Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 46071.1845929129 + 0.626558835163595X[t] + 0.336631429022401`yt-1`[t] -0.0518462980042751`yt-2`[t] + 0.0698520891405935`yt-3`[t] -0.0690390803881129`yt-4`[t] -0.0228142693555400`yt-5`[t] -0.243418679323981`yt-6`[t] -16257.540984572M1[t] -29962.1038916211M2[t] -30104.4363888772M3[t] -26010.3620742694M4[t] -21521.0979193019M5[t] -14857.4290050065M6[t] -9613.76497647236M7[t] -6977.30610908971M8[t] -5770.32808988139M9[t] -3321.17746051666M10[t] -1454.50789014262M11[t] -481.174713519072t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)46071.184592912913809.7168233.33610.0016880.000844
X0.6265588351635950.0679259.224300
`yt-1`0.3366314290224010.1137682.95890.0048640.002432
`yt-2`-0.05184629800427510.124676-0.41580.6794550.339728
`yt-3`0.06985208914059350.1247370.560.5781990.2891
`yt-4`-0.06903908038811290.123304-0.55990.5782590.289129
`yt-5`-0.02281426935554000.122964-0.18550.8536250.426812
`yt-6`-0.2434186793239810.087382-2.78570.0077330.003866
M1-16257.5409845723917.093507-4.15040.0001427.1e-05
M2-29962.10389162114202.85066-7.12900
M3-30104.43638887724208.413418-7.153400
M4-26010.36207426943692.10032-7.044900
M5-21521.09791930192663.7328-8.079300
M6-14857.42900500652857.27529-5.19994e-062e-06
M7-9613.764976472362292.691171-4.19320.0001246.2e-05
M8-6977.306109089712142.876229-3.2560.0021240.001062
M9-5770.328089881392018.424177-2.85880.006370.003185
M10-3321.177460516662022.570357-1.64210.1073980.053699
M11-1454.507890142621657.246921-0.87770.3846870.192343
t-481.17471351907284.364183-5.70351e-060


Multiple Linear Regression - Regression Statistics
Multiple R0.996201542618571
R-squared0.992417513515621
Adjusted R-squared0.989285616924248
F-TEST (value)316.874291523239
F-TEST (DF numerator)19
F-TEST (DF denominator)46
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2531.77697481877
Sum Squared Residuals294855153.910234


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1337302334182.3936850913119.60631490889
2349420348213.4484171591206.55158284101
3336923341900.468061574-4977.46806157396
4330758332279.700038611-1521.70003861141
5321002323166.254835277-2164.25483527702
6320820321929.166038643-1109.16603864280
7327032326836.598873915195.401126084623
8324047323806.749403543240.250596456604
9316735319479.040238083-2744.04023808320
10315710318101.459009824-2391.45900982406
11313427317014.503459581-3587.50345958097
12310527313888.55918022-3361.55918022006
13330962328292.6819070672669.31809293342
14339015338017.323828611997.676171389256
15341332342842.360036983-1510.36003698263
16339092342421.208319436-3329.20831943553
17323308325374.687756089-2066.68775608868
18325849326257.511723956-408.511723956002
19330675330340.823332562334.176667438436
20332225330123.1892400642101.81075993640
21331735329264.6268059922470.37319400763
22328047326297.5051303471749.49486965282
23326165325936.595958109228.404041890979
24327081326162.887375317918.112624682797
25346764346754.7732273269.22677267383943
26344190344133.12883041556.8711695849656
27343333340630.8909413562702.10905864447
28345777343590.479909662186.52009034034
29344094341508.4305546202585.56944537954
30348609348322.530233225286.469766775032
31354846354529.1133241316.886675900142
32356427357559.466306435-1132.46630643475
33353467354645.014911777-1178.01491177684
34355996354597.0235745051398.97642549531
35352487351792.189410360694.810589640337
36355178353726.7034280131451.29657198703
37374556375969.728003829-1413.72800382922
38375021373941.2631732981079.73682670212
39375787372483.7298086983303.27019130241
40372720369113.1105181163606.88948188375
41364431360183.1958779194247.80412208104
42370490367322.7376787343167.26232126571
43376974374282.308630822691.69136918042
44377632376886.579680783745.420319217177
45378205374916.8685839273288.13141607309
46370861370662.490357632198.509642368109
47369167366677.3964837692489.60351623071
48371551369629.9778049211921.02219507947
49382842383469.928717746-627.928717746472
50381903383974.434894233-2071.43489423252
51384502383920.116739475581.883260525253
52392058390099.3956839781958.60431602236
53384359385279.304395970-920.304395970423
54388884388693.171047198190.828952802351
55386586390124.155838604-3538.15583860362
56387495389450.015369175-1955.01536917543
57385705387541.449460221-1836.44946022068
58378670379625.521927692-955.521927692172
59377367377192.314688181174.685311818939
60376911377839.872211529-928.872211529229
61389827393583.494458940-3756.49445894046
62387820389089.400856285-1269.40085628483
63387267387366.434411916-99.4344119155428
64380575383476.105530200-2901.10553019951
65372402374084.126580124-1682.12658012445
66376740378866.883278244-2126.88327824429


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
230.005865192737358340.01173038547471670.994134807262642
240.001435930054551800.002871860109103600.998564069945448
250.8079308993911020.3841382012177970.192069100608898
260.9422605428187330.1154789143625350.0577394571812674
270.9273291613505430.1453416772989130.0726708386494567
280.8790964682356830.2418070635286350.120903531764317
290.818528125197860.362943749604280.18147187480214
300.8457248939470490.3085502121059030.154275106052951
310.8174058841351030.3651882317297940.182594115864897
320.7366713370527230.5266573258945530.263328662947277
330.7651928602305040.4696142795389920.234807139769496
340.7059666278923520.5880667442152970.294033372107648
350.7046893639097630.5906212721804750.295310636090237
360.7324517604974330.5350964790051350.267548239502567
370.8564112753376930.2871774493246150.143588724662307
380.8747807633438670.2504384733122670.125219236656133
390.7920748063129820.4158503873740350.207925193687018
400.6917013659993530.6165972680012940.308298634000647
410.5997005492494190.8005989015011620.400299450750581
420.5131314376876330.9737371246247340.486868562312367
430.3633519240882360.7267038481764720.636648075911764


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level10.0476190476190476NOK
5% type I error level20.0952380952380952NOK
10% type I error level20.0952380952380952OK