Multiple Linear Regression - Estimated Regression Equation
uitvoer[t] = + 5955.77107260798 + 0.900208484398036invoer[t] -867.895942836455crisis[t] -0.0883075849666572`y-1t`[t] -0.138612433670325`y-2t`[t] + 47.9932567530819M1[t] + 12.2726899811716M2[t] + 442.313077321896M3[t] + 699.792225468448M4[t] + 886.719663826503M5[t] -701.240818544068M6[t] + 326.178227477193M7[t] + 336.934312118696M8[t] + 477.992501240360M9[t] -333.713518950042M10[t] -664.563611004632M11[t] -16.2181101813024t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)5955.77107260798846.1513167.038700
invoer0.9002084843980360.06033114.921100
crisis-867.895942836455195.974054-4.42868.5e-054.2e-05
`y-1t`-0.08830758496665720.059826-1.47610.1486150.074308
`y-2t`-0.1386124336703250.061502-2.25380.0303940.015197
M147.9932567530819278.2916260.17250.8640440.432022
M212.2726899811716275.3673360.04460.9646980.482349
M3442.313077321896290.4489531.52290.1365310.068265
M4699.792225468448264.8415372.64230.0121110.006055
M5886.719663826503288.6136523.07230.0040320.002016
M6-701.240818544068326.830462-2.14560.0387240.019362
M7326.178227477193314.4513231.03730.3065170.153258
M8336.934312118696342.1570350.98470.3313260.165663
M9477.992501240360316.0195541.51250.1391260.069563
M10-333.713518950042324.548101-1.02820.3106960.155348
M11-664.563611004632289.250609-2.29750.0275080.013754
t-16.21811018130244.361496-3.71850.000680.00034


Multiple Linear Regression - Regression Statistics
Multiple R0.98801967954049
R-squared0.976182887159291
Adjusted R-squared0.965597503674532
F-TEST (value)92.2198887328718
F-TEST (DF numerator)16
F-TEST (DF denominator)36
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation380.234952554574
Sum Squared Residuals5204830.28919044


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
119554.220006.8612357149-452.661235714887
215903.816255.1567172060-351.356717206033
318003.817938.325326047065.4746739530497
418329.618729.504385277-399.904385276993
516260.716321.1937791186-60.4937791186145
614851.915289.2654953303-437.365495330281
718174.118069.2538362125104.846163787522
818406.618401.48447574835.1155242517048
918466.518223.5360939552242.963906044835
1016016.515827.2003998483189.299600151695
1117428.516859.6241967510568.875803248966
1217167.217100.385683132566.8143168675023
131963019061.3216146861568.678385313898
1417183.616680.5810860151503.018913984892
1518344.718265.364554926979.3354450731468
1619301.419057.0057913796244.394208620444
1718147.518345.6609161178-198.160916117803
1816192.915456.9595534970735.940446503026
1918374.418203.0561591202171.343840879794
2020515.220363.3764542983151.823545701736
2118957.219322.2584139307-365.058413930744
2216471.516971.0000656789-499.50006567888
2318746.819015.0091105593-268.209110559266
2419009.518776.5086375919232.991362408146
2519211.219545.5396709669-334.339670966895
2620547.720545.37201173212.32798826786109
2719325.819193.1078643412132.692135658825
2820605.520598.94404785236.55595214767582
2920056.920021.500369742535.3996302575103
3016141.416527.6672123013-386.267212301292
3120359.820738.6326401936-378.832640193638
3219711.619263.8362266042447.763773395803
3315638.615933.8066215111-295.206621511076
3414384.514327.883574888556.6164251114918
3513855.613985.475036422-129.875036421998
3614308.314358.6154596421-50.3154596421506
3715290.615456.8951562114-166.295156211382
3814423.814065.4764942971358.323505702895
3913779.714000.2776596302-220.577659630219
4015686.315845.3072975004-159.007297500377
4114733.814831.7436964113-97.9436964112903
4212522.512434.807738871587.6922611285465
4316189.416086.7573644737102.642635526322
4416059.116663.8028433492-604.702843349243
4516007.115589.7988706030417.301129396984
4615806.815553.2159595843253.584040415694
471516015330.7916562677-170.791656267702
4815692.115941.5902196335-249.490219633498
4918908.918524.2823224207384.617677579268
5016969.917482.2136907496-512.313690749615
5116997.517054.4245950548-56.924595054803
5219858.919550.9384779908307.961522009251
5317681.217360.0012386098321.198761390197


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
200.7941768755299770.4116462489400460.205823124470023
210.7553995733856540.4892008532286920.244600426614346
220.8041047638250890.3917904723498220.195895236174911
230.750665267457610.4986694650847780.249334732542389
240.7196013588315050.560797282336990.280398641168495
250.7559406670166470.4881186659667070.244059332983353
260.6753242360719080.6493515278561840.324675763928092
270.6606834217278730.6786331565442530.339316578272127
280.5865012847793780.8269974304412440.413498715220622
290.4798442949733930.9596885899467860.520155705026607
300.3733345142819350.746669028563870.626665485718065
310.3229472538267370.6458945076534730.677052746173263
320.5056789352174070.9886421295651870.494321064782593
330.4320186983944260.8640373967888520.567981301605574


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