Multiple Linear Regression - Estimated Regression Equation
BEL_20[t] = -204.722456427373 + 0.177400378019995Nikkei[t] + 0.220142962023709DJ_Indust[t] -0.0793121795843404Goudprijs[t] + 8.83568088071237Conjunct_Seizoenzuiver[t] -8.23572530490068Cons_vertrouw[t] + 18.5328439084293Alg_consumptie_index_BE[t] -280.1553727945Gem_rente_kasbon_5j[t] + 161.090413781246M1[t] + 247.445572641716M2[t] + 189.272612931734M3[t] + 111.726785113516M4[t] + 83.0601724822622M5[t] -3.16898498687954M6[t] + 12.8625451025933M7[t] + 4.30907126374565M8[t] + 35.700574039436M9[t] + 112.037528681405M10[t] + 84.5376550919719M11[t] + 22.318614447017t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)-204.722456427373567.980524-0.36040.7199790.359989
Nikkei0.1774003780199950.01511.826700
DJ_Indust0.2201429620237090.0387355.68331e-060
Goudprijs-0.07931217958434040.025185-3.14920.0027130.001356
Conjunct_Seizoenzuiver8.835680880712377.8939631.11930.2681580.134079
Cons_vertrouw-8.235725304900688.790611-0.93690.3531530.176576
Alg_consumptie_index_BE18.532843908429318.1314341.02210.3114470.155724
Gem_rente_kasbon_5j-280.155372794557.69116-4.85611.1e-056e-06
M1161.09041378124693.4761071.72330.0907710.045385
M2247.445572641716100.6772852.45780.0173480.008674
M3189.27261293173494.808281.99640.0511420.025571
M4111.72678511351692.8976721.20270.2345450.117273
M583.060172482262287.5021240.94920.3468920.173446
M6-3.1689849868795490.438848-0.0350.9721820.486091
M712.862545102593391.4980110.14060.8887470.444374
M84.3090712637456594.3133480.04570.9637330.481867
M935.70057403943691.7730.3890.6988580.349429
M10112.03752868140592.2755991.21420.2301710.115086
M1184.537655091971988.0557420.960.3414740.170737
t22.3186144470175.8369673.82370.0003540.000177


Multiple Linear Regression - Regression Statistics
Multiple R0.988447189712945
R-squared0.97702784685142
Adjusted R-squared0.968634175508669
F-TEST (value)116.400536422631
F-TEST (DF numerator)19
F-TEST (DF denominator)52
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation149.766092731832
Sum Squared Residuals1166353.89167231


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
12350.442457.19413196077-106.754131960772
22440.252549.12448662837-108.874486628374
32408.642625.97178134145-217.331781341454
42472.812747.03073202865-274.22073202865
52407.62562.79767991999-155.197679919987
62454.622574.70138828411-120.081388284106
72448.052556.89086760979-108.840867609793
82497.842450.7264947758647.1135052241398
92645.642558.1330649603387.5069350396716
102756.762612.99804019027143.761959809726
112849.272685.56989857376163.700101426239
122921.442700.82327186014220.616728139856
132981.852970.4099769572811.4400230427194
143080.583154.54727189964-73.9672718996395
153106.223147.43852908107-41.2185290810652
163119.312924.76125570302194.548744296976
173061.262921.63048091606139.629519083944
183097.312929.66638572503167.643614274971
193161.693059.96349556821101.726504431785
203257.163128.60208016773128.557919832274
213277.013353.1645764035-76.1545764034988
223295.323384.93807770034-89.6180777003413
233363.993577.88541387396-213.895413873962
243494.173654.62023521827-160.450235218271
253667.033812.5768870342-145.546887034203
263813.063976.84952769536-163.78952769536
273917.964003.99128282905-86.031282829049
283895.513985.23019143339-89.7201914333885
293801.063740.0918136670960.9681863329113
303570.123477.0832584611193.0367415388856
313701.613457.93546917912243.674530820884
323862.273631.36036248836230.90963751164
333970.13836.65793640225133.44206359775
344138.524124.8524503926713.6675496073332
354199.754050.88530692903148.864693070973
364290.894261.5869640353229.3030359646797
374443.914441.65027315012.25972684989876
384502.644485.9897769864616.6502230135373
394356.984301.576265050155.4037349498997
404591.274395.30283486492195.967165135077
414696.964585.94842480073111.011575199273
424621.44555.787428328465.6125716715979
434562.844597.77025661072-34.9302566107224
444202.524240.52368549951-38.0036854995115
454296.494285.9114926009810.5785073990201
464435.234509.52120170601-74.2912017060101
474105.184158.55265483927-53.3726548392649
484116.684097.476143397519.2038566024962
493844.493653.92798637897190.562013621027
503720.983664.3586127237556.6213872762538
513674.43524.29355076329150.106449236707
523857.623842.8953448999514.7246551000516
533801.063978.68360376993-177.623603769927
543504.373631.39353313422-127.023533134216
553032.63152.21281263012-119.612812630116
563047.033251.44229105332-204.412291053316
572962.343068.07875184762-105.738751847617
582197.822117.6359550997680.184044900241
592014.451969.4242906443345.025709355671
601862.831834.1177322205628.7122677794436
611905.411857.3707445186748.0392554813297
621810.991537.63032406642273.359675933582
631670.071530.99859093504139.071409064962
641864.441905.73964107007-41.2996410700661
652052.022030.8079969262121.2120030737858
662029.62108.78800606713-79.188006067132
672070.832152.84709840204-82.0170984020375
682293.412457.57508601523-164.165086015227
692443.272492.90417778533-49.6341777853266
702513.172586.87427491095-73.7042749109487
712466.922557.24243513966-90.322435139655
722502.662640.04565326821-137.385653268205


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
230.01990774155383930.03981548310767860.98009225844616
240.02874061050915390.05748122101830790.971259389490846
250.02619619902117430.05239239804234870.973803800978826
260.021055028973940.04211005794788010.97894497102606
270.0130647014279310.0261294028558620.98693529857207
280.0985010675728580.1970021351457160.901498932427142
290.3779272795075370.7558545590150740.622072720492463
300.894647354343110.210705291313780.10535264565689
310.861141895660010.2777162086799790.13885810433999
320.8118113113702170.3763773772595650.188188688629783
330.7411538831824250.5176922336351490.258846116817574
340.7564427614441810.4871144771116370.243557238555819
350.7096929323771640.5806141352456720.290307067622836
360.6279158476006440.7441683047987110.372084152399356
370.5926711587358170.8146576825283660.407328841264183
380.6338704557749660.7322590884500690.366129544225034
390.6971386858465320.6057226283069370.302861314153468
400.6086173060155790.7827653879688420.391382693984421
410.53663904467160.92672191065680.4633609553284
420.5133193424511820.9733613150976350.486680657548818
430.5352308886881710.9295382226236570.464769111311829
440.860847843844360.278304312311280.13915215615564
450.907978376545160.1840432469096790.0920216234548395
460.9103625662967190.1792748674065610.0896374337032807
470.9452388933006550.1095222133986910.0547611066993455
480.8920016953042510.2159966093914980.107998304695749
490.7760956642314860.4478086715370280.223904335768514


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level30.111111111111111NOK
10% type I error level50.185185185185185NOK