Multiple Linear Regression - Estimated Regression Equation

BESTC[t] = -6.92605201264424 + 0.259801879535493INDUSTR[t] + 0.155336451654076Y1[t] + 0.0649152601439141Y2[t] + 0.580833848588579Y3[t] + 0.0285751652133791Y4[t] -2.62125269928172M1[t] + 0.187869465600903M2[t] -2.89674579770143M3[t] -6.45300354254062M4[t] -2.02482601983913M5[t] -2.17130347109709M6[t] + 3.40503068660951M7[t] -0.58488239993721M8[t] + 0.271970079284188M9[t] + 0.552450778154068M10[t] -1.88858950952297M11[t] + 0.00827710547737372t + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	-6.92605201264424	12.419377	-0.5577	0.580333	0.290166
INDUSTR	0.259801879535493	0.050456	5.149	8e-06	4e-06
Y1	0.155336451654076	0.127793	1.2155	0.23166	0.11583
Y2	0.0649152601439141	0.134293	0.4834	0.631596	0.315798
Y3	0.580833848588579	0.121949	4.7629	2.8e-05	1.4e-05
Y4	0.0285751652133791	0.157421	0.1815	0.856924	0.428462
M1	-2.62125269928172	0.959351	-2.7323	0.00949	0.004745
M2	0.187869465600903	1.028426	0.1827	0.856023	0.428011
M3	-2.89674579770143	1.065543	-2.7186	0.009825	0.004913
M4	-6.45300354254062	1.00255	-6.4366	0	0
M5	-2.02482601983913	1.086113	-1.8643	0.07002	0.03501
M6	-2.17130347109709	0.954236	-2.2754	0.028605	0.014303
M7	3.40503068660951	1.356839	2.5095	0.01647	0.008235
M8	-0.58488239993721	1.429526	-0.4091	0.684731	0.342365
M9	0.271970079284188	1.273798	0.2135	0.83207	0.416035
M10	0.552450778154068	1.55929	0.3543	0.725075	0.362538
M11	-1.88858950952297	0.950698	-1.9865	0.054221	0.02711
t	0.00827710547737372	0.04689	0.1765	0.86082	0.43041

Multiple Linear Regression - Regression Statistics
Multiple R	0.985914410283178
R-squared	0.972027224404027
Adjusted R-squared	0.959513087953198
F-TEST (value)	77.6743347991521
F-TEST (DF numerator)	17
F-TEST (DF denominator)	38
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	1.07109106142283
Sum Squared Residuals	43.5949703506755

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	96.38	96.926373980974	-0.546373980973961
2	100.82	102.240407944953	-1.42040794495348
3	99.06	99.2271092997082	-0.167109299708232
4	94.03	94.3955388344205	-0.365538834420504
5	102.07	101.967289124756	0.102710875244458
6	99.31	98.9462952009838	0.363704799016176
7	98.64	100.327220414353	-1.68722041435251
8	101.82	101.809582788123	0.0104172118765759
9	99.14	99.1018527997348	0.0381472002652051
10	97.63	98.0112482316177	-0.381248231617671
11	100.06	99.9855820027115	0.0744179972884663
12	101.32	101.215732222646	0.104267777353873
13	101.49	100.990305700593	0.49969429940682
14	105.43	105.621925591510	-0.191925591509872
15	105.09	103.866016196302	1.22398380369764
16	99.48	99.5385856687715	-0.0585856687714791
17	108.53	108.154754867277	0.375245132722899
18	104.34	103.621358723548	0.718641276452006
19	106.1	105.95234047571	0.147659524290009
20	107.35	107.354123429917	-0.00412342991744168
21	103	103.546725557649	-0.546725557648704
22	104.5	104.091491127845	0.40850887215464
23	105.17	104.282239563621	0.887760436378853
24	104.84	105.656298987443	-0.816298987443351
25	106.18	106.094741120960	0.0852588790398619
26	108.86	109.011286867993	-0.151286867992541
27	107.77	106.603449483248	1.16655051675178
28	102.74	102.659904103448	0.0800958965522788
29	112.63	109.372015271112	3.25798472888756
30	106.26	106.015993216398	0.244006783601768
31	108.86	108.586164084375	0.273835915625037
32	111.38	110.611289359264	0.768710640735976
33	106.85	106.748769714301	0.101230285699228
34	107.86	107.617742548510	0.242257451489595
35	107.94	108.638234630358	-0.698234630357818
36	111.38	111.353408526568	0.0265914734319444
37	111.29	111.685694332439	-0.395694332439290
38	113.72	113.826482487517	-0.106482487516764
39	111.88	113.381925865696	-1.50192586569553
40	109.87	109.050428684655	0.819571315344856
41	113.72	114.853770272849	-1.13377027284880
42	111.71	112.780908813621	-1.07090881362101
43	114.81	113.939560478499	0.870439521500768
44	112.05	113.319128074169	-1.26912807416897
45	111.54	111.132651928316	0.40734807168427
46	110.87	111.139518092027	-0.269518092026565
47	110.87	111.133943803310	-0.263943803309501
48	115.48	114.794560263342	0.685439736657536
49	111.63	111.272884865033	0.357115134966568
50	116.24	114.369897108027	1.87010289197265
51	113.56	114.281499155046	-0.72149915504565
52	106.01	106.485542708705	-0.475542708705153
53	110.45	113.052170464006	-2.60217046400612
54	107.77	108.025444045449	-0.255444045448937
55	108.61	108.214714547063	0.395285452936694
56	108.19	107.695876348526	0.494123651473859

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
21	0.0865657664786096	0.173131532957219	0.91343423352139
22	0.0406185467378701	0.0812370934757403	0.95938145326213
23	0.0139493626966791	0.0278987253933581	0.98605063730332
24	0.0131920669820690	0.0263841339641381	0.98680793301793
25	0.0100237951212482	0.0200475902424963	0.989976204878752
26	0.00772342306559093	0.0154468461311819	0.99227657693441
27	0.00289829978092058	0.00579659956184117	0.99710170021908
28	0.00143168315009831	0.00286336630019662	0.998568316849902
29	0.255251754931251	0.510503509862502	0.744748245068749
30	0.206268414445646	0.412536828891293	0.793731585554354
31	0.124843804312208	0.249687608624416	0.875156195687792
32	0.122995822652591	0.245991645305182	0.87700417734741
33	0.0793964580214579	0.158792916042916	0.920603541978542
34	0.0612678977076657	0.122535795415331	0.938732102292334
35	0.0682948747788699	0.136589749557740	0.93170512522113

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	2	0.133333333333333	NOK
5% type I error level	6	0.4	NOK
10% type I error level	7	0.466666666666667	NOK