Multiple Linear Regression - Estimated Regression Equation
intermediair-goederen[t] = + 63.2918547561732 + 0.492112301221743`totale-consumptie`[t] + 0.069106408222602`Duurzame-consumptiegoederen`[t] -0.246532951311145`Niet-duurzame-consumptiegoederen`[t] + 1.81049508054877`invoering-Euro`[t] + 4.20172076779845M1[t] + 2.26857772228726M2[t] + 7.14366835956165M3[t] + 3.63110271774098M4[t] + 2.16895492885366M5[t] + 4.79576035750822M6[t] -1.77454089871045M7[t] -1.66808691604056M8[t] + 4.56736297935084M9[t] + 7.82975549476553M10[t] + 5.91401219955562M11[t] + 0.0521337471754658t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)63.291854756173218.8096093.36490.0013080.000654
`totale-consumptie`0.4921123012217430.9593050.5130.6097540.304877
`Duurzame-consumptiegoederen`0.0691064082226020.1500710.46050.6467490.323375
`Niet-duurzame-consumptiegoederen`-0.2465329513111450.882686-0.27930.7809310.390465
`invoering-Euro`1.810495080548772.4733390.7320.466880.23344
M14.201720767798453.3964051.23710.2206380.110319
M22.268577722287263.4489610.65780.5130910.256545
M37.143668359561653.4180182.090.040660.02033
M43.631102717740983.4494211.05270.2965130.148256
M52.168954928853663.4079650.63640.5267970.263399
M64.795760357508223.4014711.40990.1634850.081742
M7-1.774540898710454.488736-0.39530.6939330.346967
M8-1.668086916040564.149851-0.4020.6890720.344536
M94.567362979350843.76721.21240.2298850.114943
M107.829755494765533.7607922.08190.0414160.020708
M115.914012199555623.3649821.75750.0836880.041844
t0.05213374717546580.0893330.58360.561580.28079


Multiple Linear Regression - Regression Statistics
Multiple R0.741721604215162
R-squared0.550150938159513
Adjusted R-squared0.435903557374627
F-TEST (value)4.81543589340908
F-TEST (DF numerator)16
F-TEST (DF denominator)63
p-value3.02267090046549e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation5.65892758359492
Sum Squared Residuals2017.47806797140


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1103.198.53917181896934.56082818103073
2100.696.7181341353553.88186586464502
3103.1104.497520881244-1.39752088124411
495.597.2774322560174-1.77743225601737
590.597.189958874084-6.68995887408404
690.9102.312805670147-11.4128056701465
788.889.0945852677263-0.294585267726265
890.791.1212016479903-0.421201647990273
994.3101.994369707986-7.69436970798589
10104.6108.209864390325-3.60986439032454
11111.1102.7712710729048.3287289270964
12110.894.273684277253116.5263157227469
13107.2100.3098670462816.89013295371897
149998.69719978323380.302800216766244
1599105.765889182835-6.76588918283475
1691100.926890117607-9.92689011760664
1796.299.486699548254-3.28669954825395
1896.9103.331959329582-6.43195932958242
1996.292.11403272716784.08596727283221
20100.191.6376303480978.46236965190303
2199103.69888510378-4.69888510378004
22115.4109.4187902442465.98120975575422
23106.9103.6400515635233.25994843647731
24107.196.407713269414310.6922867305857
2599.3102.601118151118-3.30111815111762
2699.299.4810416429704-0.281041642970379
27108.3106.8362737054631.46372629453747
28105.6102.3129614622743.28703853772636
2999.597.90528016129481.59471983870518
30107.4102.849770979254.55022902074993
3193.193.5698350072495-0.469835007249489
3288.192.6182240025408-4.51822400254083
33110.7107.8958152509042.80418474909566
34113.1111.4243569274521.67564307254827
3599.6105.513329801018-5.91332980101804
3693.6101.309009421050-7.70900942104974
3798.699.8084863348103-1.20848633481026
3899.699.33555097935930.264449020640698
39114.3108.9186919477215.38130805227891
40107.8101.757042036776.04295796322997
41101.299.23005920796881.96994079203116
42112.5108.2559701444884.24402985551156
43100.594.1008721607346.39912783926596
4493.994.8353388603932-0.935338860393201
45116.2108.4562185884047.74378141159617
46112109.633415660042.36658433995998
47106.4106.60905887101-0.209058871010030
4895.7102.654453665150-6.95445366514951
4996101.744562934875-5.74456293487478
5095.899.3854963310302-3.58549633103023
51103108.566001150835-5.56600115083498
52102.2102.611349077943-0.411349077942749
5398.4100.497503102618-2.09750310261814
54111.4106.6810728195864.71892718041355
5586.692.239858841648-5.63985884164799
5691.395.1246894015325-3.82468940153247
57107.9108.760322515694-0.860322515694005
58101.8108.555104907329-6.75510490732889
59104.4108.174771103752-3.77477110375184
6093.4100.699461287331-7.29946128733058
61100.1102.947889582913-2.84788958291286
6298.5102.067941402434-3.56794140243439
63112.9111.8491024824231.05089751757684
64101.4102.496270890399-1.09627089039948
65107.1103.901882705613.19811729438999
66110.8108.2557577606482.54424223935164
6790.393.4560294386773-3.1560294386773
6895.596.9131036761314-1.41310367613142
69111.4108.6943888332322.7056111667681
70113112.6584678706090.341532129390953
71107.5109.191517587794-1.69151758779381
7295.9101.155678079803-5.25567807980271
73106.3104.6489041310341.65109586896583
74105.2102.2146357256172.98536427438304
75117.2111.3665206494795.83347935052061
76106.9103.018054158993.8819458410099
77108.2102.8886164001705.3113835998298
78110108.2126632962981.78733670370228
7996.197.0247865567971-0.92478655679712
80100.697.94981206331482.65018793668517