Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 8.0159995930798 -0.396793923176626X[t] + 0.429040951968163Y1[t] + 0.117021660229381Y2[t] + 0.0321909561234374Y3[t] + 0.0338671313400513Y4[t] + 0.522084696539833M1[t] + 1.60881904762785M2[t] + 0.429102182903779M3[t] + 1.21952238869631M4[t] -0.0690080080649838M5[t] + 0.0599839230344053M6[t] + 0.21231296050147M7[t] + 0.870779207535017M8[t] + 0.429799214978465M9[t] + 2.35819701640652M10[t] + 0.84752047137127M11[t] -0.027329651821742t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)8.01599959307983.5193162.27770.0270530.013527
X-0.3967939231766260.640905-0.61910.5386510.269326
Y10.4290409519681630.1424213.01250.0040580.002029
Y20.1170216602293810.1507430.77630.441230.220615
Y30.03219095612343740.1525930.2110.8337760.416888
Y40.03386713134005130.1430650.23670.8138370.406918
M10.5220846965398330.9071110.57550.5675030.283752
M21.608819047627850.8919561.80370.0773050.038652
M30.4291021829037790.8657430.49560.6223160.311158
M41.219522388696310.8292261.47070.1476440.073822
M5-0.06900800806498380.884278-0.0780.9381090.469054
M60.05998392303440530.8509470.07050.9440840.472042
M70.212312960501470.8998260.23590.8144360.407218
M80.8707792075350170.8868250.98190.3308740.165437
M90.4297992149784650.9051790.47480.6369810.31849
M102.358197016406520.8778212.68640.0097780.004889
M110.847520471371270.9302270.91110.366620.18331
t-0.0273296518217420.018785-1.45490.1519480.075974


Multiple Linear Regression - Regression Statistics
Multiple R0.86441380380356
R-squared0.747211224206141
Adjusted R-squared0.661263040436229
F-TEST (value)8.69374071017563
F-TEST (DF numerator)17
F-TEST (DF denominator)50
p-value1.00810626513237e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.35086548652037
Sum Squared Residuals91.2418781335953


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
12021.3143257579137-1.31432575791368
22121.9973292531943-0.997329253194314
32121.0667587218306-0.0667587218305936
42121.9485471112474-0.948547111247382
51920.6310108874477-1.63101088744773
62119.90845839412911.09154160587090
72120.6574963632520.342503636748009
82221.45829436667570.541705633324316
91921.4156733238323-2.41567332383232
102422.21437454044361.78562545955636
112222.5026990788628-0.502699078862749
122221.29216961585010.707830384149943
132221.61223472670640.387765273293582
142422.77659317042611.22340682957392
152222.3598942951365-0.359894295136486
162322.49894626562970.501053734370291
172421.44246576080302.55753423919705
182122.0935430027114-1.09354300271137
192021.0128978861249-1.01289788612492
202220.92998663614391.07001336385609
212321.14003149844231.85996850155770
222323.5703915703319-0.570391570331944
232222.1799218146112-0.179921814611156
242020.9759559582535-0.97595595825352
252120.13268064696930.867319353030671
262121.3548920216216-0.35489202162157
272020.1666181217182-0.166618121718209
282020.4651244171642-0.465124417164170
291719.0661098396918-2.06610983969180
301817.84845830694150.151541693058476
311918.01756653252680.982433467473184
321919.0981928715659-0.098192871565853
332018.67749444952021.32250555047978
342121.0736616385582-0.0736616385581894
352020.1155851852388-0.115585185238791
362118.96090672643042.03909327356957
371919.8337391503508-0.833739150350797
382220.15375978112671.84624021887326
392019.99811662481000.00188337518995838
401820.2236754746258-2.22367547462582
411617.8445288073379-1.84452880733791
421716.89128534399370.108714656006254
431817.07916618622150.920833813778507
441918.12424921870390.875750781296134
451818.1664588799664-0.166458879966450
462019.82156582529750.17843417470253
472119.09067795961091.90932204038909
481818.8805882840614-0.880588284061438
491918.23575691401120.764243085988755
501919.4730628033611-0.473062803361084
511918.32033221001440.679667789985612
522119.01401232608851.98598767391154
531918.59010131278180.409898687218198
541918.06772500858190.932274991418116
551718.0230629860153-1.02306298601532
561617.7994700277240-1.79947002772403
571616.6003418482387-0.600341848238704
581718.3200064253688-1.32000642536876
591617.1111159616764-1.11111596167639
601515.8903794154045-0.890379415404548
611615.87126280404850.128737195951467
621617.2443629702702-1.24436297027021
631616.0882800264903-0.0882800264902834
641816.84969440524451.15030559475554
651916.42578339193782.5742166080622
661617.1905299436424-1.19052994364237
671616.2098100458595-0.209810045859461
681616.5898068791867-0.589806879186663


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
210.836013165368370.3279736692632610.163986834631631
220.9018511866828810.1962976266342370.0981488133171186
230.8262189099143640.3475621801712720.173781090085636
240.8806994036101140.2386011927797720.119300596389886
250.8219181003021040.3561637993957910.178081899697896
260.7363750714062290.5272498571875420.263624928593771
270.6439590490794580.7120819018410830.356040950920542
280.5472784527900110.9054430944199780.452721547209989
290.6556197668427330.6887604663145340.344380233157267
300.5559325867492740.8881348265014520.444067413250726
310.4888564184109220.9777128368218430.511143581589078
320.3921391686918860.7842783373837730.607860831308114
330.3942775993068610.7885551986137220.605722400693139
340.3012689863276370.6025379726552740.698731013672363
350.2280811441842660.4561622883685320.771918855815734
360.2905000540011880.5810001080023760.709499945998812
370.2575957147906490.5151914295812980.742404285209351
380.3350717637846890.6701435275693770.664928236215311
390.2910725156420830.5821450312841650.708927484357917
400.4764222354010310.9528444708020630.523577764598969
410.8264605811516750.3470788376966500.173539418848325
420.8253328869515020.3493342260969950.174667113048498
430.7325282466361920.5349435067276150.267471753363808
440.6695705817784120.6608588364431750.330429418221588
450.5334836268952730.9330327462094530.466516373104727
460.3877856549165640.7755713098331270.612214345083437
470.5084061676163430.9831876647673140.491593832383657


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level00OK