Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 23742.1551966182 + 6615.98887332214X[t] + 0.902769444396003Y1[t] + 0.187257523728878Y2[t] + 0.0782568056750277Y3[t] -0.261594494752365Y4[t] -4817.45387065382M1[t] -9797.82497078342M2[t] -7592.9204932169M3[t] -10990.3561951020M4[t] -7520.4387858831M5[t] + 15571.2127480332M6[t] -1051.92432274379M7[t] -10008.0686935439M8[t] -15844.4644416581M9[t] -10334.1572687118M10[t] -1324.53698797528M11[t] + 144.895467430072t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)23742.155196618212205.5788931.94520.0591790.029589
X6615.988873322142553.859072.59060.0135140.006757
Y10.9027694443960030.1477666.109500
Y20.1872575237288780.2063730.90740.3699280.184964
Y30.07825680567502770.206250.37940.7064830.353241
Y4-0.2615944947523650.162849-1.60640.1164740.058237
M1-4817.453870653822604.005125-1.850.0720990.036049
M2-9797.824970783422998.209807-3.26790.0023030.001152
M3-7592.92049321692926.792723-2.59430.0133920.006696
M4-10990.35619510202565.546722-4.28380.0001216e-05
M5-7520.43878588312775.472514-2.70960.0100490.005025
M615571.21274803322595.6642525.99891e-060
M7-1051.924322743793485.975333-0.30180.7644810.382241
M8-10008.06869354394463.886007-2.2420.0308770.015439
M9-15844.46444165815372.774649-2.9490.0054290.002714
M10-10334.15726871183144.926122-3.2860.0021910.001096
M11-1324.536987975282822.16277-0.46930.6415130.320756
t144.89546743007282.5290971.75570.08720.0436


Multiple Linear Regression - Regression Statistics
Multiple R0.987881224556706
R-squared0.975909313831657
Adjusted R-squared0.96513190159845
F-TEST (value)90.5513580360972
F-TEST (DF numerator)17
F-TEST (DF denominator)38
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3444.73750487735
Sum Squared Residuals450916226.145328


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1277026275450.5476940241575.45230597623
2274960272203.663525562756.33647443986
3270073272300.834214719-2227.83421471922
4267063264453.5041087052609.49589129474
5264916264280.714741103635.285258896512
6287182285173.3838157322008.61618426771
7291109289437.0240686341671.97593136619
8292223288959.8088641743263.19113582563
9288109287313.463455624795.536544375801
10281400283945.928938919-2545.92893891904
11282579285333.283532642-2754.28353264171
12280113285997.405670592-5884.4056705917
13280331279870.569280101460.430719898766
14276759276617.422571949141.577428050907
15275139275281.951009628-142.951009628418
16274275270560.1924081893714.80759181126
17271234272755.094386712-1521.09438671162
18289725293892.16851721-4167.16851720995
19290649293893.755781926-3244.75578192557
20292223289367.2834138562855.71658614362
21278429280896.334769534-2467.33476953379
22269749269628.644522239120.355477761316
23265784268245.554109713-2461.55410971316
24268957263018.88629995938.11370009986
25264099263397.504649515701.495350485206
26255121256730.89515868-1609.89515868026
27253276251351.4649977151924.53500228535
28245980243541.9061964932438.09380350746
29235295240792.859529705-5497.85952970512
30258479255221.2956919713257.70430802932
31260916257583.6944350713332.30556492931
32254586256386.292562900-1800.29256289958
33250566250046.051243715519.948756285099
34243345245012.685661507-1667.68566150673
35247028245762.6566426651265.34335733471
36248464250546.103175904-2082.10317590375
37244962248346.108629851-3384.10862985125
38237003242795.229868860-5792.22986885955
39237008236453.036206586554.963793413793
40225477231064.922160057-5587.92216005662
41226762224564.0948652492197.90513475080
42247857248883.855964289-1026.85596428925
43248256250786.474509755-2530.47450975508
44246892249402.634192042-2510.63419204164
45245021243869.1505311271151.84946887290
46246186242092.7408773364093.25912266446
47255688251737.505714983950.49428502015
48264242262213.6048536042028.39514639559
49268270267623.269746509646.73025349105
50272969268464.7888749514504.21112504904
51273886273994.713571351-108.713571351506
52267353270527.475126557-3174.47512655684
53271916267730.2364772314185.76352276943
54292633292705.296010798-72.296010797836
55295804295033.051204615770.948795385147
56293222295029.980967028-1807.98096702804


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
210.01590909602088240.03181819204176490.984090903979118
220.005071234106339580.01014246821267920.99492876589366
230.006914394179285660.01382878835857130.993085605820714
240.005819565339534630.01163913067906930.994180434660465
250.006797665661356620.01359533132271320.993202334338643
260.02438050139003340.04876100278006680.975619498609967
270.0396585525665960.0793171051331920.960341447433404
280.1548944111493580.3097888222987170.845105588850642
290.3797468943931110.7594937887862230.620253105606889
300.4251999150339640.8503998300679270.574800084966036
310.6122308122475460.7755383755049080.387769187752454
320.6014762332916170.7970475334167660.398523766708383
330.5319939291526550.9360121416946910.468006070847345
340.3762021307157170.7524042614314350.623797869284283
350.3580060886714130.7160121773428250.641993911328587


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level60.4NOK
10% type I error level70.466666666666667NOK