Week isales iprom walmart Ifeat holiday ipromwm

1 13.2827 -.1187 0 -.1386 0 .00 2 13.6388 .0725 0 -.1773 0 .00 3 13.6670 -.0471 0 .1093 0 .00 4 13.5505 .0563 0 -.0468 0 .00 5 13.5637 .0119 0 .0579 0 .00 6 13.4952 .0654 0 .0853 0 .00 7 13.4610 .1973 0 .0250 0 .00 8 13.8423 .0536 0 .0786 0 .00 9 13.5353 .0790 0 -.0060 0 .00 10 13.0080 -.2209 0 -.1243 0 .00 11 13.3996 .0485 0 .0021 0 .00 12 13.2502 -.0284 0 -.0223 0 .00 13 13.3038 -.0445 0 -.0809 0 .00 14 13.5000 .0853 0 .0506 0 .00 15 13.2240 -.0769 0 .1075 0 .00 16 13.3085 .1623 0 -.0062 0 .00 17 13.2812 -.0128 0 .1290 0 .00 18 13.4572 -.0123 0 .0792 0 .00 19 13.4356 .0572 0 .0448 0 .00 20 13.4846 -.0327 0 -.0151 0 .00 21 13.6677 -.0080 0 .0326 0 .00 22 13.3871 .0612 0 .0483 0 .00 23 13.2940 -.0602 0 .0500 0 .00 24 13.1536 .0480 0 -.0017 0 .00 25 13.6671 .0211 0 .0756 0 .00 26 13.4161 -.0102 0 .0777 0 .00 27 13.5043 -.0504 0 -.0051 0 .00 28 14.0010 .0632 0 .1018 0 .00 29 13.6910 .0431 0 .1056 0 .00 30 14.0524 .2159 0 .0468 1 .00 31 13.8706 .1144 0 -.1158 1 .00 32 13.3947 .0371 0 .0806 0 .00 33 13.5293 .0876 0 -.2136 0 .00 34 13.1509 .0440 0 -.1034 0 .00 35 13.9120 .1115 0 -.0611 1 .00 36 13.4902 -.0939 0 -.1350 1 .00 37 13.8823 .1489 0 -.1135 0 .00 38 13.5749 -.0007 0 .0356 0 .00 39 13.7016 -.0290 0 .0594 0 .00 40 14.0224 .0325 0 .1182 0 .00 41 13.2727 -.1325 0 .0551 0 .00 42 13.2072 .0281 0 -.1647 0 .00 43 13.3818 .0611 0 -.1799 0 .00 44 13.1719 -.0665 0 .1091 0 .00 45 13.3766 .0172 0 -.0334 0 .00 46 13.4892 .0225 0 -.1467 0 .00 47 13.2319 -.0465 0 -.0561 0 .00 48 13.8784 .0940 0 .0216 0 .00 49 13.4930 .0352 0 .2063 0 .00 50 13.2015 -.1297 0 -.0391 0 .00 51 13.0491 .2239 1 .0258 0 .22 52 13.4614 -.0364 1 .1689 0 -.04 53 13.2385 -.0975 1 .1043 0 -.10 54 13.2147 .0125 1 .0175 0 .01 55 13.1037 .0121 1 -.0394 0 .01 56 12.7894 -.1064 1 -.0631 0 -.11 57 13.2486 .0917 1 -.0440 0 .09 58 13.2199 .0366 1 -.0351 0 .04 59 13.1487 .2828 1 .0787 0 .28 60 13.1431 .0406 1 -.1259 0 .04 61 12.8728 -.0212 1 -.0397 0 -.02 62 13.2321 -.0450 1 -.1129 0 -.05 63 12.8661 .1448 1 .0537 0 .14 64 13.4802 .0520 1 .1294 0 .05 65 13.3462 .2328 1 -.0108 0 .23 66 13.2813 .1729 1 .0740 0 .17 67 13.3957 -.0111 1 -.0566 0 -.01 68 13.0300 -.1537 1 -.0031 0 -.15 69 13.1323 .0548 1 -.0744 0 .05 70 13.3574 -.0662 1 -.1534 0 -.07 71 13.8422 .0829 1 .2325 0 .08 72 12.6094 -.1506 1 -.1868 0 -.15 73 13.4238 -.0485 1 -.0237 0 -.05 74 13.1239 -.0928 1 .0323 0 -.09 75 13.0199 -.0836 1 .1442 0 -.08 76 13.3223 .1291 1 -.2064 0 .13 77 13.0664 -.0728 1 .2065 0 -.07 78 13.0106 .0029 1 .0905 0 .00 79 13.0213 .1044 1 .0583 0 .10 80 12.9042 .0749 1 -.0859 0 .07 81 12.8941 -.0298 1 -.0052 0 -.03 82 13.3544 .0671 1 .0428 1 .07 83 13.3226 -.1726 1 .0930 1 -.17 84 13.3559 -.1710 1 .1019 0 -.17 85 12.8475 -.1856 1 -.1171 0 -.19 86 12.9356 -.0578 1 -.2476 0 -.06 87 13.3768 .0233 1 -.0533 1 .02 88 13.0538 -.2209 1 .0147 1 -.22 89 12.9945 -.0881 1 -.1446 0 -.09 90 13.1610 -.0119 1 -.0496 0 -.01 91 13.1921 -.0803 1 .0684 0 -.08 92 12.8131 .0164 1 .0037 0 .02 93 13.4498 -.0467 1 .1999 0 -.05 94 13.7590 .1370 1 .0299 0 .14 95 12.7540 -.2303 1 -.1861 0 -.23 96 13.2477 -.0300 1 .0967 0 -.03 97 13.0747 -.0634 1 .0524 0 -.06 98 13.4461 -.0907 1 .0107 0 -.09 99 13.3315 .0216 1 .0681 0 .02 100 13.0114 .0532 1 .0581 0 .05

You have been hired as a consultant for a major local grocery store. Store management is worried since Wal-Mart has entered the market by opening a "Wal-Mart Super-center" only 3 miles away from the local store. Management is interested in analyzing the impact on store sales of the Wal-Mart entry and whether or not a new strategy is required.

For analysis, management has given you access to one hundred weeks of sales data for the local store covering the period both pre- and post-entry of Wal-Mart (see walmart.xls or walmart.sav).

(a) (4 points) You start by estimating a multiple linear regression model using log(sales)=log weekly sales as the dependent variable. As independent variables you use log(promotion index)=the log of an index of weekly promotional activity in the store (the bigger the promotional index is in a given week the more products are on promotion in the store in that week), and Walmart, a Wal-mart dummy equal to one in the weeks after the Wal-mart store has opened (and, of course, zero in the weeks before the Wal-mart store opened).

Interpret the estimates of this regression. What is the effect of Wal-mart entry?

(b) (4 points) Which independent variables are significant in explaining the variation in sales? In other words, which independent variables are likely to have a non-zero impact on the dependent variable?

(c) (4 points) The local store also engages in feature advertising by mailing ads to households. Feature Advertising Index gives the feature advertising activity in a given week. You add the log of this variable to the previous regression. In addition to this, you also add a Holiday Dummy equal to one if the corresponding week covers a major holiday. Add these two variables to the regression and re-estimate the model

Interpret the two newly estimated coefficients.

(d) (4 points) Estimate the regression. Is the effect of promotions on store sales higher or lower after Wal-Mart enters?