Multiple Linear Regression - Estimated Regression Equation
Maandelijksewerkloosheid[t] = + 6.06645265428026 + 6.51400634022988x[t] + 1.04111636612974`y-1`[t] -0.0567105374733346`y-2`[t] -1.78757398818603M1[t] -1.38927597259309M2[t] -3.46312965581879M3[t] + 1.39314919046846M4[t] + 17.4477569184918M5[t] + 0.647957883429362M6[t] -5.98306251125522M7[t] -3.6123360833013M8[t] -4.38508073448924M9[t] + 7.56499978638544M10[t] + 3.54606068516857M11[t] -0.112186792756548t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)6.0664526542802612.9759360.46750.6419780.320989
x6.514006340229882.2691252.87070.0058030.002902
`y-1`1.041116366129740.1359797.656500
`y-2`-0.05671053747333460.139013-0.4080.6848930.342446
M1-1.787573988186032.901074-0.61620.540320.27016
M2-1.389275972593092.958344-0.46960.6404880.320244
M3-3.463129655818793.01557-1.14840.2557670.127884
M41.393149190468463.0529240.45630.6499480.324974
M517.44775691849182.9007396.014900
M60.6479578834293623.4178940.18960.8503380.425169
M7-5.983062511255222.910269-2.05580.0445560.022278
M8-3.61233608330133.198459-1.12940.2636310.131816
M9-4.385080734489243.067963-1.42930.158570.079285
M107.564999786385443.0881392.44970.017510.008755
M113.546060685168572.8952011.22480.2258680.112934
t-0.1121867927565480.067224-1.66890.100830.050415


Multiple Linear Regression - Regression Statistics
Multiple R0.992938292177012
R-squared0.985926452071402
Adjusted R-squared0.982088211727238
F-TEST (value)256.869389008090
F-TEST (DF numerator)15
F-TEST (DF denominator)55
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation4.71073709484016
Sum Squared Residuals1220.50741871867


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1378.205375.947149294172.25785070583032
2370.861376.792504661141-5.93150466114085
3369.167366.9280104543302.23898954567037
4371.551370.3249335708411.22606642915933
5382.842388.845443573441-6.00344357344062
6381.903383.553504714256-1.65050471425601
7384.502375.1923705804089.30962941959232
8392.058380.21002284586411.8479771541363
9384.359387.044375977502-2.6853759775023
10388.884390.438209981639-1.55420998163903
11386.586391.45475007241-4.86875007240991
12387.495385.1474020030522.34759799694818
13385.705384.3243368140351.38066318596509
14378.67382.695299862936-4.02529986293576
15377.367373.2865176133084.08048238669189
16376.911377.072993672897-0.161993672896697
17389.827392.614559375536-2.78755937553608
18387.82389.175492537737-1.35549253773660
19387.267379.6102915014677.65670849853251
20380.575381.406911834904-0.831911834904114
21372.402373.586190596042-1.18419059604217
22376.74377.294547180554-0.554547180553501
23377.795378.143279305620-0.348279305620464
24376.126375.3373992824030.788600717597068
25370.804371.640185669355-0.836185669355417
26367.98366.4801254786921.4998745213077
27367.866361.6557858651936.21021413480716
28366.121366.441341210809-0.320341210809422
29379.421380.573479088452-1.15247908845178
30378.519377.6073008180490.911699181950759
31372.423369.1707565199643.25224348003624
32355.072365.133803692035-10.0618036920352
33344.693346.530169615811-1.83716961581112
34342.892348.546301115568-5.6543011155685
35344.178343.1287233146311.04927668536882
36337.606340.911487161538-3.30548716153839
37327.103332.096579871200-4.99357987120045
38323.953321.8205475528512.13245244714898
39316.532316.950621298642-0.418621298642485
40306.307314.147226992165-7.8402269921654
41327.225319.8650819823457.35991801765472
42329.573325.3110335468934.26196645310698
43313.761319.826096564257-6.0650965642572
44307.836305.4893478762242.34665212377615
45300.074299.3325089814890.741491018510982
46304.198303.4252674102380.772732589762322
47306.122304.0278926020512.09410739794875
48300.414302.13887875602-1.72487875601977
49292.133294.18731468311-2.05431468310993
50290.616286.1756450259244.44035497407624
51280.244289.393857323569-9.1498573235692
52285.179283.4255203129491.75347968705057
53305.486305.094052209740.391947790260164
54305.957309.044149926487-3.08714992648651
55293.886301.639687663022-7.75368766302145
56289.441291.304200979517-1.86320097951692
57288.776286.4760601859662.29993981403372
58299.149297.8736898696771.27531013032284
59306.532304.5797765489871.95222345101272
60309.914308.0198327969871.89416720301292
61313.468309.2224336681304.24556633187039
62314.901313.0168774184561.88412258154369
63309.16312.121207444958-2.96120744495772
64316.15310.8069842403385.34301575966162
65336.544334.3523837704862.19161622951359
66339.196338.2765184565790.919481543421384
67326.738333.137797170882-6.39979717088243
68320.838322.275712771456-1.43771277145621
69318.62315.9546946431892.66530535681088
70331.533325.8179844423245.71501555767586
71335.378335.25657815630.121421843700092


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
190.0742208521442160.1484417042884320.925779147855784
200.4645781272091320.9291562544182640.535421872790868
210.5652031420998560.8695937158002870.434796857900144
220.4865247464159840.9730494928319670.513475253584016
230.3922044058708770.7844088117417550.607795594129123
240.3125264649538240.6250529299076470.687473535046176
250.2396707403164770.4793414806329540.760329259683523
260.2526965395622580.5053930791245160.747303460437742
270.3091451376217080.6182902752434160.690854862378292
280.2536752299829600.5073504599659210.74632477001704
290.1900878809121630.3801757618243260.809912119087837
300.1352608176106660.2705216352213320.864739182389334
310.4880459213702590.9760918427405190.511954078629741
320.8879026434166380.2241947131667240.112097356583362
330.8483326456660470.3033347086679070.151667354333953
340.8491427424253570.3017145151492850.150857257574643
350.81672291953210.3665541609357990.183277080467900
360.7784190725121520.4431618549756970.221580927487848
370.7741867417952860.4516265164094280.225813258204714
380.7777030450586380.4445939098827230.222296954941362
390.77728164799850.4454367040030.2227183520015
400.9772636521417240.04547269571655120.0227363478582756
410.9908296054020450.01834078919591060.00917039459795532
420.9922425476398040.01551490472039240.00775745236019619
430.992671221938360.01465755612328110.00732877806164057
440.9961759371236830.007648125752633170.00382406287631659
450.991975367219620.01604926556076030.00802463278038013
460.9833780863522520.03324382729549560.0166219136477478
470.9979892943993540.004021411201291160.00201070560064558
480.9997224937684950.000555012463010220.00027750623150511
490.9987936785538140.002412642892372450.00120632144618623
500.9953677674189990.009264465162002470.00463223258100123
510.9854092839291870.02918143214162550.0145907160708128
520.953865346375260.09226930724947960.0461346536247398


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level50.147058823529412NOK
5% type I error level120.352941176470588NOK
10% type I error level130.382352941176471NOK