Multiple Linear Regression - Estimated Regression Equation
Maandelijksewerkloosheid[t] = + 399.088944444444 + 0.119125661375424M1[t] -6.30220105820107M2[t] -8.53696428571428M3[t] -10.5497275132276M4[t] -13.5971574074074M5[t] -11.8899206349206M6[t] + 6.02448280423279M7[t] + 7.68838624338623M8[t] + 1.68328968253969M9[t] -2.38280687830688M10[t] -7.13873677248678M11[t] -1.39340343915344t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)399.0889444444449.56963441.703700
M10.11912566137542411.3083770.01050.991630.495815
M2-6.3022010582010711.775598-0.53520.5944950.297248
M3-8.5369642857142811.765123-0.72560.4708950.235447
M4-10.549727513227611.755742-0.89740.3730870.186543
M5-13.597157407407411.747459-1.15750.2516730.125837
M6-11.889920634920611.740275-1.01270.3152480.157624
M76.0244828042327911.7341940.51340.6095480.304774
M87.6883862433862311.7292150.65550.5146580.257329
M91.6832896825396911.7253420.14360.8863290.443165
M10-2.3828068783068811.722574-0.20330.8396150.419807
M11-7.1387367724867811.720913-0.60910.5447840.272392
t-1.393403439153440.113924-12.23100


Multiple Linear Regression - Regression Statistics
Multiple R0.849858359743331
R-squared0.722259231625625
Adjusted R-squared0.66671107795075
F-TEST (value)13.0023985289058
F-TEST (DF numerator)12
F-TEST (DF denominator)60
p-value1.38489220091742e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation20.300258574558
Sum Squared Residuals24726.029891635


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1376.974397.814666666668-20.8406666666681
2377.632389.999936507936-12.3679365079365
3378.205386.37176984127-8.16676984126978
4370.861382.965603174603-12.1046031746032
5369.167378.52476984127-9.35776984126975
6371.551378.838603174603-7.28760317460311
7382.842395.359603174603-12.5176031746031
8381.903395.630103174603-13.7271031746031
9384.502388.231603174603-3.72960317460311
10392.058382.7721031746039.28589682539687
11384.359376.622769841277.7362301587302
12388.884382.3681031746036.5158968253969
13386.586381.0938253968255.49217460317498
14387.495373.27909523809514.2159047619048
15385.705369.65092857142916.0540714285714
16378.67366.24476190476212.4252380952382
17377.367361.80392857142915.5630714285715
18376.911362.11776190476214.7932380952381
19389.827378.63876190476211.1882380952381
20387.82378.9092619047628.91073809523811
21387.267371.51076190476215.7562380952381
22380.575366.05126190476214.5237380952381
23372.402359.90192857142912.5000714285714
24376.74365.64726190476211.0927380952381
25377.795364.37298412698413.4220158730161
26376.126356.55825396825419.5677460317460
27370.804352.93008730158717.8739126984127
28367.98349.52392063492118.4560793650794
29367.866345.08308730158722.7829126984127
30366.121345.39692063492120.7240793650794
31379.421361.91792063492117.5030793650794
32378.519362.18842063492116.3305793650794
33372.423354.78992063492117.6330793650794
34355.072349.3304206349215.74157936507937
35344.693343.1810873015871.51191269841268
36342.892348.926420634921-6.03442063492065
37344.178347.652142857143-3.47414285714263
38337.606339.837412698413-2.23141269841271
39327.103336.209246031746-9.10624603174603
40323.953332.803079365079-8.8500793650794
41316.532328.362246031746-11.8302460317461
42306.307328.676079365079-22.3690793650794
43327.225345.197079365079-17.9720793650794
44329.573345.467579365079-15.8945793650794
45313.761338.069079365079-24.3080793650794
46307.836332.609579365079-24.7735793650794
47300.074326.460246031746-26.386246031746
48304.198332.205579365079-28.0075793650794
49306.122330.931301587301-24.8093015873014
50300.414323.116571428571-22.7025714285715
51292.133319.488404761905-27.3554047619048
52290.616316.082238095238-25.4662380952381
53280.244311.641404761905-31.3974047619048
54285.179311.955238095238-26.7762380952381
55305.486328.476238095238-22.9902380952381
56305.957328.746738095238-22.7897380952381
57293.886321.348238095238-27.4622380952381
58289.441315.888738095238-26.4477380952381
59288.776309.739404761905-20.9634047619048
60299.149315.484738095238-16.3357380952381
61306.532314.21046031746-7.67846031746016
62309.914306.395730158733.51826984126978
63313.468302.76756349206410.7004365079365
64314.901299.36139682539715.5396031746031
65309.16294.92056349206414.2394365079365
66316.15295.23439682539720.9156031746031
67336.544311.75539682539724.7886031746031
68339.196312.02589682539727.1701031746031
69326.738304.62739682539722.1106031746031
70320.838299.16789682539721.6701031746031
71318.62293.01856349206425.6014365079365
72331.533298.76389682539732.7691031746031
73335.378297.48961904761937.8883809523811


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
167.82716348216002e-050.0001565432696432000.999921728365178
172.64739844036383e-065.29479688072766e-060.99999735260156
181.07224366610251e-062.14448733220503e-060.999998927756334
195.8294858276586e-081.16589716553172e-070.999999941705142
205.17741895871307e-091.03548379174261e-080.999999994822581
215.37506316177653e-091.07501263235531e-080.999999994624937
225.83555960711212e-061.16711192142242e-050.999994164440393
231.61781803239488e-053.23563606478976e-050.999983821819676
241.88342885362498e-053.76685770724996e-050.999981165711464
257.03128401072435e-061.40625680214487e-050.99999296871599
263.45055823378163e-066.90111646756326e-060.999996549441766
272.82393443080600e-065.64786886161200e-060.99999717606557
281.20425709091510e-062.40851418183021e-060.99999879574291
295.96895638894492e-071.19379127778898e-060.99999940310436
303.91125133886769e-077.82250267773539e-070.999999608874866
312.17072092921056e-074.34144185842111e-070.999999782927907
321.26816881117096e-072.53633762234192e-070.99999987318312
333.08561776688866e-076.17123553377732e-070.999999691438223
342.11861642261216e-054.23723284522431e-050.999978813835774
350.0003584876669407730.0007169753338815470.99964151233306
360.00356908135870.00713816271740.9964309186413
370.009762727376306280.01952545475261260.990237272623694
380.03683390220969820.07366780441939640.963166097790302
390.1158732596435850.2317465192871710.884126740356415
400.2189340048188340.4378680096376680.781065995181166
410.4344384894959910.8688769789919810.565561510504009
420.604349319254930.791301361490140.39565068074507
430.6938890564198620.6122218871602750.306110943580138
440.784203405443650.4315931891126980.215796594556349
450.8919267359249970.2161465281500060.108073264075003
460.9654618572970170.06907628540596660.0345381427029833
470.9914148076321880.0171703847356230.0085851923678115
480.998151737510650.003696524978700320.00184826248935016
490.9999499163977460.0001001672045089315.00836022544653e-05
500.9999996745829586.50834084964026e-073.25417042482013e-07
510.999999942491321.15017359525667e-075.75086797628333e-08
520.9999999934709881.30580241381422e-086.52901206907111e-09
530.9999999675706536.48586940590337e-083.24293470295168e-08
540.9999994977070421.00458591651325e-065.02292958256626e-07
550.9999924650226081.50699547848338e-057.5349773924169e-06
560.9999412295585630.0001175408828741455.87704414370725e-05
570.9995532959005130.0008934081989737310.000446704099486866


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level310.738095238095238NOK
5% type I error level330.785714285714286NOK
10% type I error level350.833333333333333NOK