Multiple Linear Regression - Estimated Regression Equation
Ye[t] = + 27.2834214053944 + 0.397125190922649`Ye-1`[t] + 0.241628865980788`Ye-2`[t] -0.0721154477263936`Ye-3`[t] + 0.194553871149098`Ye-4`[t] -8.55123851482719M1[t] -2.43346143954193M2[t] + 8.75387561158733M3[t] -12.7401440949288M4[t] -2.18969425871734M5[t] -16.6086800675589M6[t] -17.5742918715359M7[t] + 23.4944770899369M8[t] + 3.14624069205249M9[t] -11.5904562802941M10[t] -13.6691227830971M11[t] -0.290723078985568t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)27.283421405394413.8269971.97320.0531630.026582
`Ye-1`0.3971251909226490.1263293.14360.0026120.001306
`Ye-2`0.2416288659807880.1357261.78030.0801820.040091
`Ye-3`-0.07211544772639360.134954-0.53440.5950940.297547
`Ye-4`0.1945538711490980.1234481.5760.1203730.060186
M1-8.5512385148271912.080546-0.70790.4818240.240912
M2-2.4334614395419312.239001-0.19880.8430810.42154
M38.7538756115873312.3117750.7110.4798760.239938
M4-12.740144094928812.466598-1.02190.310980.15549
M5-2.1896942587173412.734413-0.1720.8640650.432032
M6-16.608680067558912.472345-1.33160.18810.09405
M7-17.574291871535912.332299-1.42510.1594080.079704
M823.494477089936912.3322751.90510.0616420.030821
M93.1462406920524913.5092360.23290.8166490.408324
M10-11.590456280294113.781157-0.8410.4037230.201862
M11-13.669122783097113.151083-1.03940.3028640.151432
t-0.2907230789855680.13498-2.15380.035350.017675


Multiple Linear Regression - Regression Statistics
Multiple R0.819156252095656
R-squared0.671016965347402
Adjusted R-squared0.581801227136528
F-TEST (value)7.52128468366599
F-TEST (DF numerator)16
F-TEST (DF denominator)59
p-value3.64684837883544e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation21.0468770596200
Sum Squared Residuals26135.2910038028


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
13048.7324279956963-18.7324279956963
24347.086469936221-4.08646993622098
38266.110368242706515.8896317572935
44060.980613945781-20.9806139457810
54762.0743382813179-15.0743382813179
61939.7127912223652-20.7127912223652
75239.644802834757312.3551971652427
813678.08630104788357.913698952117
980102.160719820264-22.1607198202642
104277.3637956525042-35.3637956525042
115446.7350124596347.26498754036598
126676.0780077967497-10.0780077967497
138166.746465115031614.2535348849684
146373.171510890558-10.1715108905580
1513782.013565496878354.9864345031217
167286.5196819898917-14.5196819898917
1710793.063193546035413.9368064539646
185867.7084772393128-9.70847723931278
193674.5345088777169-38.5345088777169
205279.565943831732-27.5659438317321
217970.30819478685888.69180521314117
227761.922616909805615.0773830901944
235459.8489239987506-5.84892399875062
248464.775931429452619.2240685705474
254867.6874470622396-19.6874470622396
269667.736407720156428.2635922798436
278382.35818921305780.641810786942179
286675.4417767652626-9.4417767652626
296165.3437191668188-4.34371916681884
305354.8167802383049-1.81678023830489
313047.8720617844677-17.8720617844677
327474.636358776985-0.636358776984946
336965.5175980092193.482401990781
345959.2384464349425-0.238446434942508
354244.041841877633-2.04184187763301
366557.17377224544397.8262277545561
377053.106384442697116.8936155573029
3810065.756952211025934.2430477889741
396384.8093951335112-21.8093951335112
4010559.694048061092545.3059519389075
418276.50207071973415.49792928026586
428171.31178251222879.6882174877713
437553.873516483760321.1264835162397
44102101.85710024070.142899759300056
4512186.088124134153934.9118758658461
469885.368200907042512.6317990929575
477675.34144007216090.658559927839122
487778.3083826726402-1.30838267264018
496369.9028900677126-6.90289006771262
503767.5236210706274-30.5236210706274
513560.3598753420447-25.3598753420447
522332.7027017985157-9.70270179851573
534036.86491597750723.13508402249283
542921.09261918917187.90738081082816
553720.051875558152116.9481244418479
565157.788396377094-6.78839637709397
572048.7429062355124-28.7429062355124
582822.07039322485795.92960677514215
591315.9343250260694-2.93432502606939
602230.2482108697931-8.24821086979305
612514.747849417139110.2521505828609
621326.5791014651225-13.5791014651225
631629.8677526473628-13.8677526473628
64137.909477540022235.09052245997777
651619.1517623085866-3.15176230858660
66172.3575495986167014.6424504013833
6793.023234461145685.97676553885432
681740.065899725606-23.065899725606
692521.18245701399183.81754298600822
701412.03654687084731.96345312915268
7185.098456565752062.90154343424794
72714.4156949859207-7.41569498592066
73106.076535899483623.92346410051638
74711.1459367062888-4.14593670628875
751020.4808539244387-10.4808539244387
763-1.248300100565774.24830010056577


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
200.9960993359498880.007801328100224420.00390066405011221
210.9970242451121290.005951509775743120.00297575488787156
220.9970102011530750.005979597693850760.00298979884692538
230.9979756372390230.004048725521953010.00202436276097650
240.9968933571068950.006213285786209330.00310664289310467
250.9982856764959040.003428647008192550.00171432350409628
260.9986465605704660.002706878859067150.00135343942953357
270.998982453013920.002035093972159230.00101754698607962
280.9989892078349040.002021584330192320.00101079216509616
290.9986225365877340.002754926824532280.00137746341226614
300.997338229585380.005323540829239340.00266177041461967
310.9975491775564210.004901644887157570.00245082244357879
320.9965721550529060.006855689894188420.00342784494709421
330.9934910441877450.01301791162450980.00650895581225492
340.9915274954249260.01694500915014760.00847250457507381
350.9905749882830610.01885002343387740.0094250117169387
360.983202765050020.03359446989995920.0167972349499796
370.974683728557730.05063254288453920.0253162714422696
380.9874621199120820.02507576017583660.0125378800879183
390.9939527481103820.01209450377923580.00604725188961791
400.9986172675233350.002765464953329050.00138273247666452
410.9977994679420490.004401064115902380.00220053205795119
420.9956442403476780.008711519304644180.00435575965232209
430.994291487467910.01141702506418210.00570851253209106
440.9954019063971390.009196187205721680.00459809360286084
450.9998960498716610.0002079002566770330.000103950128338516
460.9998622975113020.0002754049773966680.000137702488698334
470.999621620478160.0007567590436804630.000378379521840231
480.9994282302215770.001143539556845850.000571769778422925
490.9992980531144720.001403893771056240.000701946885528119
500.9988152802292450.002369439541509340.00118471977075467
510.997588637071420.004822725857160410.00241136292858021
520.9936886582170020.01262268356599610.00631134178299806
530.9869473354762860.02610532904742770.0130526645237139
540.9645164715433720.07096705691325580.0354835284566279
550.9486501591083470.1026996817833050.0513498408916527
560.9953250504571160.009349899085768990.00467494954288449


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level250.675675675675676NOK
5% type I error level340.918918918918919NOK
10% type I error level360.972972972972973NOK