Demand Estimation for The San Francisco Bread CompanyConsider 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.E. Interpret each coefficient and its impact on the dependent variable.(See Below for Data) Table 1 - San Francisco Bread Company (30 Markets)Market Demand Price Competitor Advertising IncomeMarket (Q) (P) Price(Px) (Ad) (I)1 596,611 7.62 6.52 200,259 54,8802 596,453 7.29 5.01 204,559 51,7553 599,201 6.66 5.96 206,647 52,9554 572,258 8.01 5.30 207,025 54,3915 558,142 7.53 6.16 207,422 48,4916 627,973 6.51 7.56 216,224 51,2197 593,024 6.20 7.15 217,954 48,6858 565,004 7.28 6.97 220,139 47,2199 596,254 5.96 5.52 220,215 49,75510 652,880 6.42 6.27 220,728 54,93211 596,784 5.94 5.66 226,603 48,09212 657,468 6.47 7.68 228,620 54,92913 519,886 6.99 5.10 230,241 46,05714 612,941 7.72 5.38 232,777 55,23915 621,707 6.46 6.20 237,300 53,97616 597,215 7.31 7.43 238,756 49,57617 617,427 7.36 5.28 241,957 55,45418 572,320 6.19 6.12 251,317 48,48019 602,400 7.95 6.38 254,393 53,24920 575,004 6.34 5.67 255,699 49,69621 667,581 5.54 7.08 262,270 52,60022 569,880 7.89 5.10 275,588 50,47223 644,684 6.76 7.22 277,667 53,40924 605,468 6.39 5.21 277,816 52,66025 599,213 6.42 6.00 279,031 50,46426 610,735 6.82 6.97 279,934 49,52527 603,830 7.10 5.30 287,921 49,48928 617,803 7.77 6.96 289,358 49,37529 529,009 8.07 5.76 294,787 48,25430 573,211 6.91 5.96 296,246 46,017Mean 598,412 6.93 6.16 244,649 51,044

Question

Demand Estimation for The San Francisco Bread CompanyConsider 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.E. Interpret each coefficient and its impact on the dependent variable.(See Below for Data) Table 1 - San Francisco Bread Company (30 Markets)Market   Demand    Price    Competitor    Advertising    IncomeMarket        (Q)          (P)        Price(Px)            (Ad)              (I)1              596,611     7.62         6.52             200,259        54,8802              596,453     7.29         5.01             204,559        51,7553              599,201     6.66         5.96             206,647        52,9554              572,258     8.01         5.30             207,025        54,3915              558,142     7.53         6.16             207,422        48,4916              627,973     6.51         7.56             216,224        51,2197              593,024     6.20         7.15             217,954        48,6858              565,004     7.28         6.97             220,139        47,2199              596,254     5.96         5.52             220,215        49,75510            652,880     6.42         6.27             220,728        54,93211            596,784     5.94         5.66             226,603        48,09212            657,468     6.47         7.68             228,620        54,92913            519,886     6.99         5.10             230,241        46,05714            612,941     7.72         5.38             232,777        55,23915            621,707     6.46         6.20             237,300        53,97616            597,215     7.31         7.43             238,756        49,57617            617,427     7.36         5.28             241,957        55,45418            572,320     6.19         6.12             251,317        48,48019            602,400     7.95         6.38             254,393        53,24920            575,004     6.34         5.67             255,699        49,69621            667,581     5.54         7.08             262,270        52,60022            569,880     7.89         5.10             275,588        50,47223            644,684     6.76         7.22             277,667        53,40924            605,468     6.39         5.21             277,816        52,66025            599,213     6.42         6.00             279,031        50,46426            610,735     6.82         6.97             279,934        49,52527            603,830     7.10         5.30             287,921        49,48928            617,803     7.77         6.96             289,358        49,37529            529,009     8.07         5.76             294,787        48,25430            573,211     6.91         5.96             296,246        46,017Mean       598,412     6.93         6.16             244,649        51,044

Accepted Answer

Multiple linear regression model:
A multiple linear regression model is given as y = b0 + b1x1 +…