Multiple Linear Regression - Estimated Regression Equation
Spaar[t] = + 35.2908642381885 + 0.435286320955128Alg_E[t] + 1.76715415124219M1[t] + 2.30585896286539M2[t] -0.242370093898710M3[t] + 0.735286320955132M4[t] + 0.834127782758336M5[t] + 2.76941410371346M6[t] + 1.44352863209552M7[t] -1.52234358514615M8[t] -1.43528632095512M9[t] -0.92704400981474M10[t] + 0.0176431604775675M11[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)35.29086423818852.32391315.18600
Alg_E0.4352863209551280.0456229.541200
M11.767154151242192.3098450.76510.4459090.222954
M22.305858962865392.3671370.97410.3321770.166089
M3-0.2423700938987102.365307-0.10250.9185750.459287
M40.7352863209551322.3636170.31110.7563360.378168
M50.8341277827583362.3639210.35290.7248830.362441
M62.769414103713462.3632171.17190.2438230.121911
M71.443528632095522.3631810.61080.5425880.271294
M8-1.522343585146152.363811-0.6440.5209270.260464
M9-1.435286320955122.363617-0.60720.5449650.272483
M10-0.927044009814742.364766-0.3920.6958130.347907
M110.01764316047756752.3632870.00750.9940570.497029


Multiple Linear Regression - Regression Statistics
Multiple R0.687725442575715
R-squared0.472966284365964
Adjusted R-squared0.414406982628848
F-TEST (value)8.07670635297544
F-TEST (DF numerator)12
F-TEST (DF denominator)108
p-value1.25376264925592e-10
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation5.28422435604139
Sum Squared Residuals3015.68692085796


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
16251.422466980949910.5775330190501
26454.57288971830399.42711028169615
36254.63637858727057.36362141272949
46456.04932132307957.95067867692052
56455.71287646392768.28712353607242
66957.648162784882711.3518372151173
76958.063422597085310.9365774029147
86555.53283670079879.46716329920128
95657.3610392488103-1.36103924881026
105860.0457131647263-2.04571316472628
115360.5551140140635-7.55511401406346
126259.66689821167562.33310178832436
135557.9517617952768-2.95176179527681
146059.36103924881030.638960751189743
155957.68338283395641.31661716604359
165859.0963255697654-1.09632556976538
175360.0657396734789-7.06573967347885
185756.77759014297240.222409857027564
195755.01641835039941.98358164960064
205350.30940084933722.69059915066282
215451.70231707639362.29768292360641
225352.2105593875340.789440612466026
235752.2846739159164.71532608408397
245750.09059915066286.90940084933718
255548.81074905521916.18925094478089
264944.12601801538084.87398198461923
275041.14250263766158.85749736233846
284949.5200265087526-0.520026508752561
295453.9717311801070.0282688198929497
305856.77759014297241.22240985702756
315856.75756363421991.24243636578013
325252.0505461331577-0.0505461331576936
335653.44346236021412.55653763978590
345253.9517046713545-1.95170467135449
355952.71996023687126.28003976312884
365350.5258854716182.47411452838206
375252.7283259438153-0.728325943815265
385354.1376033973487-1.13760339734872
395152.0246606615397-1.02466066153974
405049.95531282970770.0446871702923097
415646.57186372386999.42813627613013
425247.20129108195964.79870891804039
434641.95782872174554.04217127825449
444846.3918239607411.60817603925898
454649.525885471618-3.52588547161795
464847.85769617798270.142303822017309
474847.49652438540960.503475614590386
484948.34945386684230.650546133157697
495353.5988985857255-0.598898585725522
504849.3494538668423-1.34945386684231
515152.4599469824949-1.45994698249487
524853.4376033973487-5.43760339734872
535055.2775901429724-5.27759014297243
545558.518735426793-3.51873542679295
555256.3222773132647-4.32227731326474
565352.05054613315770.949453866842307
575250.39645811352821.60354188647180
585554.38699099230960.613009007690384
595351.41410127400581.58589872599423
605353.1376033973487-0.137603397348714
615654.46947122763581.53052877236422
625451.96117179257312.03882820742692
635249.84822905676412.15177094323590
645551.69645811352823.3035418864718
655451.79529957533142.20470042466859
665954.60115853819684.3988414618032
675655.01641835039940.98358164960064
685649.00354188647186.9964581135282
695144.73773594111156.26226405888846
705344.81069193129688.1893080687032
715244.88480645967887.11519354032115
725147.04359490397693.95640509602308
734644.45788584566781.54211415433218
744950.6553128297077-1.65531282970769
754648.1070837729436-2.10708377294359
765550.8258854716184.17411452838205
775752.23058589628654.76941410371346
785353.7305858962865-0.730585896286538
795251.09884146180320.901158538196794
805348.13296924456154.86703075543846
815048.22002650875261.77997349124744
825450.46941410371353.53058589628654
835352.71996023687120.280039763128846
845050.525885471618-0.525885471617945
855153.1636122647704-2.16361226477039
865256.3140350021244-4.31403500212436
874753.3305196244051-6.33051962440513
885150.39059915066280.609400849337182
894953.1011585381968-4.10115853819679
905355.471731180107-2.47173118010705
915252.8399867456237-0.839986745623718
924552.921118775068-7.92111877506795
935352.13760339734870.862396602651282
945153.0811320294442-2.08113202944423
954852.7199602368712-4.71996023687116
964848.3494538668423-0.349453866842303
974850.1166080180845-2.11660801808450
984851.0905991506628-3.09059915066282
994042.883647921482-2.88364792148205
1004346.4730222620667-3.47302226206666
1014045.7012910819596-5.70129108195961
1023949.3777226867353-10.3777226867353
1033948.9224098570276-9.92240985702757
1043643.7801060350103-7.78010603501026
1054141.2554453734705-0.25544537347051
1063939.5872560798353-0.587256079835253
1074039.22608428726220.773915712737824
1083943.5613043363359-4.56130433633589
1094646.1990311294883-0.199031129488339
1104045.4318769782462-5.43187697824615
1113742.883647921482-5.88364792148205
1123742.5554453734705-5.55544537347051
1134446.5718637238699-2.57186372386987
1144145.8954321190942-4.89543211909423
1154045.0048329684314-5.00483296843141
1163646.8271102816962-10.8271102816962
1173848.2200265087526-10.2200265087526
1184349.5988414618032-6.5988414618032
1194250.9788149530506-8.97881495305064
1204555.7493213230795-10.7493213230795
1214657.0811891533665-11.0811891533665


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
160.02152815958723690.04305631917447390.978471840412763
170.07536491186578350.1507298237315670.924635088134216
180.5370809620441830.9258380759116340.462919037955817
190.8465342129554770.3069315740890460.153465787044523
200.9416340759336230.1167318481327550.0583659240663773
210.9115184767896340.1769630464207330.0884815232103664
220.8833322956000770.2333354087998450.116667704399923
230.8503678637557970.2992642724884060.149632136244203
240.8306860587516190.3386278824967620.169313941248381
250.7987254233091240.4025491533817530.201274576690876
260.8461870299330020.3076259401339960.153812970066998
270.8423037856430960.3153924287138090.157696214356904
280.8482583290666830.3034833418666350.151741670933317
290.8034401608802960.3931196782394070.196559839119704
300.7781758765713090.4436482468573830.221824123428691
310.758001488535670.4839970229286610.241998511464330
320.7503583926758630.4992832146482730.249641607324136
330.7006760184866080.5986479630267840.299323981513392
340.6447104104731420.7105791790537160.355289589526858
350.6609199938606540.6781600122786920.339080006139346
360.6273105780648710.7453788438702590.372689421935129
370.6054394243400190.7891211513199620.394560575659981
380.5867970449465250.826405910106950.413202955053475
390.5855207849201650.828958430159670.414479215079835
400.5445913968991070.9108172062017850.455408603100893
410.5890943236108380.8218113527783230.410905676389162
420.580152809963750.8396943800725010.419847190036250
430.5953778353796530.8092443292406940.404622164620347
440.569661394216680.860677211566640.43033860578332
450.5641501906469610.8716996187060780.435849809353039
460.50390926558590.99218146882820.4960907344141
470.4528612760613770.9057225521227530.547138723938623
480.4236889234097060.8473778468194110.576311076590294
490.3841366472185370.7682732944370740.615863352781463
500.3676626114786680.7353252229573360.632337388521332
510.3478090232218320.6956180464436650.652190976778168
520.3692380558656430.7384761117312850.630761944134357
530.392218184871160.784436369742320.60778181512884
540.3886012483696030.7772024967392050.611398751630397
550.4005684316940390.8011368633880780.599431568305961
560.3610792140621060.7221584281242120.638920785937894
570.3110294182722980.6220588365445950.688970581727702
580.2634102778360130.5268205556720260.736589722163987
590.2224005844824860.4448011689649720.777599415517514
600.1906284420316820.3812568840633640.809371557968318
610.163777703555970.327555407111940.83622229644403
620.1451045426871460.2902090853742920.854895457312854
630.1342449016997980.2684898033995950.865755098300202
640.1174756532823040.2349513065646090.882524346717696
650.09797789421671550.1959557884334310.902022105783284
660.1083166527376430.2166333054752870.891683347262357
670.0955865909167780.1911731818335560.904413409083222
680.1527049387206220.3054098774412450.847295061279378
690.1656350053601130.3312700107202250.834364994639887
700.215024321751420.430048643502840.78497567824858
710.2716244997008610.5432489994017220.728375500299139
720.2903760501612360.5807521003224720.709623949838764
730.2837437718387380.5674875436774760.716256228161262
740.2591782536786670.5183565073573340.740821746321333
750.2488882795746630.4977765591493250.751111720425337
760.2610613562706520.5221227125413040.738938643729348
770.3191799659006140.6383599318012280.680820034099386
780.3208202206514060.6416404413028130.679179779348594
790.327701333961260.655402667922520.67229866603874
800.5979903228867620.8040193542264760.402009677113238
810.5875340341282320.8249319317435360.412465965871768
820.6315778316698490.7368443366603020.368422168330151
830.6344059382362640.7311881235274730.365594061763736
840.6352978075821240.7294043848357530.364702192417876
850.599109490223560.8017810195528790.400890509776440
860.5536804842079170.8926390315841670.446319515792083
870.5287346722656280.9425306554687440.471265327734372
880.550685724235010.898628551529980.44931427576499
890.5120090553860890.9759818892278220.487990944613911
900.5867472958397910.8265054083204180.413252704160209
910.7128935936872970.5742128126254060.287106406312703
920.7576420106720730.4847159786558550.242357989327927
930.9055607610146620.1888784779706760.094439238985338
940.9435577070962470.1128845858075060.0564422929037531
950.9523097816370320.09538043672593610.0476902183629681
960.9763239278669450.04735214426611080.0236760721330554
970.9666318748668970.06673625026620680.0333681251331034
980.9840406889134740.03191862217305280.0159593110865264
990.9786008868531060.04279822629378720.0213991131468936
1000.9864020748405780.02719585031884360.0135979251594218
1010.986904952703450.02619009459309830.0130950472965491
1020.9826275430161580.03474491396768370.0173724569838418
1030.9678114326712270.06437713465754690.0321885673287735
1040.9274466623849260.1451066752301480.0725533376150739
1050.9376891768969630.1246216462060740.0623108231030372


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level70.0777777777777778NOK
10% type I error level100.111111111111111NOK