Multiple Linear Regression - Estimated Regression Equation

cultuurbestedingen[t] = + 110.49 -1.72600000000004M1[t] -1.344M2[t] -1.28M3[t] -0.764000000000003M4[t] -0.722000000000002M5[t] -0.384000000000005M6[t] -0.216000000000002M7[t] + 0.165999999999995M8[t] + 1.496M9[t] + 1.7M10[t] -0.1875M11[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	110.49	3.049833	36.2282	0	0
M1	-1.72600000000004	4.09178	-0.4218	0.67512	0.33756
M2	-1.344	4.09178	-0.3285	0.744052	0.372026
M3	-1.28	4.09178	-0.3128	0.75583	0.377915
M4	-0.764000000000003	4.09178	-0.1867	0.852705	0.426352
M5	-0.722000000000002	4.09178	-0.1765	0.860714	0.430357
M6	-0.384000000000005	4.09178	-0.0938	0.925639	0.462819
M7	-0.216000000000002	4.09178	-0.0528	0.958129	0.479064
M8	0.165999999999995	4.09178	0.0406	0.967815	0.483907
M9	1.496	4.09178	0.3656	0.716331	0.358166
M10	1.7	4.09178	0.4155	0.679732	0.339866
M11	-0.1875	4.313115	-0.0435	0.965513	0.482757

Multiple Linear Regression - Regression Statistics
Multiple R	0.184116543409472
R-squared	0.0338989015570519
Adjusted R-squared	-0.197125274157566
F-TEST (value)	0.146733134972536
F-TEST (DF numerator)	11
F-TEST (DF denominator)	46
p-value	0.999225903166059
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	6.09966569825223
Sum Squared Residuals	1711.472395

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	101.76	108.764	-7.00400000000017
2	102.37	109.146	-6.776
3	102.38	109.21	-6.83
4	102.86	109.726	-6.866
5	102.87	109.768	-6.898
6	102.92	110.106	-7.186
7	102.95	110.274	-7.324
8	103.02	110.656	-7.636
9	104.08	111.986	-7.906
10	104.16	112.19	-8.03
11	104.24	110.3025	-6.06250000000001
12	104.33	110.49	-6.16
13	104.73	108.764	-4.03399999999995
14	104.86	109.146	-4.286
15	105.03	109.21	-4.18
16	105.62	109.726	-4.106
17	105.63	109.768	-4.138
18	105.63	110.106	-4.476
19	105.94	110.274	-4.334
20	106.61	110.656	-4.046
21	107.69	111.986	-4.296
22	107.78	112.19	-4.41
23	107.93	110.3025	-2.37249999999999
24	108.48	110.49	-2.01
25	108.14	108.764	-0.623999999999959
26	108.48	109.146	-0.665999999999996
27	108.48	109.21	-0.729999999999996
28	108.89	109.726	-0.835999999999999
29	108.93	109.768	-0.837999999999993
30	109.21	110.106	-0.896000000000003
31	109.47	110.274	-0.804
32	109.8	110.656	-0.856
33	111.73	111.986	-0.255999999999997
34	111.85	112.19	-0.340000000000002
35	112.12	110.3025	1.8175
36	112.15	110.49	1.66
37	112.17	108.764	3.40600000000004
38	112.67	109.146	3.524
39	112.8	109.21	3.59
40	113.44	109.726	3.714
41	113.53	109.768	3.762
42	114.53	110.106	4.424
43	114.51	110.274	4.236
44	115.05	110.656	4.394
45	116.67	111.986	4.684
46	117.07	112.19	4.87999999999999
47	116.92	110.3025	6.6175
48	117	110.49	6.51
49	117.02	108.764	8.25600000000004
50	117.35	109.146	8.204
51	117.36	109.21	8.15
52	117.82	109.726	8.094
53	117.88	109.768	8.112
54	118.24	110.106	8.134
55	118.5	110.274	8.226
56	118.8	110.656	8.144
57	119.76	111.986	7.774
58	120.09	112.19	7.9

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
15	0.0645893929316011	0.129178785863202	0.935410607068399
16	0.0359893264042392	0.0719786528084784	0.96401067359576
17	0.0213879206131235	0.0427758412262469	0.978612079386877
18	0.0136170394310904	0.0272340788621809	0.98638296056891
19	0.0101066555341159	0.0202133110682319	0.989893344465884
20	0.00963159584388178	0.0192631916877636	0.990368404156118
21	0.00996493520835897	0.0199298704167179	0.99003506479164
22	0.0112566868735289	0.0225133737470579	0.98874331312647
23	0.0110864841604224	0.0221729683208448	0.988913515839578
24	0.0121488516846592	0.0242977033693185	0.98785114831534
25	0.0209377049293235	0.041875409858647	0.979062295070677
26	0.0325552412018383	0.0651104824036767	0.967444758798162
27	0.0471685673852667	0.0943371347705333	0.952831432614733
28	0.0659306624002628	0.131861324800526	0.934069337599737
29	0.0923365843578947	0.184673168715789	0.907663415642105
30	0.140624188991064	0.281248377982127	0.859375811008936
31	0.21020083475561	0.42040166951122	0.78979916524439
32	0.312124005241856	0.624248010483713	0.687875994758144
33	0.444300268001595	0.88860053600319	0.555699731998405
34	0.613391200454307	0.773217599091386	0.386608799545693
35	0.662892803744851	0.674214392510297	0.337107196255149
36	0.701594229772469	0.596811540455062	0.298405770227531
37	0.766452204323638	0.467095591352723	0.233547795676362
38	0.810691125505355	0.378617748989289	0.189308874494645
39	0.839769048191785	0.32046190361643	0.160230951808215
40	0.856206312719428	0.287587374561144	0.143793687280572
41	0.86615000140447	0.267699997191061	0.133849998595531
42	0.853261402125933	0.293477195748134	0.146738597874067
43	0.838073030879996	0.323853938240007	0.161926969120004

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	9	0.310344827586207	NOK
10% type I error level	12	0.413793103448276	NOK