Micro Economics: Demand Analysis Project.
Using regression analysis, the attached data and a linear functional form, estimate the
demand for PIZZA .
Include the computation and explanation of the following in your report:
1.
2.
3.
4.
5.
6.
7.
8.
9.
Write your regression equation i.e. demand function, enter information into
excel as per instructions attached and compute the regression equation. (4pts)
Using your regression output, write your estimated coefficients into the
demand function. (5pts)
Interpret all the coefficients. (20pts)
Using the average values for the independent variables and your estimated
demand function, compute the demand for PIZZA in a typical market. (6pts)
Define and interpret the standard error of the estimate AND estimate the
range within which actual demand for pizza is expected to fall with a 95%
confidence level. (10pts)
Define the coefficient of determination (R-squared). What percentage of
demand variation is explained by this model? (5pts)
Are the coefficient’s statistically significant? i.e. does each of the independent
variable have a significant effect on the dependent variable? Explain using tstats. (8pts)
Calculate the point price, point advertising and point income elasticity of
demand for PIZZA. (12pts)
As a Business Analyst, use the analysis you have done to advise your
Manager on
a. Whether a decrease in the price of PIZZA would increase or decrease
revenues.
b. The impact of increasing advertising dollars on total revenues.
Explain your answer, using your elasticity estimates (and or regression )
including how much revenue would be generated (or lost) by a decrease ( e.g.
$1) in price. (20pts)
For question 9 type a business memo to your Manager, using your regression and
elasticity results to support your decision.
This is not a group project. Your final report must be typed. Please submit regression
results (output) ( 10points) and show your formulas and calculations.
PRICE OF
QUANITITY CHECKERS
DEMANDED PIZZA
3090
3059
3040
3039
2942
2934
2875
2870
2849
2842
2934
2821
2819
2791
2729
2721
2659
2633
2623
2586
2557
2517
2503
2502
AVERAGES
7.5
7.5
7.5
7.5
8.5
8.5
8.5
8.65
8.65
8.65
8.65
8.65
8.65
9.75
9.75
9.75
9.75
9.99
9.99
9.99
9.99
10.25
10.25
10.25
9.05
INCOME
………..
28444
28264
28259
27950
27350
27350
26850
26450
26350
26350
26200
26120
26120
26120
25970
25970
25950
25950
25750
25750
25700
25600
25500
????
ADVERTISING
EXPIDENTURE
10.55
10.45
10.35
10.3
10.3
10.25
10.25
10.25
10.25
10.25
10.25
10.2
10.15
10.1
10.1
10.1
10
10
10
10
9.75
9.75
9.65
9.6
10.12
PRICE OF
BIG MAC
1.85
1.75
1.75
1.5
1.35
1.25
1.25
1.25
1.2
1.2
1.15
1.15
1.15
1.1
1.05
1.05
0.95
0.95
0.85
0.55
0.55
0.55
0.55
0.16
1.09
PROCEDURE : 1. DATA ENTRY - OPEN EXCEL WORKSHEET.
Begin on Cell A1
Input Headings
For example in cell A1 enter Qs for quantity demanded – PIZZA
Cell BI input PC for price of checker’s pizza, cell C1 input PBMAC for price of
big mac, Cell D1 input A for advertising and cell E1 input I for income
Input data
input data beginning with Qs.
From cell A2…. A13 enter Qs data
From cell B2….B13 input Ps data
From cell C2…. C13 enter Pts data
From cell D2….D13 input Advertising data
From cell E2….E13 input Income data
2. Save your data. You are now ready to run your regression
Click on Tools, then click on data analysis
If data analysis is not available in the tools menu click on add-ins
Select Analysis ToolPak and click OK
Go back to the Tools menu and Click on Data Analysis
Double Click on Regression
Input "Y" range: Dependent variable: A1: A:13
Input "X" range : Independent variables range: B1:E13
Click on Labels and input "output" range A19:I50
Click Ok and you should get your results.
You can also use any statistical software such as SPSS, Statplus
etc.
Statplus can be downloaded for free.
If using statplus:
Input data as described in (1) above.
Click on regression
Click on multiple linear regression.
To Input dependent variable
Click Qs A on left column and click the arrow.
To input independent variable: click on all the independent variables
including the headings and click the arrow.
Click ok and save results.
PRICE OF
QUANITITY
CHECKERS
DEMANDED
PIZZA
3090
3059
3040
3039
2942
2934
2875
2870
2849
2842
2934
2821
2819
2791
2729
2721
2659
2633
2623
2586
2557
2517
2503
2502
AVERAGES
7,5
INCOME
ADVERTISIN
G
EXPIDENTU
RE
28100
10,55
7,5
28444
7,5
28264
7,5
28259
8,5
27950
8,5
27350
8,5
27350
8,65
26850
8,65
26450
8,65
26350
8,65
26350
8,65
26200
8,65
26120
9,75
26120
9,75
26120
9,75
25970
9,75
25970
9,99
25950
9,99
25950
9,99
25750
9,99
25750
10,25
25700
10,25
25600
10,25
25500
9,05 26600,7083
10,45
10,35
10,3
10,3
10,25
10,25
10,25
10,25
10,25
10,25
10,2
10,15
10,1
10,1
10,1
10
10
10
10
9,75
9,75
9,65
9,6
10,12
PRICE OF
BIG MAC
1,85
1,75
1,75
1,5
1,35
1,25
1,25
1,25
1,2
1,2
1,15
1,15
1,15
1,1
1,05
1,05
0,95
0,95
0,85
0,55
0,55
0,55
0,55
0,16
1,09
Linear Regression
Regression Statistics
R
0,98632
R-Squared
0,97282
Adjusted R-Squared
0,9671
S
33,55076
MSE
1.125,65
RMSE
33,55076
MAPE
0,83315
DW
1,80203
PRESS
36.845,39
PRESS RMSE
39,18194
Predicted R-Squared
0,95318
N
24
Quantity Demand = 57.69481 - 83.40048 * Price of Ckckers Pizza + 0.01893 * Income +
ANOVA
d.f.
Regression
Residual
Total
SS
MS
4 765.565,54 191.391,39
19
21.387,42
1.125,65
23 786.952,96
Coefficient Standard ErrorLCL
Intercept
57,69481
1.331,52
-2.729,21
Price of Ckckers Pizza
-83,40048
22,48591 -130,46403
Income
0,01893
0,01908
-0,021
Adevertising Expidenture
289,27728 100,94079
78,00578
Price of Big Mac
50,52224
68,37048 -92,57881
T (5%)
2,09302
LCL - Lower limit of the 95% confidence interval
UCL - Upper limit of the 95% confidence interval
** - Requires Pro version, please upgrade.
Residuals
Observation
1
2
3
4
Quantity Demand
Predicted Y Residual
3.090
3.109,56
-19,5557
3.059
3.082,09 -23,08878
3.040
3.049,75
-9,75307
3.039
3.022,56
16,43602
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Minimum
Maximum
Mean
2.942
2.934
2.875
2.870
2.849
2.842
2.934
2.821
2.819
2.791
2.729
2.721
2.659
2.633
2.623
2.586
2.557
2.517
2.503
2.502
2.502
3.090
2.788,96
2.925,73
2.894,86
2.894,86
2.872,88
2.862,78
2.860,89
2.858,36
2.841,06
2.825,08
2.716,35
2.713,82
2.710,98
2.677,00
2.656,61
2.651,56
2.632,61
2.560,29
2.537,66
2.506,84
2.470,78
2.470,78
3.109,56
2.788,96
16,26519
39,14121
-19,85879
-2,88212
-13,78273
-18,8894
75,63671
-20,05945
-6,08093
74,64958
15,17569
10,01567
-18,00438
-23,6096
-28,55738
-46,61406
-3,29474
-20,66396
-3,84291
31,21795
-46,61406
75,63671
0
ers Pizza + 0.01893 * Income + 289.27728 * Adevertising Expidenture + 50.52224 * Price of Big Mac
F
p-value
170,0269
UCL
2.844,60
-36,33692
0,05887
500,54877
193,62329
0
t Stat
0,04333
-3,70901
0,99233
2,86581
0,73895
p-value
0,96589
0,00149
0,33351
0,00989
0,46897
H0 (5%)
accepted
rejected
accepted
rejected
accepted
VIF
**
**
**
**
**
TOL
**
**
**
**
**
Standardized Studentized
Deleted t
Leverage
Cook's D
DFIT
PRESS
-0,58287
-0,64827
-0,63808
0,1916
0,01992
-0,31064 -24,19057
-0,68817
-0,77385
-0,76537
0,20917
0,03168
-0,39362
-29,1955
-0,2907
-0,35353
-0,34524
0,32387
0,01197
-0,23894 -14,42486
0,48989
0,5737
0,5633
0,27085
0,02445
0,34332
22,5414
0,48479
1,16663
-0,5919
-0,0859
-0,4108
-0,56301
2,2544
-0,59788
-0,18125
2,22497
0,45232
0,29852
-0,53663
-0,7037
-0,85117
-1,38936
-0,0982
-0,6159
-0,11454
0,93047
-1,38936
2,2544
0
0,58786
1,23479
-0,62649
-0,08873
-0,44099
-0,61431
2,49049
-0,67131
-0,21223
2,47145
0,49179
0,32514
-0,5674
-0,77162
-0,9098
-1,83712
-0,10795
-0,67147
-0,14225
1,25119
-1,83712
2,49049
-0,00045
0,57746
1,25319
-0,61617
-0,08638
-0,43144
-0,60395
2,95365
-0,66129
-0,20681
2,92031
0,48175
0,31735
-0,55701
-0,76309
-0,90548
-1,9718
-0,1051
-0,66146
-0,13853
1,27131
-1,9718
2,95365
0,03671
0,31992
0,10736
0,10736
0,06269
0,13221
0,16004
0,18061
0,20679
0,27066
0,18951
0,15408
0,15701
0,10552
0,16831
0,12473
0,42805
0,17242
0,15867
0,35163
0,44695
0,06269
0,44695
0,20833
0,03251
0,03667
0,00944
0,00011
0,00593
0,01438
0,27343
0,0235
0,00334
0,28564
0,00881
0,00394
0,0076
0,0241
0,02359
0,50518
0,00049
0,01701
0,00219
0,25303
0,00011
0,50518
0,06745
0,39606
0,4346
-0,21369
-0,02234
-0,1684
-0,26362
1,38671
-0,33765
-0,12599
1,41213
0,2056
0,13696
-0,19131
-0,34328
-0,34181
-1,70583
-0,04797
-0,28725
-0,10202
1,14289
-1,70583
1,41213
0,01516
23,91663
43,84861
-22,24716
-3,07489
-15,88248
-22,48837
92,30852
-25,28898
-8,33755
92,10445
17,93985
11,88112
-20,12834
-28,3874
-32,62693
-81,50077
-3,98118
-24,56101
-5,92705
56,44738
-81,50077
92,30852
-0,05229

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