2012
6
10734

8.2

2012
7

8.2

2

2012
8

3.668

2012
9

7.8

2012
10

7.8

2012
11

7.7

2012
12

7.9

1

8

6

2013
2

7.7

2013
3

7.5

2013
4

7.6

2013
5

7.5

2013
6

7.5

2013
7

7.3

2013
8

3.515

2013
9

7.2

2013
10

7.2

2013
11

2013
12

6.7

9

2014
1

6.6

2014
2

6.7

2014
3

3.474
6.7

2014
4

2014
5

6.3

2014
6

6.1

2014
7

6.2

2014
8

6.2

2014
9

5.9

2014
10

5.7

2014
11

5.8

2014
12

5.6

1

5.7

2015
2

5.5

2015
3

5.5

2015
4

5.4

2015
5

8

5.5

2015
6

2.7

2015
7

5.2

2015
8

5.1

2015
9

5

2015
10

2.23
5

2015
11

5

2015
12

5

1

4.9

2016
2

4.9

2016
3

5

2016
4

5

2016
5

4.7

2016
6

4.9

2016
7

4.9

2016
8

4.9

2016
9

5

2016
10

4.9

2016
11

4.6

2016
12

4.7

2017
1

4.8

2017
2

4.7

2017
3

4.5

2017
4

2.34
4.4

2017
5
16316

2017
6

4.3

2017
7

2.211
4.3

2017
8

4.4

2017
9

2.57
4.2

2017
10

4.1

2017
11

4.1

2017
12

4.1

2018
1

4.1

Forecast

Yr
Mo
Gas
U
S&P

2

3.6

2023
3
3.19
3.6

2023
4

3.7

2023
5
3.77
3.9

2023
6

3.7

Spring 202

3

Take-Home Project
Professor C. Brown
02-08-23

Answer all questions. The project is due. Please submit your answers in Word (PDF also
acceptable). Do NOT submit Excel files. Charts should be copied and pasted from Excel to Word.

The Excel file necessary to complete this project is attached (also available at the MANAGERIAL
ECON SP23 course shell).

1. This question is worth 50 points—2 points each, except for subparts (a) and (i), which are

worth 6 points each, and subpart (j), which is worth 10 points.

Use the file “Data for Question 1.” This file contains 145 monthly observations (2006-1 to
2018-1) on the following variables:

SUV: Sales of new sport utility vehicles in the U.S. (seasonally adjusted, in millions of
dollars).

U: The civilian unemployment rate.

Gas: Average price per gallon of unleaded gasoline.

SP: Standard and Poor’s Index of 500 stock prices with dividend reinvestment, monthly
average.

a) Use regression to estimate the following model specification. Report the results of the

regression—that is, report your estimates of β0 , β1 , β2, and β3.

𝑆𝑈𝑉𝑡 = 𝛽0 + 𝛽1𝐺𝑎𝑠𝑡 + 𝛽2𝑈𝑡 + 𝛽3𝑆𝑃𝑡

b) Are the signs of the (estimated) coefficients consistent with your (prior) expectations?
Explain.

c) Suppose that the unemployment rate (U) is projected to decline by 0.2 percentage
points next month. Based on the equation you have estimated, what is the predicted
effect on SUV in the next month, holding all other factors constant? Be precise.

d) Can the following null hypothesis be rejected at the 0.01 significance level? Explain.

𝐻0: 𝛽2 = 0

2

e) Use the equation you estimated above to obtain a fitted value of SUV for 2008-7.

Compute (and report) the ratio of the in-sample forecast error (𝑆𝑈𝑉𝑡 − 𝑆𝑈�̂�𝑡) for this
month to the standard error of the regression (SE). Provide an interpretation of this
ratio.

f) Prepare a chart (not table or spreadsheet) illustrating actual and fitted values of SUV for
the period 2006-4 to 2018-1.

g) Report the value of R2 and provide a (precise) interpretation.

h) Set up an F-test. Can you reject null hypothesis at the 1 percent (.01) significance level?

i) Use the data contained in “Forecast” of your spreadsheet to forecast the value of SUV
for 2023-02 t 2023-06. Report your results.

j) Estimate the following regression specification:

𝑙𝑛𝑆𝑈𝑉𝑡 = 𝛽0 + 𝛽1𝑙𝑛𝐺𝑎𝑠𝑡 + 𝛽2𝑙𝑛𝑈𝑡 + 𝛽3𝑙𝑛𝑆𝑃𝑡

Is the demand fo𝑟 𝑆𝑈𝑉𝑠 elastic with respect to gas prices? 𝑃𝑙𝑒𝑎𝑠𝑒 𝑒𝑥𝑝𝑙𝑎𝑖𝑛.

2. This question is worth 10 points. Answer the following questions.
a) See the diagram above that depicts the demand for non-diet soft drinks. Assume the

current price of soft drinks is $3.58 per 12-pack. Compute point elasticity of demand at
the current price. Are soft drink companies maximizing profits from the sale of soft
drinks? Explain.

b) Soft drink consumption is blamed for health problems such as childhood obesity and
diabetes. Several states (including Arkansas) impose a soft drink tax, justified by public

3

health concerns. Suppose a soft drink tax is imposed that raises the price of soft drinks
(from the current price of $3.50) by 8 percent. How successful would the tax be in
reducing soft drink consumption? Would it make a difference if the pre-tax price were
$4.89 per 12-pack?

c) Which figures stated below is likely to represent each of the following. Give the reasons
for your choice in each case.

a. Income elasticity of demand for low price cuts of meat;
b. Income elasticity of demand for Apple iPads;
c. Price elasticity of demand for gasoline

-1.6 -0.1 +4.3

d) When the price of Good X is $27, the quantity-demanded of Good Y is 1,200 units. When
the price of Good X falls to $23 (the price of good Y unchanged), the quantity-demanded
of Good Y falls to 800 units. Compute cross-price elasticity of demand between Goods X
and Y. Are Goods X and Y substitutes, or complements? Explain.

ECON 6313-001
• Spring 2023 Take-Home Project
• Professor C. Brown 02-08-23
• Answer all questions. The project is due. Please submit your answers in Word (PDF also acceptable). Do NOT submit Excel files. Charts should be copied and pasted from Excel to Word.

This project is worth sixty (60) points. Submit your work in-class on Wednesday, February 15.