Multiple Linear Regression - Estimated Regression Equation

cultuurbesteding[t] = + 110.49 -1.72599999999997M1[t] -1.34400000000002M2[t] -1.28000000000001M3[t] -0.764000000000012M4[t] -0.72200000000001M5[t] -0.384000000000014M6[t] -0.216000000000015M7[t] + 0.165999999999983M8[t] + 1.49599999999999M9[t] + 1.69999999999998M10[t] + 1.78399999999999M11[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	3.084974	35.8155	0	0
M1	-1.72599999999997	4.138928	-0.417	0.678565	0.339283
M2	-1.34400000000002	4.138928	-0.3247	0.746833	0.373416
M3	-1.28000000000001	4.138928	-0.3093	0.758492	0.379246
M4	-0.764000000000012	4.138928	-0.1846	0.854346	0.427173
M5	-0.72200000000001	4.138928	-0.1744	0.862268	0.431134
M6	-0.384000000000014	4.138928	-0.0928	0.926475	0.463237
M7	-0.216000000000015	4.138928	-0.0522	0.958601	0.4793
M8	0.165999999999983	4.138928	0.0401	0.968178	0.484089
M9	1.49599999999999	4.138928	0.3614	0.719386	0.359693
M10	1.69999999999998	4.138928	0.4107	0.683134	0.341567
M11	1.78399999999999	4.138928	0.431	0.668417	0.334209

Multiple Linear Regression - Regression Statistics
Multiple R	0.206383754586892
R-squared	0.0425942541573825
Adjusted R-squared	-0.181479431039826
F-TEST (value)	0.190090389774663
F-TEST (DF numerator)	11
F-TEST (DF denominator)	47
p-value	0.997475740470135
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	6.16994886009358
Sum Squared Residuals	1789.20864000000

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	101.76	108.764000000000	-7.00399999999979
2	102.37	109.146	-6.77599999999999
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	112.274	-8.03400000000001
12	104.33	110.49	-6.16000000000002
13	104.73	108.764	-4.03400000000005
14	104.86	109.146	-4.28600000000000
15	105.03	109.21	-4.18
16	105.62	109.726	-4.10600000000000
17	105.63	109.768	-4.13800000000001
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	112.274	-4.34400000000000
24	108.48	110.49	-2.01000000000001
25	108.14	108.764	-0.624000000000049
26	108.48	109.146	-0.665999999999991
27	108.48	109.21	-0.729999999999995
28	108.89	109.726	-0.836
29	108.93	109.768	-0.837999999999997
30	109.21	110.106	-0.896000000000005
31	109.47	110.274	-0.804
32	109.8	110.656	-0.856
33	111.73	111.986	-0.255999999999996
34	111.85	112.19	-0.340000000000002
35	112.12	112.274	-0.153999999999998
36	112.15	110.49	1.65999999999999
37	112.17	108.764	3.40599999999995
38	112.67	109.146	3.52400000000001
39	112.8	109.21	3.59
40	113.44	109.726	3.714
41	113.53	109.768	3.76200000000000
42	114.53	110.106	4.424
43	114.51	110.274	4.23600000000001
44	115.05	110.656	4.394
45	116.67	111.986	4.684
46	117.07	112.19	4.88
47	116.92	112.274	4.646
48	117	110.49	6.50999999999999
49	117.02	108.764	8.25599999999994
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	8.11199999999999
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
59	120.16	112.274	7.886

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
15	0.0625431275149165	0.125086255029833	0.937456872485083
16	0.0343463683012999	0.0686927366025997	0.9656536316987
17	0.0200632531385263	0.0401265062770526	0.979936746861474
18	0.0124966583389785	0.024993316677957	0.987503341661021
19	0.00904181575334084	0.0180836315066817	0.99095818424666
20	0.00838309046924735	0.0167661809384947	0.991616909530753
21	0.00837777033006432	0.0167555406601286	0.991622229669936
22	0.00906583787679538	0.0181316757535908	0.990934162123205
23	0.0106933044746504	0.0213866089493007	0.98930669552535
24	0.011628981160812	0.023257962321624	0.988371018839188
25	0.0199113719446392	0.0398227438892784	0.98008862805536
26	0.0307257853942331	0.0614515707884661	0.969274214605767
27	0.0441204005104185	0.088240801020837	0.955879599489582
28	0.060990700536247	0.121981401072494	0.939009299463753
29	0.0843838260014154	0.168767652002831	0.915616173998585
30	0.126727756521352	0.253455513042704	0.873272243478648
31	0.187037658629354	0.374075317258708	0.812962341370646
32	0.274353474425008	0.548706948850015	0.725646525574992
33	0.390595457388951	0.781190914777902	0.609404542611049
34	0.541988045063532	0.916023909872936	0.458011954936468
35	0.693945213381106	0.612109573237788	0.306054786618894
36	0.733319254071194	0.533361491857612	0.266680745928806
37	0.797414992803127	0.405170014393747	0.202585007196873
38	0.840950055903128	0.318099888193743	0.159049944096872
39	0.869832975124948	0.260334049750105	0.130167024875052
40	0.88729319770487	0.225413604590258	0.112706802295129
41	0.899020741137836	0.201958517724328	0.100979258862164
42	0.894357511222216	0.211284977555569	0.105642488777785
43	0.88918226793846	0.221635464123079	0.110817732061539
44	0.869580708478664	0.260838583042672	0.130419291521336

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	0.3	NOK
10% type I error level	12	0.4	NOK