In: Economics
The table below shows a sample of 100 companies firms that were targets of tender offers during the period 1975–1985. A tender offer is an offer to purchase some or all of shareholders' shares in a corporation. The price offered is usually at a premium to the market price. Conduct an analysis where the response variable represents the number of bids (BIDS) received preceding the takeover of the firm. The explanatory variables include the bid premium (PREMIUM) and firm size (SIZE). In general, it is reasonable to expect that a high initial bid premium, defined as the percentage excess of the firm's stock price, would discourage subsequent bids. Additionally, while tender offers for large corporations are likely to receive more media exposure and thus attract the attention of opportunistic bidders, the size of the firm also will act as deterrence mechanism given the wealth constraint that will impose to potential bidders. FIRM BIDS PREMIUM SIZE 1 3 1.1905 0.7668 2 1 1.036 0.1625 3 2 1.4034 0.1205 4 2 1.5045 0.0723 5 2 1.3807 0.1891 6 4 1.4001 0.1542 7 3 1.1817 0.4604 8 2 1.3226 0.2768 9 2 1.6506 0.2289 10 1 1.3561 0.914 11 2 1.3058 0.2308 12 3 1.4723 0.1073 13 3 1.387 0.037 14 2 2.0664 0.3081 15 3 1.3336 0.4237 16 2 1.6146 0.1139 17 4 1.3494 0.1801 18 3 1.3222 0.5516 19 3 1.4022 0.2236 20 2 1.5364 0.081 21 4 1.5105 0.1355 22 2 1.5306 0.1119 23 3 1.3195 0.7498 24 5 0.9535 1.2994 25 2 1.5732 0.0525 26 2 1.4456 0.0353 27 2 1.4194 0.1194 28 2 1.4389 0.1046 29 5 1.3353 0.2076 30 2 1.209 0.2216 31 3 1.2171 0.0307 32 2 1.6733 0.4245 33 5 1.588 0.0767 34 2 1.3654 2.966 35 2 1.6797 1.7649 36 11 1.3032 11.0363 37 2 1.3944 0.0241 38 2 1.4286 2.0104 39 2 1.3896 0.0611 40 2 1.3966 0.1071 41 2 1.7451 0.293 42 3 1.7553 0.1202 43 2 1.2465 0.2157 44 3 1.4918 0.9539 45 2 1.8904 0.3208 46 3 1.4309 5.0431 47 2 1.3044 0.0502 48 2 1.2779 0.0835 49 2 1.3733 0.4404 50 4 1.3424 0.6808 51 2 1.3199 0.6081 52 3 1.9045 0.0679 53 5 1.3742 6.0485 54 2 1.7543 0.2295 55 4 1.3519 0.0764 56 2 1.4588 1.1209 57 2 1.3055 0.1044 58 4 1.6021 3.2185 59 3 1.0456 0.0566 60 3 1.4197 0.0471 61 1 1.356 0.0496 62 4 1.2964 0.121 63 1 1.4027 3.7112 64 2 1.3132 0.5241 65 7 1.2941 0.4077 66 3 1.3629 0.163 67 3 1.2107 0.2297 68 2 1.4341 2.8329 69 3 1.4213 0.1333 70 2 1.5087 0.1904 71 2 1.3341 0.0184 72 6 1.1603 2.1932 73 4 1.2755 0.2664 74 7 1.1437 0.0909 75 2 1.127 2.4135 76 3 1.2012 0.163 77 2 1.404 0.0894 78 2 1.3932 0.5346 79 3 1.2985 0.123 80 4 1.2945 9.9245 81 2 1.2617 0.1888 82 2 1.0586 0.5253 83 3 1.2131 20.964 84 2 1.2082 0.0698 85 2 1.6332 22.169 86 4 1.1741 0.086 87 4 1.2813 0.6891 88 3 1.1309 0.2155 89 2 1.2064 0.3128 90 3 0.9427 0.9494 91 2 1.3971 0.1288 92 2 1.4932 0.0634 93 2 1.3207 1.5622 94 2 1.154 0.0177 95 1 1.3918 0.2212 96 2 1.3145 2.8801 97 1 1.5846 0.3397 98 2 1.3849 0.0221 99 2 1.0385 0.88 100 2 1.2279 0.0909 Estimate the following linear model: BIDSi=beta0+beta1PREMIUMi+beta2SIZEi+ui Question 1 The estimated linear model is: BIDSi=5.09−1.04×PREMIUMi+2.76×SIZEi BIDSi=3.01−1.13×PREMIUMi+1.10×SIZEi BIDSi=2.21−1.35×PREMIUMi+0.43×SIZEi BIDSi=4.53−1.38×PREMIUMi+0.09×SIZEi BIDSi=1.56−1.91×PREMIUMi+2.14×SIZEi
On running the OLS regression over the given 100 observations in excel such that BIDS is regressed on PREMIUM and SIZE, the result is:
SUMMARY OUTPUT | ||||||||
Regression Statistics | ||||||||
Multiple R | 0.280921365 | |||||||
R Square | 0.078916813 | |||||||
Adjusted R Square | 0.059925407 | |||||||
Standard Error | 1.382358587 | |||||||
Observations | 100 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 2 | 15.88121951 | 7.940609754 | 4.15539606 | 0.018556431 | |||
Residual | 97 | 185.3587805 | 1.910915263 | |||||
Total | 99 | 201.24 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 99.0% | Upper 99.0% | |
Intercept | 4.53 | 0.995910608 | 4.544401763 | 1.58878E-05 | 2.549211048 | 6.502424796 | 1.909094894 | 7.142540949 |
PREMIUM | -1.38 | 0.716855334 | -1.923144771 | 0.057394592 | -2.80137599 | 0.044142815 | -3.262130876 | 0.504897701 |
SIZE | 0.09 | 0.040891084 | 2.1555379 | 0.03359396 | 0.006984799 | 0.169299765 | -0.019297724 | 0.195582288 |
Thus, it is observed that the regression equation is:
BIDSi=4.53−1.38×PREMIUMi+0.09×SIZEi
Thus, the correct answer is: BIDSi=4.53−1.38×PREMIUMi+0.09×SIZEi