Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 4707.37233564554 -889.595599244605X[t] + 0.153530771296594Y1[t] + 0.436558232697684Y2[t] + 0.0508654692781182Y3[t] -6720.22713821588M1[t] + 14266.9491999809M2[t] + 11667.1125103659M3[t] + 7644.99499046983M4[t] + 4714.7777808122M5[t] + 460.306602584105M6[t] + 3169.10551863843M7[t] -1444.75317412772M8[t] -2090.70678676465M9[t] + 2356.44218947412M10[t] + 5209.20853962815M11[t] + 14.0026261095115t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)4707.372335645543579.1491321.31520.1959260.097963
X-889.595599244605889.524958-1.00010.3232840.161642
Y10.1535307712965940.159480.96270.3414830.170742
Y20.4365582326976840.1436083.03990.004160.00208
Y30.05086546927811820.159970.3180.7521620.376081
M1-6720.227138215881491.209035-4.50665.6e-052.8e-05
M214266.94919998092354.1565826.060300
M311667.11251036592236.8427515.21596e-063e-06
M47644.994990469832523.6609123.02930.004280.00214
M54714.77778081222035.2686522.31650.0257350.012867
M6460.3066025841051983.6055890.23210.8176780.408839
M73169.105518638432204.8526221.43730.1584010.0792
M8-1444.753174127721755.2875-0.82310.4153390.20767
M9-2090.706786764651833.958534-1.140.2610680.130534
M102356.442189474122051.7213781.14850.2575760.128788
M115209.208539628151359.8925163.83060.0004410.000221
t14.002626109511524.0847590.58140.564240.28212


Multiple Linear Regression - Regression Statistics
Multiple R0.966482294440936
R-squared0.934088025467816
Adjusted R-squared0.907723235654942
F-TEST (value)35.4293750148430
F-TEST (DF numerator)16
F-TEST (DF denominator)40
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1786.11048781796
Sum Squared Residuals127607626.987733


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
11380711925.77498316041881.22501683961
22974330649.3280308136-906.328030813608
32559127985.5581544637-2394.55815446371
42909630024.2348482547-928.23484825475
52648226644.1479543565-162.147954356516
62240523321.2931432313-916.293143231263
72704424455.26998036692588.73001963306
81797018654.8329103538-684.832910353758
91873018447.5588283187282.441171681305
101968419300.0293253348383.970674665202
111978522183.4976460359-2398.49764603589
121847917458.93265106321020.06734893684
131069810644.814990837253.1850091627691
143195629886.36338417872069.63661582131
152950627100.99654539822405.00345460179
163450631601.30195616942904.69804383064
172716529464.4717049091-2299.47170490913
182673626155.1045244593580.895475540727
192369125861.5947258938-2170.59472589377
201815720233.5505688410-2076.55056884103
211732817400.8191890735-72.8191890734954
221820519163.8951683160-958.895168316047
232099521521.9143491152-526.91434911522
241738217095.7533835584286.246616441618
25936711097.4286805409-1730.42868054086
263112429432.68827745421691.31172254578
272655126504.432029474946.5679705251251
283065130884.7316510884-233.731651088411
292585927708.2924468138-1849.29244681385
302510024289.3854016936810.61459830635
312577825012.2184613964765.78153860364
322041819941.3612302805476.638769719473
331868818743.8649001903-55.8649001902982
342042420633.9429291065-209.94292910645
352477622739.35666644322036.64333355682
361981418882.1844997193931.815500280656
371273813402.3441838064-664.344183806407
383156631372.3039820705193.696017929485
393011128335.66676741041775.33323258962
403001931963.7589460073-1944.75894600734
413193428466.32675924863467.67324075139
422582624405.69701895521420.30298104484
432683527022.0620024819-187.062002481873
442020520008.0281724136196.971827586355
451778918487.9691426310-698.969142631017
462052019735.1325772427784.867422757295
472251821629.2313384057888.768661594281
481557217810.1294656591-2238.12946565911
491150911048.6371616551460.362838344891
502544728495.3163254830-3048.31632548296
512409025922.3465032528-1832.34650325282
522778627583.9725984801202.027401519862
532619525351.7611346719843.238865328108
542051622411.5199116607-1895.51991166066
552275923755.8548298611-996.85482986105
561902816940.22711811102087.77288188896
571697116425.7879397865545.212060213505


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
200.9091218553159530.1817562893680930.0908781446840466
210.8602757629444880.2794484741110240.139724237055512
220.871226839750940.257546320498120.12877316024906
230.8241656833224740.3516686333550530.175834316677526
240.7584010901873570.4831978196252850.241598909812643
250.7870890339080960.4258219321838080.212910966091904
260.7725637683718640.4548724632562720.227436231628136
270.6732450122822140.6535099754355710.326754987717786
280.6245444645744290.7509110708511420.375455535425571
290.8425172441452380.3149655117095250.157482755854762
300.7802936366012650.439412726797470.219706363398735
310.692407434535830.615185130928340.30759256546417
320.6390349007355570.7219301985288850.360965099264443
330.5398169435559050.920366112888190.460183056444095
340.452643955282090.905287910564180.54735604471791
350.4264831852291020.8529663704582040.573516814770898
360.2918475115798050.583695023159610.708152488420195
370.2330853311381730.4661706622763460.766914668861827


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 level00OK