Posted: February 26th, 2023

ECONOMICS

<h2>Data V U 27.732987724 2 9429 2006 3 751293191 2006 4 0719 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 68991273 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
Yr Mo SU GasS&P
2006 1 127 2.3 4 197.985
200611 2.24 4.8 1943.1870549586
12523 2.413 4.7 1967.3
110 2.71993.7
12500 2.831 4.6 1936.408422328
12336 2.8081939.0335348203
9336 2.9231950.9944548118
10515 2.911997.4147288884
10055 2.501 4.5 2048.8
10543 2.214 4.4 2115.6
10950 2.2112155.8
13141 2.2842186.1
200711443 2.1912219.1
12317 2.232175.7
12377 2.5032200.1194010049
12936 2.7872297.52017
13784 3.1192377.7
13686 3.0242338.2
13755 2.9472265.7492038732
13573 2.7772314.5698456115
12580 2.8172385.7193741474
12676 2.7912423.6
12508 3.0642322.34
12054 2.9842306.2
200811969 3.012167.9005327786
12018 3.016 4.9 2097.4743032769
9421 3.215 5.1 2088.4176404603
9468 3.42190.1299351133
8965 3.735 5.4 2218.497865491
9022 3.92031.4786230429
8100 4.0022014
7878 3.742043.5313295087
8234 3.7091861.4376860914
77666.5 1548.8132029137
7661 2.099 6.8 1437.6
7263 1.6691452.976
20096879 1.772 7.8 1330.51
6581 1.892 8.3 1188.841
6695 1.615 8.7 1292.977
6467 2.0211416.7
62399.4 1495.9
4660 2.597 9.5 1498.936
5833 2.4781612.312
6838 2.562 9.6 1670.523
7109 2.48 9.8 1732.859
70931700.668
7806 2.614 9.9 1802.68
8208 2.5681837.499
20109052 2.6781771.398
7561 2.6031826.27
7784 2.7421936.477
7948 2.8181967.049
8661 2.331809.979
8973 2.6841715.2
9826 2.6791835.404
10161 2.6831752.546
107321908.951
10734 2.7661981.585
9827 2.8151981.839
10997 2.361 9.3 2114.2
201111058 3.0582164.401
11211 3.1682238.5
11389 3.5092239.441
9768 3.7462305.763
9721 3.8492279.663
9882 3.6282241.663
11236 2.8912196.079
9563 3.6122076.784
9191 3.5731930.79
102592141.81
9806 3.33 8.6 2137.08
9438 3.222158.94
201299852255.69
9844 2.8132353.23
9710 3.772430.67
10787 3.8372415.42
10544 3.6432270.25
3.4652363.79
10692 3.3792396.6
104038.1 2450.6
10329 3.0412513.93
9660 3.6532467.51
9639 3.382481.82
9904 3.2562504.44
201310352 3.2552634.1
11205 3.6052669.92
10829 3.6482770.05
11327 2.9182823.42
11406 3.5652889.46
11562 3.5762850.66
11254 3.5152995.72
116547.2 2908.96
11848 3.4743000.18
12516 3.2853138.09
13544 2.549 6.9 3233.72
12383 3.2093315.5
11668 3.2523200.95
12808 3.3053347.38
133783375.51
13525 3.59 6.3 3400.46
13987 3.6013480.29
12813 3.0223552.18
14956 3.5393503.19
13233 3.4253643.34
12874 3.3543592.25
12968 3.123679.99
13271 2.8753778.96
14085 2.4883769.44
201513394 1.6373656.28
13423 2.1523866.42
14843 2.3523805.27
13886 2.3693841.78
14664 2.573891.18
152755.3 3815.85
15978 2.6663895.8
15479 2.1013660.75
16134 2.2753570.17
153933871.33
15690 2.0883882.84
15004 1.9463821.6
201615661 1.8433631.96
15847 1.6813627.06
14970 1.5163873.11
15566 2.0273888.13
14573 2.1993957.95
14775 2.3033968.21
15171 2.1574114.51
15410 2.1194120.29
15440 2.1614121.06
15825 1.8224045.89
15664 2.1054195.73
16459 2.1924278.66
16316 2.2854359.81
16323 2.2274532.93
16075 2.2434538.21
156084584.82
1.919 4.3 4649.34
16252 2.2574678.36
156714774.56
16011 2.2974789.18
161644887.97
16941 2.435002.03
17221 2.4745155.44
17192 1.9115212.76
17428 2.4675511.21

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
SUV (hat)
20233.363899
3365
3.264081
4211
4.074098

  • ECON 6313-001
  • 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.
  • This project is worth sixty (60) points. Submit your work in-class on Wednesday, February 15.
  • 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.

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