Multiple Linear Regression - Estimated Regression Equation
saldo_zichtrek[t] = + 32.8617038709678 -0.55318467741935crisis[t] -1.08223211917562M1[t] -1.72115552867384M2[t] -2.26926673387097M3[t] -0.965814874551973M4[t] -1.46756301523298M5[t] -0.99851115591398M6[t] -0.881859296594985M7[t] -0.751807437275987M8[t] -0.231355577956992M9[t] + 1.43949628136201M10[t] + 1.593148140681M11[t] + 0.0899481406810033t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)32.86170387096780.90880536.159200
crisis-0.553184677419350.761496-0.72640.4711690.235585
M1-1.082232119175621.019167-1.06190.2937160.146858
M2-1.721155528673841.07-1.60860.1144110.057206
M3-2.269266733870971.072621-2.11560.0397040.019852
M4-0.9658148745519731.070408-0.90230.3715050.185753
M5-1.467563015232981.068451-1.37350.17610.08805
M6-0.998511155913981.066752-0.9360.3540430.177022
M7-0.8818592965949851.065313-0.82780.4119710.205986
M8-0.7518074372759871.064134-0.70650.4833670.241683
M9-0.2313555779569921.063216-0.21760.8286830.414341
M101.439496281362011.062561.35470.1819760.090988
M111.5931481406811.0621661.49990.1403270.070163
t0.08994814068100330.0167035.38522e-061e-06


Multiple Linear Regression - Regression Statistics
Multiple R0.797953120470371
R-squared0.636729182468403
Adjusted R-squared0.53625002017243
F-TEST (value)6.33692765663034
F-TEST (DF numerator)13
F-TEST (DF denominator)47
p-value1.07600384402495e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.67922394172143
Sum Squared Residuals132.530273183172


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
129.83731.8694198924731-2.03241989247307
229.57131.3204446236559-1.74944462365591
330.16730.8622815591398-0.695281559139789
430.52432.2556815591398-1.73168155913979
530.99631.8438815591398-0.847881559139785
631.03332.4028815591398-1.36988155913979
731.19832.6094815591398-1.41148155913979
830.93732.8294815591398-1.89248155913979
931.64933.4398815591398-1.79088155913979
1033.11535.2006815591398-2.08568155913979
1134.10635.4442815591398-1.33828155913979
1233.92633.9410815591398-0.0150815591397881
1333.38232.94879758064520.433202419354821
1432.85132.39982231182800.451177688172041
1532.94831.94165924731181.00634075268817
1636.11233.33505924731182.77694075268817
1736.11332.92325924731183.18974075268817
1835.2133.48225924731181.72774075268817
1935.19333.68885924731181.50414075268817
2034.38333.90885924731180.474140752688173
2135.34934.51925924731180.829740752688169
2237.05836.28005924731180.77794075268817
2338.07636.52365924731181.55234075268817
2436.6335.02045924731181.60954075268817
2536.04534.02817526881722.01682473118279
2635.63833.47922.15880000000000
2735.11433.02103693548392.09296306451613
2835.46534.41443693548391.05056306451613
2935.25434.00263693548391.25136306451613
3035.29934.56163693548390.73736306451613
3135.91634.76823693548391.14776306451613
3236.68334.98823693548391.69476306451613
3337.28835.59863693548391.68936306451613
3438.53637.35943693548391.17656306451613
3538.97737.60303693548391.37396306451613
3636.40736.09983693548390.307163064516126
3734.95535.1075529569893-0.152552956989258
3834.95134.55857768817200.392422311827960
3932.6834.1004146236559-1.42041462365591
4034.79135.4938146236559-0.702814623655914
4134.17835.0820146236559-0.904014623655912
4235.21335.6410146236559-0.42801462365591
4334.87135.8476146236559-0.976614623655907
4435.29936.0676146236559-0.76861462365591
4535.44336.6780146236559-1.23501462365591
4637.10838.4388146236559-1.33081462365591
4736.41938.6824146236559-2.26341462365591
4834.47137.1792146236559-2.70821462365591
4933.86836.1869306451613-2.31893064516129
5034.38535.6379553763441-1.25295537634408
5133.64334.6266076344086-0.9836076344086
5234.62736.0200076344086-1.3930076344086
5332.91935.6082076344086-2.6892076344086
5435.536.1672076344086-0.667207634408602
5536.1136.3738076344086-0.263807634408602
5637.08636.59380763440860.492192365591397
5737.71137.20420763440860.506792365591399
5840.42738.96500763440861.46199236559140
5939.88439.20860763440860.675392365591399
6038.51237.70540763440860.806592365591398
6138.76736.7131236559142.05387634408602


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
170.4898997989114770.9797995978229530.510100201088523
180.3153873497804850.630774699560970.684612650219515
190.1868311394651380.3736622789302760.813168860534862
200.1388583737439860.2777167474879720.861141626256014
210.09301796763721750.1860359352744350.906982032362782
220.07015612536746180.1403122507349240.929843874632538
230.0416129376709370.0832258753418740.958387062329063
240.04468041607892220.08936083215784430.955319583921078
250.05666616684571330.1133323336914270.943333833154287
260.05311800563326610.1062360112665320.946881994366734
270.1036890068711310.2073780137422620.896310993128869
280.2987183160389960.5974366320779910.701281683961004
290.5319413766330850.936117246733830.468058623366915
300.5521135056621960.895772988675610.447886494337804
310.5023594139081980.9952811721836040.497640586091802
320.4093208434576010.8186416869152010.5906791565424
330.3334036386968610.6668072773937210.66659636130314
340.251906794856510.503813589713020.74809320514349
350.2249308164388970.4498616328777930.775069183561103
360.2701292213393020.5402584426786030.729870778660698
370.3246136673540810.6492273347081610.67538633264592
380.2956454573409190.5912909146818380.70435454265908
390.4086304635863160.8172609271726330.591369536413684
400.4783830607359090.9567661214718170.521616939264091
410.764563172784570.470873654430860.23543682721543
420.8437145997314850.3125708005370290.156285400268515
430.8665658212290260.2668683575419470.133434178770974
440.8658503393298470.2682993213403060.134149660670153


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 level20.0714285714285714OK