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A4 Industrial produces hydraulic pumps using a process that can be approximated

ID: 1113210 • Letter: A

Question

A4 Industrial produces hydraulic pumps using a process that can be approximated by a Cobb-Douglas production function. The production method uses tool shops that contain pieces of equipment that can be operated by a varying number of workers. The number of shops (units of variable capital) used during the month are given. The firm also hires skilled workers, and the number of full-time skilled workers hired for the month is given. The monthly output (number of pumps) produced is also given. The manager wants to estimate the Cobb-Douglas production function in order to determine the number of shops and number of workers required to achieve various levels of production.

The manager thus asks you to estimate a log-linear regression model based on the following monthly data over the last 2 years.

Q = quantity of boats produced per year

L = number of full-time workers per year

K = capital (number of shops) rented per year

P = average selling price per pump sold

Month

t

L

K

Q

P

Oct-15

1

120

25

1150

$438.93

Nov-15

2

122

25

1170

$437.88

Dec-15

3

118

26

1160

$438.46

Jan-16

4

110

26

1122

$440.14

Feb-16

5

116

24

1128

$439.96

Mar-16

6

120

24

1146

$439.01

Apr-16

7

124

27

1193

$436.90

May-16

8

125

27

1202

$436.38

Jun-16

9

130

28

1235

$434.92

Jul-16

10

127

28

1219

$435.58

Aug-16

11

128

27

1216

$435.85

Sep-16

12

136

27

1250

$434.09

Oct-16

13

140

27

1265

$433.54

Nov-16

14

135

28

1255

$433.85

Dec-16

15

130

28

1233

$435.05

Jan-17

16

135

29

1264

$433.43

Feb-17

17

128

29

1235

$434.95

Mar-17

18

138

30

1286

$432.39

Apr-17

19

145

30

1315

$431.19

May-17

20

141

28

1282

$432.58

Jun-17

21

134

29

1260

$433.78

Jul-17

22

140

29.0

1290

$432.20

Aug-17

23

142

30.0

1300

$431.89

Sep-17

24

146

30.0

1324

$430.72

A4 Industrial hires labor and procures capital in competitive input markets. For that last two years, the input prices have been constant, and given as follows:

w   = $2,400 = monthly wage rate per worker

r    = $1,600 = monthly rental rate per shop

The firm also faces fixed cost (FC) of building rental, fixed capital, and overhead expenses given as follows:

f    = $60,000

Month

t

L

K

Q

P

Oct-15

1

120

25

1150

$438.93

Nov-15

2

122

25

1170

$437.88

Dec-15

3

118

26

1160

$438.46

Jan-16

4

110

26

1122

$440.14

Feb-16

5

116

24

1128

$439.96

Mar-16

6

120

24

1146

$439.01

Apr-16

7

124

27

1193

$436.90

May-16

8

125

27

1202

$436.38

Jun-16

9

130

28

1235

$434.92

Jul-16

10

127

28

1219

$435.58

Aug-16

11

128

27

1216

$435.85

Sep-16

12

136

27

1250

$434.09

Oct-16

13

140

27

1265

$433.54

Nov-16

14

135

28

1255

$433.85

Dec-16

15

130

28

1233

$435.05

Jan-17

16

135

29

1264

$433.43

Feb-17

17

128

29

1235

$434.95

Mar-17

18

138

30

1286

$432.39

Apr-17

19

145

30

1315

$431.19

May-17

20

141

28

1282

$432.58

Jun-17

21

134

29

1260

$433.78

Jul-17

22

140

29.0

1290

$432.20

Aug-17

23

142

30.0

1300

$431.89

Sep-17

24

146

30.0

1324

$430.72

6. When the firm maximizes profit (and given the choice of output, also minimizes costs), what is the marginal rate of technical substitution (which, of course, is also equal to the slope of the isocost line at the cost-minimizing point)? MRTSKL -# =

Explanation / Answer

[ Only for reference since the question talks about log linear version of Cobb douglas function

The log linear form of Cobb-Douglas production function will be -

log Q = A + B*log L + C*log K

Below are regression results -

Log Q = 1.7742 + 0.4668*Log K + 0.2279*Log L]

6. The iso-cost line equation is -

2400L+ 16000K = C

2400 dL + 1600 dK = dC
dc = 0

2400 + 1600 dk/dL = 0
dk/dL = -2400/1600 =-1.5

The MRTS = dk/dL = - 1.5

Dependent var:Log Q Coefficients Standard Error t Stat P-value Intercept 1.7742 0.01 137.36 0.00 Log K 0.4668 0.01 45.40 0.00 Log L 0.2279 0.01 19.89 0.00
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