Multiple Linear Regression - Estimated Regression Equation

Y[t] = + 52.9237129088855 -0.456561313045817X[t] + 0.529784539853996Y1[t] + 0.00162859374509381Y2[t] + 0.211227162008023Y3[t] -0.268925741424594Y4[t] + 0.779715739410484M1[t] + 0.72084508465959M2[t] + 1.39416708889035M3[t] -0.251540990310942M4[t] + 1.76147716754322M5[t] + 1.11916991858972M6[t] -0.0997453594323863M7[t] + 0.207964494807340M8[t] + 1.42410413266541M9[t] + 1.02998559517508M10[t] + 1.50184215778441M11[t] -0.00838297611828369t + 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)	52.9237129088855	13.880394	3.8128	0.00049	0.000245
X	-0.456561313045817	0.136277	-3.3502	0.001834	0.000917
Y1	0.529784539853996	0.150924	3.5103	0.001171	0.000585
Y2	0.00162859374509381	0.169852	0.0096	0.9924	0.4962
Y3	0.211227162008023	0.165712	1.2747	0.210167	0.105083
Y4	-0.268925741424594	0.139164	-1.9324	0.060785	0.030393
M1	0.779715739410484	0.631015	1.2357	0.224172	0.112086
M2	0.72084508465959	0.604075	1.1933	0.240147	0.120074
M3	1.39416708889035	0.62547	2.229	0.031805	0.015902
M4	-0.251540990310942	0.599557	-0.4195	0.677181	0.33859
M5	1.76147716754322	0.654977	2.6894	0.010573	0.005287
M6	1.11916991858972	0.607961	1.8409	0.07346	0.03673
M7	-0.0997453594323863	0.66993	-0.1489	0.882428	0.441214
M8	0.207964494807340	0.660939	0.3147	0.754748	0.377374
M9	1.42410413266541	0.661141	2.154	0.037645	0.018823
M10	1.02998559517508	0.684813	1.504	0.140838	0.070419
M11	1.50184215778441	0.655248	2.292	0.027535	0.013767
t	-0.00838297611828369	0.008107	-1.0341	0.30764	0.15382

Multiple Linear Regression - Regression Statistics
Multiple R	0.904112399567176
R-squared	0.817419231051118
Adjusted R-squared	0.735738360731881
F-TEST (value)	10.0074745513406
F-TEST (DF numerator)	17
F-TEST (DF denominator)	38
p-value	2.72499856013297e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.871677777536568
Sum Squared Residuals	28.8732416183414

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	100.49	100.327887702781	0.162112297219314
2	99.72	100.194257532837	-0.474257532837242
3	100.14	100.607920449935	-0.467920449934754
4	98.48	98.865910775912	-0.385910775912100
5	100.38	99.9230217466653	0.456978253334675
6	101.45	100.617663041944	0.832336958055842
7	98.42	99.3141181480133	-0.894118148013252
8	98.6	98.8576888042644	-0.257688804264411
9	100.06	99.779613936163	0.280386063837036
10	98.62	99.1774660221021	-0.5574660221021
11	100.84	100.098542554186	0.741457445814154
12	100.02	99.9764228155368	0.043577184463196
13	97.95	99.3918683819685	-1.44186838196845
14	98.32	99.0828026740398	-0.762802674039766
15	98.27	99.1701693740367	-0.900169374036691
16	97.22	97.5474073418492	-0.32740734184915
17	99.28	99.4478931365246	-0.167893136524621
18	100.38	99.685472895083	0.694527104916929
19	99.02	98.9729186987735	0.0470813012264834
20	100.32	99.31668616935	1.00331383064994
21	99.81	100.934966827585	-1.12496682758545
22	100.6	99.8639296398403	0.736070360159702
23	101.19	101.476749011563	-0.286749011563036
24	100.47	99.686085634843	0.783914365156985
25	101.77	100.335299854558	1.43470014544176
26	102.32	101.050390753080	1.26960924691957
27	102.39	101.652422574590	0.737577425409654
28	101.16	100.504534008056	0.655465991943504
29	100.63	101.624219682587	-0.99421968258655
30	101.48	100.785897881166	0.694102118834376
31	101.44	99.7294191200466	1.71058087995335
32	100.09	100.227767187345	-0.137767187345252
33	100.7	101.087979438499	-0.387979438498780
34	100.78	100.678099663345	0.101900336655159
35	99.81	100.545300765718	-0.735300765718213
36	98.45	98.6936203162728	-0.24362031627277
37	98.49	98.5044075775133	-0.0144075775132797
38	97.48	98.0471015090648	-0.567101509064845
39	97.91	98.104956193221	-0.194956193220964
40	96.94	96.6859666547372	0.25403334526283
41	98.53	98.0902830587537	0.439716941246282
42	96.82	98.1862518815735	-1.36625188157353
43	95.76	95.415490193245	0.344509806754938
44	95.27	95.7015135892872	-0.431513589287205
45	97.32	96.0874397977528	1.23256020224719
46	96.68	96.9605046747128	-0.280504674712759
47	97.87	97.5894076685329	0.280592331467096
48	97.42	98.0038712333474	-0.583871233347412
49	97.94	98.0805364831793	-0.140536483179338
50	99.52	98.9854475309777	0.534552469022281
51	100.99	100.164531408217	0.825468591782755
52	99.92	100.116181219445	-0.196181219445085
53	101.97	101.704582375470	0.265417624530215
54	101.58	102.434714300234	-0.854714300233616
55	99.54	100.748053839922	-1.20805383992152
56	100.83	101.006344249753	-0.176344249753068

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
21	0.593475660422072	0.813048679155856	0.406524339577928
22	0.473498161661901	0.946996323323802	0.526501838338099
23	0.445663568857683	0.891327137715367	0.554336431142317
24	0.416825557649025	0.83365111529805	0.583174442350975
25	0.583074056802449	0.833851886395102	0.416925943197551
26	0.58369702741661	0.832605945166779	0.416302972583389
27	0.482413061559585	0.96482612311917	0.517586938440415
28	0.418984965646474	0.837969931292949	0.581015034353526
29	0.609556527386277	0.780886945227447	0.390443472613723
30	0.614564307178687	0.770871385642627	0.385435692821313
31	0.725467682453386	0.549064635093227	0.274532317546614
32	0.777811566458133	0.444376867083734	0.222188433541867
33	0.7781744549891	0.4436510900218	0.2218255450109
34	0.674735376359363	0.650529247281274	0.325264623640637
35	0.495918592245693	0.991837184491385	0.504081407754307

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	0	0	OK
10% type I error level	0	0	OK