Variables in Wooldridge's data set (description):
Cross-sectional data set from Wooldridge
1. return % change stock price, 90-94
2. dkr debt/capital, 1990
3. eps earnings per share, 1990
4. netinc net income, 1990 (millions $)
5. salary CEO salary, 1990 (thousands $)
Dataset:
return	dkr	eps	netinc	salary
-20.84211	4	48.1	1144	1090
-9.138381	27.3	-85.3	35	1923
86.21795	36.8	-44.1	127	1012
131.8367	46.4	192.4	367	579
-8.189655	36.2	-60.4	214	600
-26.00733	18.7	-79.8	118	735
52.27273	34.4	39	175	994
-36.10315	57.8	-62.8	1692	1227
3.508772	33.4	-16.2	157	913
28.61953	33.4	-19.1	315	733
-21.62162	16.7	12.8	407	1247
6.574394	18.3	-34.8	165	925
100.6061	27.6	-8.6	288	602
-5.21327	27.3	9.5	147	1006
-27.6	35	19.3	177	593
-33.33333	12.3	59.5	1845	3142
-43.35938	53.9	12.8	1013	1893
32.14286	33.2	9	829	1740
-6.603774	19.9	5	475	1558
-7.03125	31.4	2.7	230	1095
2.564103	14.5	2.6	335	1235
3.361345	0	16	63	569
-5.779335	32.9	-42.6	1537	930
-65	36.1	9.1	228	940
-9.666667	6.6	20.6	174	926
64.38849	20.4	-3.4	191	756
-20.93023	41.8	13.4	4237	2969
50.53078	40.2	43.5	1131	3836
5.109489	10.9	13.9	66	477
104.5685	69.9	4.3	282	2600
-27.22513	68.1	-54.4	151	1182
-35.07194	25.7	8.6	229	930
-52.02206	4.2	15.7	939	1165
-58.97436	26.7	28.8	24	357
-41.62791	34.1	13.8	1207	1704
-47.88462	18.2	15.7	127	1336
-20.12987	10.7	-42.1	217	1345
63.48315	3.8	-1.8	290	578
-0.6423983	15.2	5.8	522	932
-12.10191	1.5	14.2	64	518
59.9359	12.7	4.6	613	1769
-10.81081	15.5	4.2	474	1942
-24.9467	28.9	5	27	1416
-7.925408	0	7.9	113	729
-46.75325	22.9	-30.5	147	1081
-18.7056	40.1	20.8	138	1123
-17.57576	33.3	-5.7	112	1048
43.54166	2.8	11.9	156	773
-8.333333	26.5	0.8	114	763
-37.31343	13.8	6.6	204	1191
6.918239	51.3	-2.5	208	727
16.10942	46.6	-65.1	317	947
9.405941	17.9	266.6	1383	3667
-58.92857	24.5	17.6	824	11338
4.651163	19	-61.6	211	1017
-8.709826	28.7	-26.3	415	1434
-30.52326	21.7	17.9	290	918
-36.57143	18	6.7	76	780
-2.506964	29.3	11.9	178	842
-33.0091	3.6	6.9	1305	1275
-5.084746	15.4	29.8	103	1064
-21.76871	5.5	17.2	130	725
-8.641975	35.5	-17.5	1525	2262
-34.05904	23.8	-49.9	1349	1359
21.5	13.5	3	3940	1550
34.42361	16.3	-7.7	1724	1872
-29.66361	22.3	-89.3	8	488
1.698514	25.6	-49.9	1349	1938
-8.403361	51.3	-21.1	337	1186
-15.13158	44.9	27.4	249	1300
-9.6	44.3	18.1	540	1338
14.95327	26.3	-31.2	115	4206
3.125	1	19.9	122	832
-18.76641	17.8	16.7	474	1147
6.932773	12	-16.4	395	1278
-30.08048	23.7	-8.9	879	1249
-8.704062	35.1	-10.9	361	2146
34.62783	14.6	-11.2	265	574
-37.44395	33.7	19.3	233	1814
10.6383	0	6.8	475	2193
19.38775	6.5	13.9	216	778
-50.31446	4	11.1	399	2332
111.3757	2.1	-13.1	739	1366
-21.91235	20.1	-22.9	4150	2011
-29.74138	0	60.9	317	1162
-44.75806	14.9	81.3	76	267
72.92577	45.9	-62.4	220	1190
-22.51462	8.1	90.2	186	1101
2.544529	9.1	23.9	517	1494
47.42268	61.9	-22.4	460	1500
33.40708	27.4	-11.7	743	1444
32.31292	36.1	-29.3	157	549
35.7466	50.6	-68.7	206	647
-13.63636	32.7	-5.8	169	552
40.17857	18.3	17.4	147	806
52.4173	50.9	10.6	341	783
-11.74377	20.2	12.6	1593	1439
-44.82143	0	-68	21	740
-84.8881	30.6	15.6	502	1033
-70.2957	21.1	16.2	327	1356
-6.766917	29.8	-61.3	123	537
22.41379	27.4	-0.4	387	1300
17.84141	35.4	-88.2	23	1030
22.04969	1.8	20.2	185	1188
6.476399	11.9	4.5	184	424
52.77778	46.3	88.5	265	1283
5.483029	32.2	-50.1	90	799
-47.74775	13.9	17.4	220	694
-20.96154	8.9	10.3	152	598
25.59727	44.8	45.4	152	1587
-48.02868	32.2	20.1	379	1836
-30.81232	2.1	6.7	388	1212
12.75168	34.9	-22.5	101	300
-38.65979	28.8	-11.7	738	997
-6.684492	12.2	13.2	175	917
-42.43903	25	3.2	226	767
31.69399	46.2	-15.1	128	581
14.28571	4.1	5.2	205	565
-10.46512	0.2	10.9	125	722
-4.635762	2.4	10.4	76	439
7.97546	79.5	24.3	130	780
-67.5	31.8	20.9	667	1571
-8.091287	6	-30.4	70	526
-22.50804	38.3	11.6	185	752
-40.625	27.9	7.5	1299	1296
-55.2809	34.1	-13.8	1134	1289
2.51938	47.7	19.4	280	1264
-43.42432	30	2.1	1156	960
-36.79061	27.5	2.5	1131	1380
-52.10356	2.2	27.5	191	1222
19.4	2.8	42.3	267	545
107.8947	10.5	16.3	172	14336
52.54902	37.2	-87	4	889
-27.02703	18.8	19.7	65	653
-47.1831	32.4	26.1	757	1630
-55.68513	39.8	16.6	365	334
-23.03665	47.3	-15.9	187	447
-9.40171	40.4	-3.5	524	732
-62.85714	42.5	-5.7	214	506
-31.33047	47.4	-30.1	621	884
-19.14063	37.9	12.6	187	334
38.13814	53.9	45.1	3523	1316

Regression analysis can be used to test whether the market efficiently uses information in valuing stocks. Let return be the total return (measured in %) from holding a firm's stock over the four-year period from the end of 1990 to the end 1994. The efficient markets hypothesis (EMH) says that these returns should not be systematically related to information known in 1990. If firm characteristics known at the beginning of the period help to predict stock returns, then we could use this information in choosing stocks. For 1990, let dkr be a firm's debt-to-capital ratio, let eps denote the earnings per share, let netinc denote the net income, and let salary denote total compensation for the CEO. Using the data in Computer_Exercse_10.xlsx, please answer the following questions. Assume throughout that assumptions MLR.1-MLR.6 are satisfied.

: = + + + ln()+ +