Multiple Linear Regression - Estimated Regression Equation

Y[t] = + 2.05759809137512 -1.34349590744337X[t] + 2.04020190088604Y1[t] -1.68946994756172Y2[t] + 0.618936790208306Y3[t] -0.00770865748085621Y4[t] -0.100396827439893M1[t] + 0.107169039936851M2[t] + 0.204369358897789M3[t] -0.0585080940876201M4[t] + 0.209666525151896M5[t] + 0.146397273622895M6[t] + 0.0118560418967594M7[t] -0.0341146470032650M8[t] -0.0954261218610972M9[t] -0.126692471979731M10[t] + 0.380972209907139M11[t] + 0.00424111248802652t + 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)	2.05759809137512	1.098634	1.8729	0.068596	0.034298
X	-1.34349590744337	0.422544	-3.1795	0.002888	0.001444
Y1	2.04020190088604	0.159317	12.8059	0	0
Y2	-1.68946994756172	0.353097	-4.7847	2.5e-05	1.2e-05
Y3	0.618936790208306	0.341779	1.8109	0.07786	0.03893
Y4	-0.00770865748085621	0.146222	-0.0527	0.958225	0.479112
M1	-0.100396827439893	0.399058	-0.2516	0.802683	0.401342
M2	0.107169039936851	0.393012	0.2727	0.786533	0.393266
M3	0.204369358897789	0.392821	0.5203	0.605823	0.302911
M4	-0.0585080940876201	0.394326	-0.1484	0.882812	0.441406
M5	0.209666525151896	0.398637	0.526	0.601895	0.300948
M6	0.146397273622895	0.39033	0.3751	0.709648	0.354824
M7	0.0118560418967594	0.388459	0.0305	0.975807	0.487904
M8	-0.0341146470032650	0.391009	-0.0872	0.930921	0.465461
M9	-0.0954261218610972	0.391833	-0.2435	0.808866	0.404433
M10	-0.126692471979731	0.414571	-0.3056	0.761535	0.380768
M11	0.380972209907139	0.413636	0.921	0.362696	0.181348
t	0.00424111248802652	0.013561	0.3127	0.756143	0.378071

Multiple Linear Regression - Regression Statistics
Multiple R	0.998902011700706
R-squared	0.997805228979716
Adjusted R-squared	0.996848533919593
F-TEST (value)	1042.97102657850
F-TEST (DF numerator)	17
F-TEST (DF denominator)	39
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.573066554643035
Sum Squared Residuals	12.8078057659671

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	50.9	51.1212796649841	-0.221279664984063
2	50.6	50.4705111593721	0.129488840627942
3	52.1	51.710421055706	0.389578944294044
4	53.3	53.921030509141	-0.62103050914098
5	53.9	53.9356781469922	-0.0356781469922387
6	54.3	54.0041249939655	0.295875006034448
7	54.2	54.4073848285735	-0.207384828573497
8	54.2	53.8479587681962	0.352041231803821
9	53.5	54.2027849221773	-0.702784922177347
10	51.4	52.6826412119133	-1.28264121191334
11	50.5	50.0935228434688	0.406477156531164
12	50.3	50.9952411719861	-0.69524117198609
13	49.8	50.7171968304617	-0.91719683046171
14	50.7	49.7059419189181	0.994058081081873
15	52.8	52.3714504686365	0.428549531363487
16	55.3	54.5687885035863	0.731211496413733
17	57.3	56.9547195375772	0.345280462422786
18	57.5	58.0452497991087	-0.545249799108692
19	56.8	56.4752039597353	0.324796040264674
20	56.4	55.8860409999052	0.513959000094783
21	56.3	56.3038888835542	-0.00388888355415752
22	56.4	56.3138339502176	0.0861660497823591
23	57	56.9565282735906	0.0434717264094057
24	57.9	57.5761611059184	0.323838894081553
25	58.9	58.3651696779959	0.534830322004101
26	58.8	59.4672468143181	-0.667246814318064
27	56.5	56.8841201173723	-0.384120117372298
28	51.9	52.7139653980687	-0.813965398068738
29	47.4	47.4176309286107	-0.0176309286107529
30	44.9	44.5264722426355	0.373527757364507
31	43.9	44.0689028124578	-0.16890281245778
32	43.4	43.4608904725386	-0.0608904725386027
33	42.9	42.5605360904306	0.339463909569416
34	42.6	41.7584797296316	0.841520270368353
35	42.2	42.2013001898983	-0.00130018989829765
36	41.2	41.2097152500296	-0.00971525002955794
37	40.2	39.5673189048943	0.632681095105726
38	39.3	39.1831318125957	0.116868187404336
39	38.5	38.5220081535929	-0.0220081535929321
40	38.3	37.5405051124648	0.759494887535167
41	37.9	38.2071219683579	-0.307121968357908
42	37.6	37.181695418041	0.418304581959006
43	37.3	36.9975022755048	0.302497724495209
44	36	36.6045201285083	-0.604520128508329
45	34.5	34.2194307051851	0.280569294814949
46	33.5	33.1450451082374	0.354954891762624
47	32.9	33.3486486930423	-0.448648693042271
48	32.9	32.5188824720659	0.381117527934092
49	32.8	32.8290349216641	-0.0290349216640542
50	31.9	32.4731682947961	-0.573168294796087
51	30.5	30.9120002046923	-0.412000204692302
52	29.2	29.2557104767392	-0.0557104767391808
53	28.7	28.6848494184619	0.0151505815381141
54	28.4	28.9424575462493	-0.54245754624927
55	28	28.2510061237286	-0.251006123728606
56	27.4	27.6005896308517	-0.200589630851673
57	26.9	26.8133593986529	0.0866406013471385

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
21	0.925399369864144	0.149201260271712	0.0746006301358558
22	0.990968045339367	0.0180639093212669	0.00903195466063344
23	0.977913901032072	0.0441721979358552	0.0220860989679276
24	0.965967970832385	0.0680640583352306	0.0340320291676153
25	0.958116538106941	0.0837669237861171	0.0418834618930585
26	0.985531318012846	0.0289373639743077	0.0144686819871538
27	0.99655339671301	0.00689320657398014	0.00344660328699007
28	0.99385290058295	0.0122941988340999	0.00614709941704995
29	0.985256950135724	0.0294860997285526	0.0147430498642763
30	0.983594242951488	0.0328115140970232	0.0164057570485116
31	0.967258783746273	0.0654824325074542	0.0327412162537271
32	0.955349458056077	0.0893010838878464	0.0446505419439232
33	0.925620079294063	0.148759841411874	0.0743799207059372
34	0.877160803503436	0.245678392993127	0.122839196496564
35	0.781540274530395	0.436919450939211	0.218459725469605
36	0.795885613290518	0.408228773418964	0.204114386709482

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	1	0.0625	NOK
5% type I error level	7	0.4375	NOK
10% type I error level	11	0.6875	NOK