Demand Estimation for The San Francisco Bread Company Consider the hypothetical example of The San Francisco Bread Company, a San Francisco-based chain of bakery/cafes. San Francisco Bread Company has...




Demand Estimation for The San Francisco Bread Company


Consider the hypothetical example of The San Francisco Bread Company, a San Francisco-based chain of bakery/cafes.  San Francisco Bread Company has initiated an empirical estimation of customer traffic at 30 regional locations to help the firm formulate pricing and promotional plans for the coming year.  Annual operating data for the 30 outlets appear in the attached Table 1.


The following regression equation was fit to these data:



                    Qi
= b0
+ b1Pi
+ b2Pxi
+ b3Adi
+ b4Ii
+ uit.



Where:            Q is the number of meals served,



                        P is the average price per meal (customer ticket amount, in dollars),



                        Px
is the average price charged by competitors (in dollars),



                        Ad is the local advertising budget for each outlet (in dollars),



                        I is the average income per household in each outlet’s service area,



                        ui
is a residual (or disturbance) term.


The subscript indicates the regional market (i = 1,…, 30) from which the observation was taken.  Least squares estimation of the regression equation on the basis of the 30 data cross sectional observations resulted in the estimated regression coefficients and other statistics as shown in Table 2.


C. What are expected (average) unit sales and sales revenue in a typical market?




(See Below for Data)



Table 1 - San Francisco Bread Company (30 Markets)



Market   Demand    Price    Competitor    Advertising    Income



Market        (Q)          (P)        Price(Px)            (Ad)              (I)


1              596,611     7.62         6.52             200,259        54,880


2              596,453     7.29         5.01             204,559        51,755


3              599,201     6.66         5.96             206,647        52,955


4              572,258     8.01         5.30             207,025        54,391


5              558,142     7.53         6.16             207,422        48,491


6              627,973     6.51         7.56             216,224        51,219


7              593,024     6.20         7.15             217,954        48,685


8              565,004     7.28         6.97             220,139        47,219


9              596,254     5.96         5.52             220,215        49,755


10            652,880     6.42         6.27             220,728        54,932


11            596,784     5.94         5.66             226,603        48,092


12            657,468     6.47         7.68             228,620        54,929


13            519,886     6.99         5.10             230,241        46,057


14            612,941     7.72         5.38             232,777        55,239


15            621,707     6.46         6.20             237,300        53,976


16            597,215     7.31         7.43             238,756        49,576


17            617,427     7.36         5.28             241,957        55,454


18            572,320     6.19         6.12             251,317        48,480


19            602,400     7.95         6.38             254,393        53,249


20            575,004     6.34         5.67             255,699        49,696


21            667,581     5.54         7.08             262,270        52,600


22            569,880     7.89         5.10             275,588        50,472


23            644,684     6.76         7.22             277,667        53,409


24            605,468     6.39         5.21             277,816        52,660


25            599,213     6.42         6.00             279,031        50,464


26            610,735     6.82         6.97             279,934        49,525


27            603,830     7.10         5.30             287,921        49,489


28            617,803     7.77         6.96             289,358        49,375


29            529,009     8.07         5.76             294,787        48,254


30            573,211     6.91         5.96             296,246        46,017



Mean       598,412     6.93         6.16             244,649        51,044


SUMMARY OUTPUT<br>Regression Statistics<br>Multiple R<br>R Square<br>Adjusted R Square<br>0.91280128<br>0.83320617<br>0.80651916<br>Standard Error<br>14865.8981<br>Observations<br>30<br>ANOVA<br>df<br>MS<br>F<br>Significance F<br>Regression<br>4<br>27599092617 6.9E+09 31.22141<br>2.16137E-09<br>Residual<br>25<br>5524873170 2.21E+08<br>Total<br>29<br>33123965787<br>Coefficients<br>Standard Error<br>t Stat<br>P-value<br>Lower 95%<br>Upper 95% Lower 95.0% Upper 95.0%<br>272840.0973<br>Intercept<br>X Variable 1<br>X Variable 2<br>X Variable 3<br>X Variable 4<br>128740.913<br>69966.78194 1.840029 0.077667<br>-15358.27043<br>272840.1 -15358.27043<br>-19864.901<br>15484.5544<br>4102.111195<br>-4.8426<br>5.6E-05<br>-28313.35155 -11416.451 -28313.35155 -11416.45108<br>3459.193122 4.476349 0.000145<br>8360.217835 22608.891<br>8360.217835<br>22608.89104<br>0.26006502<br>0.093982856 2.767154 0.010486<br>0.066503838<br>0.4536262 0.066503838<br>0.453626199<br>8.78206805<br>1.016513087 8.639405 5.62E-09<br>6.688521625<br>10.875614<br>6.688521625<br>10.87561448<br>

Extracted text: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.91280128 0.83320617 0.80651916 Standard Error 14865.8981 Observations 30 ANOVA df MS F Significance F Regression 4 27599092617 6.9E+09 31.22141 2.16137E-09 Residual 25 5524873170 2.21E+08 Total 29 33123965787 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 272840.0973 Intercept X Variable 1 X Variable 2 X Variable 3 X Variable 4 128740.913 69966.78194 1.840029 0.077667 -15358.27043 272840.1 -15358.27043 -19864.901 15484.5544 4102.111195 -4.8426 5.6E-05 -28313.35155 -11416.451 -28313.35155 -11416.45108 3459.193122 4.476349 0.000145 8360.217835 22608.891 8360.217835 22608.89104 0.26006502 0.093982856 2.767154 0.010486 0.066503838 0.4536262 0.066503838 0.453626199 8.78206805 1.016513087 8.639405 5.62E-09 6.688521625 10.875614 6.688521625 10.87561448
Jun 09, 2022
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