Economics

1.

a.

Company is primarily an athletic apparel and shoe manufacturer. Company will be producing athletic shoes and equipment mainly targeting youth and sports men. However, it products range will also include items which could be used by people of any age. Therefore, it can be stated that though, company is primarily producing products for young generation but it will also have segments targeting people from all sizes, and ages.

b.

Sales  $          100,000  $          150,000  $          200,000  $          2,500,000  $          300,000  $          350,000  $          400,000  $          450,000  $          500,000  $          550,000
Profits  $             10,000  $             15,750  $             22,000  $              300,000  $             37,500  $             45,500  $             54,000  $             63,000  $             72,500  $             82,500
Valuation $ 1000000

This graph shows that the sales of the apparel business is expected to increase by $50, 000 every year, and shows the related profits as well.

2.

a.

P= It is the price of good which company is selling

M=M represents the income of the consumers, which can change with time. SO it can change and is a variable is the equation

PR= This is the price of the related goods, which can change and can attract the consumers to switch products or substitute them for Sultan’s Athletic products

This shows the taste patterns of the consumers in the market

Pe= This is the expected price of the product in some future period

Expected price of the product in some future period

N= There no special number all consumers buy shoes even if they are not        exercising

b.

The variables which could affect the supply  side of the equation are given below:

P= It is the price of good which company is selling

PI= This is the price of raw material or inputs used in the manufacturing of shoes, clothes and other equipment.

Pr= It is the prices of related goods in the market which competitors are trying to sell.

T= It defines the available technology in the market used by the manufacturer

Pe= It is the producers price expectations based on the inflation projected by the central bank.

F= It represents the number of similar fi9rms which are operating in the industry.

3.

a.

TB 180A – A2
MB 180-2.5A
TC 200-15A+3A2
MC 20+5A
A TB TC MB MC
1 179 188 177.5 25
2 356 182 175 30
3 531 182 172.5 35
4 704 188 170 40
5 875 200 167.5 45
6 1044 218 165 50
7 1211 242 162.5 55
8 1376 272 160 60
9 1539 308 157.5 65
10 1700 350 155 70
11 1859 398 152.5 75
12 2016 452 150 80
13 2171 512 147.5 85
14 2324 578 145 90
15 2475 650 142.5 95
16 2624 728 140 100
17 2771 812 137.5 105
18 2916 902 135 110
19 3059 998 132.5 115
20 3200 1100 130 120
21 3339 1208 127.5 125
22 3476 1322 125 130
23 3611 1442 122.5 135
24 3744 1568 120 140
25 3875 1700 117.5 145
26 4004 1838 115 150
27 4131 1982 112.5 155
28 4256 2132 110 160
29 4379 2288 107.5 165
30 4500 2450 105 170
31 4619 2618 102.5 175
32 4736 2792 100 180
33 4851 2972 97.5 185
34 4964 3158 95 190
35 5075 3350 92.5 195
36 5184 3548 90 200
37 5291 3752 87.5 205
38 5396 3962 85 210
39 5499 4178 82.5 215
40 5600 4400 80 220
41 5699 4628 77.5 225
42 5796 4862 75 230
43 5891 5102 72.5 235
44 5984 5348 70 240
45 6075 5600 67.5 245
46 6164 5858 65 250
47 6251 6122 62.5 255
48 6336 6392 60 260
49 6419 6668 57.5 265
50 6500 6950 55 270

The table shows that the total benefit is incresaing with the total cost as wll whereas the total cost is greater then the total benefit. The marginal benefit is declining with the increase in the value of A, and the marginal cost is increasing.

The graph shows the curve of the total benefit and total cost. The total cost is greater than the total benefit at the highest value of A.

b.

This graph shows the declining trend of the marginal benefit and the increasing trend of the marginal cost.

According to this chart, look at the point of intersection between MB and MC. They intersect at Unit 21. It means that company should manufacture 21 units.

c.

i. MB at half A is 125

ii. MC at half A is 132

iii. But, if we continue producing more, company can produce 41 units where MB=MC. This is the optimal point.

d.

i. MC is 20.5

ii. MB  is 20.5

iii. If company will go beyond this point, it will only incur loss. Therefore, optimal point is that company only makes 10 units.

e

These estimations may not be practical for the company. Since, Company is expected to make thousands of dollars. How is it possible that it only makes only 21, 41 or 10 units in different scenarios? Therefore,   the model may not be a realistic presentation of the real scenario, where sports manufacturers make healthy sales and units.

4.

a.In this business of sport apparel and shoes, like any other business, many variables affect the demand and supply of the company’s products. Here, what’s important is to determine that how each factor will have an impact on the dependent factor in the model.  SO, all these factors must be factored out which could realistically have a profound impact on demand of the company’s products.

b. Dependent variable in this project is the demand for the products of Sultan’s Athletics Store. Independent variables are all the variables which could have effect on the demand of the product. These are on the right side of the equation stated above.

Qd  abPcMdPR  efPe    gN

Qs   hkPlPI   mPr   nTrPe  sF

c. Regression Analysis

Here, regression is run by keeping the other variables constant and effect of price on demand is determined here. Result is depicted in following table:

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.654562
R Square 0.428452
Adjusted R Square 0.411642
Standard Error 135.5019
Observations 36
ANOVA
  df SS MS F Significance F
Regression 1 467971 467971 25.48757 1.49E-05
Residual 34 624265.6 18360.75
Total 35 1092237      
  Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 760.109 84.488 8.99665 1.63E-10 588.4087 931.8093 588.4087 931.8093
Price -53.0049 10.49909 -5.04852 1.49E-05 -74.3416 -31.6682 -74.3416 -31.6682

d. Interpretation:

Two important pieces of information here given here are:

Intercept:  Value of intercept is 760.109, it depicts that whether there is high price or lower price, this demand of 760 will be there. So, it is autonomous demand for the product of Sultan.

Slope: Slope of -53 indicates the negative relationship between the demand and price of Sultan Apparel.It means that if the price increase by 1 unit, demand will decline by 53.

Similarly, if the values for other independent variables are available, regression can apply for those as well to see the impact on demand of the products.

e.

If the price is changed, it can produce different results. This is shown in the following regression models:

If Price increases by 1, we get

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.991226
R Square 0.982529
Adjusted R Square 0.982015
Standard Error 23.69054
Observations 36
ANOVA
  df SS MS F Significance F
Regression 1 1073154 1073154 1912.108 1.8E-31
Residual 34 19082.22 561.2416
Total 35 1092237      
  Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept -107.965 11.17322 -9.66284 2.79E-11 -130.672 -85.2583 -130.672 -85.2583
P+1 16.62018 0.380084 43.72765 1.8E-31 15.84775 17.3926 15.84775 17.3926

However, if price decreases with increasing demand,

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.991226
R Square 0.982529
Adjusted R Square 0.982015
Standard Error 23.69054
Observations 36
ANOVA
  df SS MS F Significance F
Regression 1 1073154 1073154 1912.108 1.8E-31
Residual 34 19082.22 561.2416
Total 35 1092237      
  Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 806.1446 11.17322 72.14974 8.74E-39 783.4379 828.8513 783.4379 828.8513
P -16.6202 0.380084 -43.7277 1.8E-31 -17.3926 -15.8478 -17.3926 -15.8478

5.

a b
Qty Marginal Utility Total Utility
1 40 40
2 35 75
3 30 105
4 25 130
5 20 150
6 15 165
7 10 175
8 5 180
9 0 180
10 -5 175

c.

Diminishing Marginal Utility is observed in case of Diminishing normal goods. If the goods are of special nature like wealth or knowledge it states that the good observed is of that specific nature

d.

Our Product Other Product
Price  $                          8  $                     16
Qty Marginal Utility of Product MU per Dollar Marginal Utility of other product MU per Dollar Other Product
1 40  $                 5.00 30  $                   1.88
2 35  $                 4.38 27  $                   1.69
3 30  $                 3.75 24  $                   1.50
4 25  $                 3.13 21  $                   1.31
5 20  $                 2.50 18  $                   1.13
6 15  $                 1.88 15  $                   0.94
7 10  $                 1.25 12  $                   0.75
8 5  $                 0.63 9  $                   0.56
9 0  $                      –   6  $                   0.38
10 -5  $               (0.63) 3  $                   0.19

The graph shows that the marginal utility of other products is lower at first but is greater with the increase in the units, whereas it is vice versa for our product.

e

Based on the results the consumer would consume first 8 units of our product and then use 3 units of Other product in order to maximize its revenue

6

a.

Quantity Price Total Revenue Marginal Revenue Elasticity
Q P TR MR E
1 50 50
2 49 98 48 -50.00
3 48 144 46 -24.50
4 47 188 44 -16.00
5 46 230 42 -11.75
6 45 270 40 -9.20
7 44 308 38 -7.50
8 43 344 36 -6.29
9 42 378 34 -5.38
10 41 410 32 -4.67
11 40 440 30 -4.10
12 39 468 28 -3.64
13 38 494 26 -3.25
14 37 518 24 -2.92
15 36 540 22 -2.64
16 35 560 20 -2.40
17 34 578 18 -2.19
18 33 594 16 -2.00
19 32 608 14 -1.83
20 31 620 12 -1.68
21 30 630 10 -1.55
22 29 638 8 -1.43
23 28 644 6 -1.32
24 27 648 4 -1.22
25 26 650 2 -1.13
26 25 650 0 -1.04
27 24 648 -2 -0.96
28 23 644 -4 -0.89
29 22 638 -6 -0.82
30 21 630 -8 -0.76
31 20 620 -10 -0.70
32 19 608 -12 -0.65
33 18 594 -14 -0.59
34 17 578 -16 -0.55
35 16 560 -18 -0.50
36 15 540 -20 -0.46
37 14 518 -22 -0.42
38 13 494 -24 -0.38
39 12 468 -26 -0.34
40 11 440 -28 -0.31
41 10 410 -30 -0.28
42 9 378 -32 -0.24
43 8 344 -34 -0.21
44 7 308 -36 -0.19
45 6 270 -38 -0.16
46 5 230 -40 -0.13
47 4 188 -42 -0.11
48 3 144 -44 -0.09
49 2 98 -46 -0.06
50 1 50 -48 -0.04

b.

The total revenue shows the elasticity behavior which is negative both for the lower quantity and high price, and higher quantity and lower price, and is highest at the 32 units and price of $19.

7

Months Sales Actual Sales Forecasted Difference
Jan-16  $            995,054  $            1,016,052  $   (20,999)
Feb-16  $        1,031,659  $            1,015,506  $     16,153
Mar-16  $            985,678  $            1,014,959  $   (29,281)
Apr-16  $        1,008,962  $            1,014,413  $     (5,451)
May-16  $        1,010,442  $            1,013,866  $     (3,424)
Jun-16  $        1,033,856  $            1,013,319  $     20,536
Jul-16  $        1,038,767  $            1,012,773  $     25,994
Aug-16  $        1,025,377  $            1,012,226  $     13,151
Sep-16  $        1,013,167  $            1,011,680  $       1,488
Oct-16  $            987,796  $            1,011,133  $   (23,337)
Nov-16  $            1,010,586
Dec-16  $            1,010,040
Jan-17  $            1,009,493
Feb-17  $            1,008,947
Mar-17  $            1,008,400
Apr-17  $            1,007,853
May-17  $            1,007,307
Jun-17  $            1,006,760
Jul-17  $            1,006,214
Aug-17  $            1,005,667
Sep-17  $            1,005,121

a.

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.170805
R Square 0.029174
Adjusted R Square -0.02192
Standard Error 20072.66
Observations 21
ANOVA
  df SS MS F Significance F
Regression 1 2.3E+08 2.3E+08 0.570969 0.45914
Residual 19 7.66E+09 4.03E+08
Total 20 7.89E+09      
  Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 1016599 9083.006 111.9232 2.95E-28 997588.1 1035610 997588.1 1035610
Time -546.596 723.3686 -0.75563 0.45914 -2060.62 967.4324 -2060.62 967.4324

b.

i.

ii

Since this is a forecasted data based on alpha and beta obtained from forecasting data with time it can be observed that the results are linear and the sales in September is forecasted to be $ 1,005,121

8

Q L FC TC TVC MP MC TP AP AVC
0 0 50 50 0 0 0 0 0.00 0
10 0.6 50 56 6 16.67 0.60 16.67 27.78 5.60
20 1 50 66 10 25.00 0.40 41.67 41.67 3.30
30 1.3 50 79 13 33.33 0.30 75.00 57.69 2.63
40 1.7 50 96 17 25.00 0.40 100.00 58.82 2.40
50 2.3 50 119 23 16.67 0.60 116.67 50.72 2.38
60 3.2 50 151 32 11.11 0.90 127.78 39.93 2.52
70 4.4 50 195 44 8.33 1.20 136.11 30.93 2.79
80 6.2 50 257 62 5.56 1.80 141.67 22.85 3.21

a.

This graph shows that the marginal profit has a curving trend, first increasing and then decreasing constantly, whereas the marginal cost is relatively constant and is well below the marginal profit.

b.

This graph shows that the major part of the average cost is not based on the average variable cost and is held fixed in nature.

c. This graph shows the relation between the marginal and average profit, which n this case has the same trend of increasing and then decreasing, however the marginal profit is greater in value than the average profit.

d.

This graph shows the relation between the marginal cost and average variable cost, depicting the high average variable cost as compared to the marginal cost, and that the MC has a declining trend whereas the AVC has an increasing trend.

9

Output L K TLC TKC TC LAC LMC
10 1 0.7 0.5 7 3.5 0.35
20 1.2 0.8 0.6 16 9.6 0.48 0.61
30 2 1 1 30 30 1 2.04
40 3 1.5 1.5 60 90 2.25 6
50 4 2.2 2 110 220 4.4 13
60 5.2 3 2.6 180 468 7.8 24.8
70 6 4.2 3 294 882 12.6 41.4

a

b

10.

Q L Forecasted Q Difference
25 5 48.64 23.64
299 7 68.30 230.70
427 8 78.13 348.87
417 11 107.61 309.39
438 12 117.44 320.56
946 13 127.27 818.73
197 6 58.47 138.53
43 6 58.47 15.47
524 14 137.09 386.91
668 12 117.44 550.56
341 15 146.92 194.08
722 13 127.27 594.73
511 7 68.30 442.70
278 9 87.95 190.05
302 7 68.30 233.70
34 5 48.64 14.64
475 12 117.44 357.56
37 5 48.64 11.64
289 8 78.13 210.87
305 8 78.13 226.87
447 11 107.61 339.39
806 7 68.30 737.70

a                                                                     

There is a huge difference between the real and estimated Q                                               

b                                                                     

No the signs are inverse to the perceived values                                           

c                                                                     

Beta here is significant but alpha is not significant                                       

d                                                                     

At 14 units of labor it reaches its maximum potential                                               

e                                                                     

The Average Variable cost is  62.98              

f                                                                      

The Short-run Marginal cost is 215.02                       

g                                                                     

Law of Diminishing Returns set in after 14.25         

Level of Output 526 units

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