Multiple Linear Regression - Estimated Regression Equation
Maandelijksewerkloosheid[t] = + 402.681268612009 + 9.6304860662359x[t] -0.232099548522936M1[t] -6.31675961612434M2[t] -8.3895588867413M3[t] -10.2403581573583M4[t] -14.7309051056812M5[t] -12.8617043762982M6[t] + 5.2146630197515M7[t] + 7.04053041580121M8[t] + 1.19739781185091M9[t] -2.7067347920994M10[t] -7.30070072938304M11[t] -1.55536739604970t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)402.68126861200910.06657640.001800
x9.63048606623598.5481721.12660.2644670.132234
M1-0.23209954852293611.287394-0.02060.9836640.491832
M2-6.3167596161243411.749271-0.53760.5928550.296427
M3-8.389558886741311.739541-0.71460.4776490.238825
M4-10.240358157358311.732667-0.87280.3863060.193153
M5-14.730905105681211.764309-1.25220.2154490.107725
M6-12.861704376298211.745736-1.0950.2779620.138981
M75.214663019751511.7299970.44460.6582660.329133
M87.0405304158012111.7171050.60090.5502240.275112
M91.1973978118509111.7070670.10230.9188810.459441
M10-2.706734792099411.699893-0.23130.8178460.408923
M11-7.3007007293830411.695586-0.62420.5348850.267442
t-1.555367396049700.183271-8.486700


Multiple Linear Regression - Regression Statistics
Multiple R0.853292678047315
R-squared0.728108394409158
Adjusted R-squared0.66820007453321
F-TEST (value)12.153710802053
F-TEST (DF numerator)13
F-TEST (DF denominator)59
p-value2.87281309852006e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation20.2548612485385
Sum Squared Residuals24205.3048476554


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1376.974400.893801667436-23.9198016674358
2377.632393.253774203785-15.6217742037849
3378.205389.625607537118-11.4206075371183
4370.861386.219440870452-15.3584408704516
5369.167380.173526526079-11.0065265260790
6371.551380.487359859412-8.93635985941227
7382.842397.008359859412-14.1663598594123
8381.903397.278859859412-15.3758598594123
9384.502389.880359859412-5.37835985941227
10392.058384.4208598594127.63714014058772
11384.359378.2715265260796.08747347392105
12388.884384.0168598594124.86714014058774
13386.586382.229392914844.35660708516037
14387.495374.58936545118912.9056345488115
15385.705370.96119878452214.7438012154781
16378.67367.55503211785511.1149678821448
17377.367361.50911777348315.8578822265174
18376.911361.82295110681615.0880488931841
19389.827378.34395110681611.4830488931841
20387.82378.6144511068169.20554889318407
21387.267371.21595110681616.0510488931841
22380.575365.75645110681614.8185488931841
23372.402359.60711777348312.7948822265174
24376.74365.35245110681611.3875488931841
25377.795363.56498416224314.2300158377567
26376.126355.92495669859220.2010433014078
27370.804352.29679003192618.5072099680745
28367.98348.89062336525919.0893766347412
29367.866342.84470902088625.0212909791138
30366.121343.15854235422022.9624576457804
31379.421359.67954235422019.7414576457804
32378.519359.95004235422018.5689576457805
33372.423352.55154235422019.8714576457804
34355.072347.0920423542207.97995764578045
35344.693340.9427090208863.75029097911376
36342.892346.688042354220-3.79604235421957
37344.178344.900575409647-0.722575409646927
38337.606337.2605479459960.345452054004159
39327.103333.632381279329-6.52938127932917
40323.953330.226214612662-6.27321461266254
41316.532324.18030026829-7.64830026828988
42306.307324.494133601623-18.1871336016232
43327.225341.015133601623-13.7901336016232
44329.573341.285633601623-11.7126336016232
45313.761333.887133601623-20.1261336016232
46307.836328.427633601623-20.5916336016232
47300.074322.27830026829-22.2043002682898
48304.198328.023633601623-23.8256336016232
49306.122326.236166657051-20.1141666570505
50300.414318.596139193399-18.1821391933995
51292.133314.967972526733-22.8349725267328
52290.616311.561805860066-20.9458058600662
53280.244315.146377581929-34.9023775819294
54285.179315.460210915263-30.2812109152627
55305.486331.981210915263-26.4952109152627
56305.957332.251710915263-26.2947109152627
57293.886324.853210915263-30.9672109152627
58289.441319.393710915263-29.9527109152627
59288.776313.244377581929-24.4683775819294
60299.149318.989710915263-19.8407109152627
61306.532317.20224397069-10.6702439706901
62309.914309.5622165070390.351783492960995
63313.468305.9340498403727.5339501596277
64314.901302.52788317370612.3731168262943
65309.16296.48196882933312.678031170667
66316.15296.79580216266619.3541978373336
67336.544313.31680216266623.2271978373336
68339.196313.58730216266625.6086978373337
69326.738306.18880216266620.5491978373336
70320.838300.72930216266620.1086978373337
71318.62294.57996882933324.040031170667
72331.533300.32530216266631.2076978373337
73335.378298.53783521809436.8401647819063


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
179.00208910280787e-050.0001800417820561570.999909979108972
182.4131030518827e-054.8262061037654e-050.999975868969481
191.40471110705488e-062.80942221410977e-060.999998595288893
201.22981276788471e-072.45962553576942e-070.999999877018723
219.12901214212345e-081.82580242842469e-070.999999908709879
223.42759698565856e-056.85519397131712e-050.999965724030143
237.32471563773426e-050.0001464943127546850.999926752843623
247.38444110392607e-050.0001476888220785210.99992615558896
252.67449358866237e-055.34898717732475e-050.999973255064113
261.19833611639213e-052.39667223278426e-050.999988016638836
278.58191700531684e-061.71638340106337e-050.999991418082995
283.39802193531959e-066.79604387063918e-060.999996601978065
291.6085746310344e-063.2171492620688e-060.999998391425369
309.95498387234975e-071.99099677446995e-060.999999004501613
315.33879055853094e-071.06775811170619e-060.999999466120944
323.06508845170268e-076.13017690340536e-070.999999693491155
337.2271282749216e-071.44542565498432e-060.999999277287173
344.34063808228959e-058.68127616457918e-050.999956593619177
350.0007487390206635840.001497478041327170.999251260979336
360.007949687786750960.01589937557350190.99205031221325
370.02835184616825310.05670369233650630.971648153831747
380.1327260471065510.2654520942131020.86727395289345
390.43261169266760.86522338533520.5673883073324
400.8094544814109590.3810910371780820.190545518589041
410.9428232820775130.1143534358449730.0571767179224866
420.9725160432635580.05496791347288380.0274839567364419
430.9818976179657620.0362047640684760.018102382034238
440.9900301451981530.01993970960369330.00996985480184666
450.996332896059230.007334207881540660.00366710394077033
460.9993068209756370.001386358048725430.000693179024362714
470.999877994823090.0002440103538199420.000122005176909971
480.9999702052699555.95894600895687e-052.97947300447843e-05
490.99999963260857.34783001564008e-073.67391500782004e-07
500.9999999990493141.90137277147092e-099.50686385735459e-10
510.9999999941955281.16089445035575e-085.80447225177874e-09
520.9999999159114551.68177090924744e-078.4088545462372e-08
530.9999994783068831.04338623465317e-065.21693117326586e-07
540.9999921984462211.56031075576671e-057.80155377883353e-06
550.9998929322448350.0002141355103308320.000107067755165416
560.9991325645684380.001734870863123350.000867435431561675


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level310.775NOK
5% type I error level340.85NOK
10% type I error level360.9NOK