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Demand Estimation

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ECO 740

CASE EXERCISE
SOFT DRINK DEMAND
ESTIMATION

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PREPARED BY
GROUP

:NIK NORMIE EDAYU BT. HJ. NIK HIM

: BM 770 (evening track)

MATRIX NO. : 2011913361
SUBMITTED TO

: DR. AZLINA BT. HANIFF

Demand can be estimated with experimental data, time-series data, or cross-section data. Sara Lee Corporation generates experimental data in test stores where the effect of an NFL-licensed Carolina Panthers logo on Champion sweatshirt sales can be carefully examined. Demand forecasts usually rely on time-series data. In contrast, cross-section data is appear in Table 1.

Soft drink consumption in cans per capita per year is related to six-pack price, income per capita, and mean temperature across the 48 contiguous in the United States.

Table 1

Alabama
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montan
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon

Cans/Capita 6-Pack $
Income
/Yr
Price
$/Capita
200
2.19
150
1.99
237
1.93
135
2.59
121
2.29
118
2.49
217
1.99
242
2.29
295
1.89
85
2.39
114
2.35
184
2.19
104
2.21
143
2.17
230
2.05
269
1.97
111
2.19
217
2.11
114
2.29
108
2.25
108
2.31
248
1.98
203
1.94
77
2.31
97
2.28
166
2.19
177
2.27
143
2.31
157
2.17
111
2.43
330
1.89
63
2.33
165
2.21
184
2.19
68
2.25

Mean
Temp. °F
13
17
11
25
19
27
28
18
14
16
24
20
16
17
13
15
16
21
22
21
18
10
19
19
16
24
18
24
15
25
13
14
22
16
19

66
62
63
56
52
50
52
72
64
46
52
52
50
56
56
69
41
54
47
47
41
65
57
44
49
48
35
54
56
48
59
39
51
82
51

Pennsylvania
Rohde Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Total
Mean

121
138
237
95
236
222
100
64
270
77
144
97
102
7594
158.208333
3

2.31
2.23
1.93
2.34
2.19
2.08
2.37
2.36
2.04
2.19
2.11
2.38
2.31
105.72

20
20
12
13
13
17
16
16
16
20
15
19
19
861

2.2025

50
50
65
45
60
69
50
44
58
49
55
46
46
2573
53.604166
67

17.9375

Question 1
Estimate the demand for soft drink using a multiple regression program available on your computer.
Answer
QD = 514.267 – 242.971 Price + 1.224 Income – 2.931 Temp (4.120)

(0.804)

r2 =0.698

(-5.582)

SSE=38.261

SPSS result:
Coefficientsa
Unstandardized

Standardized

Coefficients

Coefficients

95% Confidence Interval for B

Std.
Model
1

B
(Constant)
Price

Error

Beta

t

514.267 113.332

Sig.

Lower Bound

Upper Bound

4.538

.000

285.862

742.672

-242.971

43.526

-.588

-5.582

.000

-330.692

-155.249

Income

1.224

1.523

.076

.804

.426

-1.844

4.293

Temp

2.931

.711

.402

4.120

.000

1.497

4.365

a. Dependent Variable: Can

EViews7 result:
Dependent Variable: CAN
Method: Least Squares
Date: 04/07/12 Time: 22:00
Sample: 1 48
Included observations: 48
Variable

Coefficient

Std. Error

t-Statistic

Prob.

C
PRICE
INCOME
TEMP

514.2669
-242.9708
1.224164
2.931228

113.3315
43.52628
1.522613
0.711458

4.537722
-5.582162
0.803989
4.120027

0.0000
0.0000
0.4257
0.0002

R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)

0.698024
0.677435
38.26108
64412.06
-240.9536
33.90231

Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat

158.2083
67.36719
10.20640
10.36233
10.26533
1.980543

0.000000

Question 2
Interpret the coefficients and calculate the price elasticity of soft drink demand. Mean P =105.72 / 48
= 2.2025
Mean Q = 7594 / 48
= 158.2083
dQ/dP = -242.97
Price elasticity ED = ( dQ/dP ) / (Mean P /Mean Q )
ED = (-242.97) / ( 2.2025 / 158.2083 )
ED = ( – 3.38 )
The price elasticity at the mean price and quantity across the states is in the elastic range, as expected. These are market-level price elasticity, so no firm behaviour is directly implied by this estimate. The elastic demand at the market level does imply elastic firm-level demand at comparable prices, comparable price sensitivity, and the smaller quantities facing each
firm.

Question 3
Omit price from the regression equation and observe the bias introduced into the parameter estimate for income.
QD = -56.614 -2.054Y + 4.695F

Coefficientsa
Unstandardized
Coefficients
Model
1

Standardized
Coefficients

B
(Constan
t)
Income

Temp

Std. Error

Beta

t

63.117

56.614
-2.054

-.897 .375

1.815

4.695

Sig.

-.128

.824

1.132

.264

.644 5.699 .000

a. Dependent Variable: Can

Question 4
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 neighbourhoods? Why or why not?

ANSWER
QD = 254.563 – 5.372Y
Coefficientsa
Unstandardized Coefficients
Model
1

B
(Constant)

Std. Error

254.563

2.232

Beta

t

41.091

-5.372

Standardized Coefficients

Income
a. Dependent Variable: Can

Sig.

6.195
-.334

.000

-2.407

.020

No, a marketing plan should not be designed specifically to introduce canned soft drink machines to low-income neighbourhoods.

Cite this Demand Estimation

Demand Estimation. (2016, Aug 15). Retrieved from https://graduateway.com/demand-estimation/

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