a. Estimate the Cobb-Douglas production function Q=αL β1 K β2 , where Q=output; L = labor input; K = capital
Question 1
a.
Estimate the Cobb-Douglas production function Q=αL
β1
K
β2
, where Q=output; L = labor input; K = capital input; and α, β1, and β2 are the parameters to be estimated.
b.
Test whether the coefficients of capital and labor are statistically significant. Describe.
c.
Determine the percentage of the variation in output that is "explained" by the regression equation.
d.
Determine whether this production function exhibits increasing, decreasing or constant returns to scale. (Ignore the issue of statistical significance)
| Production Function for Wilson Company Data | |||
| Plant | Output (000 Tons) | Capital ($000) | Labor (000 Worker Hours) |
| 1 | 605.3 | 18,891 | 700.2 |
| 2 | 566.1 | 19,201 | 651.8 |
| 3 | 647.1 | 20,655 | 822.9 |
| 4 | 523.7 | 15,082 | 650.3 |
| 5 | 712.3 | 20,300 | 859 |
| 6 | 487.5 | 16,079 | 613 |
| 7 | 761.6 | 24,194 | 851.3 |
| 8 | 442.5 | 11,504 | 655.4 |
| 9 | 821.1 | 25,970 | 900.6 |
| 10 | 397.8 | 10,127 | 550.4 |
| 11 | 896.7 | 25,622 | 842.2 |
| 12 | 359.3 | 12,477 | 540.5 |
| 13 | 979.1 | 24,002 | 949.4 |
| 14 | 331.7 | 8,042 | 575.7 |
| 15 | 1064.9 | 23,972 | 925.8 |
QUESTION 2
a.
Estimate the demand for soft drinks using a multiple regression program available on your computer. Show the result.
b.
Interpret the coefficients and calculate the price elasticity of soft drink demand.
c.
Omit price from the regression equation and observe the bias introduced into the parameter estimate for income. Also describe the bias.
d.
Now omit both price and temperature from the regression equation. Should a marketing plan for soft drinks be designed that relocates most canned drink machines into low-income neighborhoods? Why or why not?
| EXPERIMENTAL DATA FOR 50 STATES | ||||
| Annual Cans per Capita | Price per six pack | Income per Capita | Mean Temp. | |
| Alabama | 200 | 2.19 | 13 | 66 |
| Arizona | 150 | 1.99 | 17 | 62 |
| Arkansas | 237 | 1.93 | 11 | 63 |
| California | 135 | 2.59 | 25 | 56 |
| Colorado | 121 | 2.29 | 19 | 52 |
| Connecticut | 118 | 2.49 | 27 | 50 |
| Delaware | 217 | 1.99 | 28 | 52 |
| Florida | 242 | 2.29 | 18 | 72 |
| Georgia | 295 | 1.89 | 14 | 64 |
| Idaho | 85 | 2.39 | 16 | 46 |
| Illinois | 114 | 2.35 | 24 | 52 |
| Indiana | 184 | 2.19 | 20 | 52 |
| Iowa | 104 | 2.21 | 16 | 50 |
| Kansas | 143 | 2.17 | 17 | 56 |
| Kentucky | 230 | 2.05 | 13 | 56 |
| Louisiana | 269 | 1.97 | 15 | 69 |
| Maine | 111 | 2.19 | 16 | 41 |
| Maryland | 217 | 2.11 | 21 | 54 |
| Massachusetts | 114 | 2.29 | 22 | 47 |
| Michigan | 108 | 2.25 | 21 | 47 |
| Minnesota | 108 | 2.31 | 18 | 41 |
| Mississippi | 248 | 1.98 | 10 | 65 |
| Missouri | 203 | 1.94 | 19 | 57 |
| Montana | 77 | 2.31 | 19 | 44 |
| Nebraska | 97 | 2.28 | 16 | 49 |
| Nevada | 166 | 2.19 | 24 | 48 |
| new Hampshire | 177 | 2.27 | 18 | 35 |
| New Jersey | 143 | 2.31 | 24 | 54 |
| New Mexico | 157 | 2.17 | 15 | 56 |
| New York | 111 | 2.43 | 25 | 48 |
| North Carolina | 330 | 1.89 | 13 | 59 |
| North Dakota | 63 | 2.33 | 14 | 39 |
| Ohio | 165 | 2.21 | 22 | 51 |
| Oklahoma | 184 | 2.19 | 16 | 82 |
| Oregon | 68 | 2.25 | 19 | 51 |
| Pennsylvania | 121 | 2.31 | 20 | 50 |
| Rhode Island | 138 | 2.23 | 20 | 50 |
| South Carolina | 237 | 1.93 | 12 | 65 |
| South Dakota | 95 | 2.34 | 13 | 45 |
| Tennessee | 236 | 2.19 | 13 | 60 |
| Texas | 222 | 2.08 | 17 | 69 |
| Utah | 100 | 2.37 | 16 | 50 |
| Vermont | 64 | 2.36 | 16 | 44 |
| Virginia | 270 | 2.04 | 16 | 58 |
| Washington | 77 | 2.19 | 20 | 49 |
| West Virginia | 144 | 2.11 | 15 | 55 |
| Wisconsin | 97 | 2.38 | 19 | 46 |
| Wyoming | 102 | 2.31 | 19 | 46 |
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