Multiple Linear Regression - Estimated Regression Equation

USDOLLAR[t] = + 0.105597037179138 + 0.00941197428820186Amerikaanse_inflatie[t] + 1.20596116767540`Y[t-1]`[t] -0.527201466526525`Y[t-2]`[t] + 0.547813323376132`Y[t-3]`[t] -0.388942635999796`Y[t-4]`[t] + 0.0293145636322456M1[t] -0.00111634037128101M2[t] + 0.0413735451661571M3[t] + 0.0121472277427398M4[t] + 0.0212072164688286M5[t] + 0.0097722538432314M6[t] -0.0136301901705398M7[t] + 0.0219708478339727M8[t] -0.00996368572382476M9[t] + 0.0239631461363912M10[t] + 0.0182904283986546M11[t] + 0.000324299601614479t + 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)	0.105597037179138	0.049654	2.1267	0.040181	0.020091
Amerikaanse_inflatie	0.00941197428820186	0.01381	0.6815	0.499782	0.249891
`Y[t-1]`	1.20596116767540	0.183309	6.5788	0	0
`Y[t-2]`	-0.527201466526525	0.247678	-2.1286	0.040012	0.020006
`Y[t-3]`	0.547813323376132	0.238998	2.2921	0.027685	0.013843
`Y[t-4]`	-0.388942635999796	0.151709	-2.5637	0.014552	0.007276
M1	0.0293145636322456	0.021012	1.3952	0.171286	0.085643
M2	-0.00111634037128101	0.021164	-0.0527	0.958217	0.479109
M3	0.0413735451661571	0.021036	1.9668	0.056745	0.028372
M4	0.0121472277427398	0.021818	0.5568	0.581042	0.290521
M5	0.0212072164688286	0.02116	1.0022	0.322739	0.16137
M6	0.0097722538432314	0.021568	0.4531	0.653129	0.326565
M7	-0.0136301901705398	0.021231	-0.642	0.524832	0.262416
M8	0.0219708478339727	0.022859	0.9611	0.342726	0.171363
M9	-0.00996368572382476	0.023219	-0.4291	0.670327	0.335163
M10	0.0239631461363912	0.022911	1.0459	0.302391	0.151196
M11	0.0182904283986546	0.022231	0.8227	0.415924	0.207962
t	0.000324299601614479	0.000282	1.1515	0.256916	0.128458

Multiple Linear Regression - Regression Statistics
Multiple R	0.94880027255588
R-squared	0.900221957202111
Adjusted R-squared	0.85437799159227
F-TEST (value)	19.6366510886849
F-TEST (DF numerator)	17
F-TEST (DF denominator)	37
p-value	1.49324996812084e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.0305246824388129
Sum Squared Residuals	0.0344749808056438

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	0.7905	0.79712299239437	-0.00662299239437012
2	0.7719	0.777946421441421	-0.00604642144142124
3	0.7811	0.786729018034817	-0.00562901803481656
4	0.7557	0.784461318183687	-0.0287613181836867
5	0.7637	0.743860913783656	0.0198390862163442
6	0.7595	0.772919651688219	-0.0134196516882189
7	0.7471	0.724007325403481	0.0230926745965185
8	0.7615	0.768137141975872	-0.00663714197587215
9	0.7487	0.74441980692445	0.00428019307554969
10	0.7389	0.744328176998905	-0.00542817699890496
11	0.7337	0.749933933683564	-0.0162339336835641
12	0.751	0.723944841133322	0.0270551588666775
13	0.7382	0.772045128350074	-0.0338451283500743
14	0.7159	0.71928584161107	-0.00338584161107040
15	0.7542	0.756278535970568	-0.00207853597056763
16	0.7636	0.770159497314745	-0.00655949731474485
17	0.7433	0.76250903565132	-0.0192090356513203
18	0.7658	0.754411694569875	0.0113883054301251
19	0.7627	0.75893338581886	0.00376661418113985
20	0.748	0.756603717086188	-0.00860371708618804
21	0.7692	0.728641503109469	0.0405584968905306
22	0.785	0.791801929764523	-0.00680192976452251
23	0.7913	0.790269837694587	0.00103016230541267
24	0.772	0.785504857569513	-0.0135048575695132
25	0.788	0.79135722109776	-0.00335722109775968
26	0.807	0.788930463502756	0.0180695364972439
27	0.8268	0.831260684911889	-0.00446068491188936
28	0.8244	0.833347966055096	-0.00894796605509596
29	0.8487	0.83166468675651	0.0170353132434903
30	0.8572	0.854486837602672	0.00271316239732783
31	0.8214	0.819192537058665	0.00220746294133468
32	0.8827	0.82478629407322	0.057913705926781
33	0.9216	0.880672152779527	0.0409278472204730
34	0.8865	0.912388358570235	-0.0258883585702349
35	0.8816	0.885072227619392	-0.0034722276193915
36	0.8884	0.878007080980017	0.0103929190199829
37	0.9466	0.882283376034397	0.0643166239656029
38	0.918	0.931741681406962	-0.0137416814069616
39	0.9337	0.912876683150589	0.0208233168494111
40	0.9559	0.950348918563324	0.00555108143667627
41	0.9626	0.94405641603773	0.0185435839622705
42	0.9434	0.947192089912107	-0.00379208991210688
43	0.8639	0.896498612726762	-0.0325986127267623
44	0.7996	0.842272846864721	-0.0426728468647208
45	0.668	0.753766537186553	-0.0857665371865532
46	0.6572	0.619081534666338	0.0381184653336624
47	0.6928	0.674124001002457	0.0186759989975429
48	0.6438	0.667743220317147	-0.0239432203171471
49	0.6454	0.665891282123399	-0.0204912821233989
50	0.6873	0.68219559203779	0.00510440796220938
51	0.7265	0.735155077932138	-0.0086550779321376
52	0.7912	0.752482299883149	0.0387177001168513
53	0.8114	0.847608947770785	-0.0362089477707847
54	0.8281	0.824989726227127	0.00311027377287283
55	0.8393	0.83576813899223	0.0035318610077692

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
21	0.145730276264427	0.291460552528853	0.854269723735573
22	0.0666558641426012	0.133311728285202	0.933344135857399
23	0.0236722145265902	0.0473444290531805	0.97632778547341
24	0.0232310826196132	0.0464621652392265	0.976768917380387
25	0.0158342423218833	0.0316684846437665	0.984165757678117
26	0.00744278463504582	0.0148855692700916	0.992557215364954
27	0.0028250229230559	0.0056500458461118	0.997174977076944
28	0.00122212352569661	0.00244424705139322	0.998777876474303
29	0.000403525439058238	0.000807050878116476	0.999596474560942
30	0.000234483543839377	0.000468967087678754	0.99976551645616
31	0.000697188006406072	0.00139437601281214	0.999302811993594
32	0.000490859058266538	0.000981718116533076	0.999509140941733
33	0.0026897377436839	0.0053794754873678	0.997310262256316
34	0.00126699205251235	0.00253398410502471	0.998733007947488

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	8	0.571428571428571	NOK
5% type I error level	12	0.857142857142857	NOK
10% type I error level	12	0.857142857142857	NOK