Multiple Linear Regression - Estimated Regression Equation |
Inflatie[t] = + 2.27575757575757 + 0.198316498316499Kredietcrisis[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) | 2.27575757575757 | 0.270002 | 8.4287 | 0 | 0 |
Kredietcrisis | 0.198316498316499 | 0.402495 | 0.4927 | 0.624072 | 0.312036 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.0645620678760925 |
R-squared | 0.00416826060843718 |
Adjusted R-squared | -0.0130012521396932 |
F-TEST (value) | 0.242771048286799 |
F-TEST (DF numerator) | 1 |
F-TEST (DF denominator) | 58 |
p-value | 0.624072026784833 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 1.55104224087335 |
Sum Squared Residuals | 139.532457912458 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 2.7 | 2.27575757575758 | 0.424242424242415 |
2 | 2.3 | 2.27575757575757 | 0.0242424242424247 |
3 | 1.9 | 2.27575757575758 | -0.375757575757575 |
4 | 2 | 2.27575757575758 | -0.275757575757575 |
5 | 2.3 | 2.27575757575758 | 0.0242424242424245 |
6 | 2.8 | 2.27575757575758 | 0.524242424242425 |
7 | 2.4 | 2.27575757575758 | 0.124242424242425 |
8 | 2.3 | 2.27575757575758 | 0.0242424242424245 |
9 | 2.7 | 2.27575757575758 | 0.424242424242425 |
10 | 2.7 | 2.27575757575758 | 0.424242424242425 |
11 | 2.9 | 2.27575757575758 | 0.624242424242425 |
12 | 3 | 2.27575757575758 | 0.724242424242425 |
13 | 2.2 | 2.27575757575758 | -0.0757575757575752 |
14 | 2.3 | 2.27575757575758 | 0.0242424242424245 |
15 | 2.8 | 2.27575757575758 | 0.524242424242425 |
16 | 2.8 | 2.27575757575758 | 0.524242424242425 |
17 | 2.8 | 2.27575757575758 | 0.524242424242425 |
18 | 2.2 | 2.27575757575758 | -0.0757575757575752 |
19 | 2.6 | 2.27575757575758 | 0.324242424242425 |
20 | 2.8 | 2.27575757575758 | 0.524242424242425 |
21 | 2.5 | 2.27575757575758 | 0.224242424242425 |
22 | 2.4 | 2.27575757575758 | 0.124242424242425 |
23 | 2.3 | 2.27575757575758 | 0.0242424242424245 |
24 | 1.9 | 2.27575757575758 | -0.375757575757575 |
25 | 1.7 | 2.27575757575758 | -0.575757575757575 |
26 | 2 | 2.27575757575758 | -0.275757575757575 |
27 | 2.1 | 2.27575757575758 | -0.175757575757575 |
28 | 1.7 | 2.27575757575758 | -0.575757575757575 |
29 | 1.8 | 2.27575757575758 | -0.475757575757575 |
30 | 1.8 | 2.27575757575758 | -0.475757575757575 |
31 | 1.8 | 2.27575757575758 | -0.475757575757575 |
32 | 1.3 | 2.27575757575758 | -0.975757575757575 |
33 | 1.3 | 2.27575757575758 | -0.975757575757575 |
34 | 1.3 | 2.47407407407407 | -1.17407407407407 |
35 | 1.2 | 2.47407407407407 | -1.27407407407407 |
36 | 1.4 | 2.47407407407407 | -1.07407407407407 |
37 | 2.2 | 2.47407407407407 | -0.274074074074074 |
38 | 2.9 | 2.47407407407407 | 0.425925925925926 |
39 | 3.1 | 2.47407407407407 | 0.625925925925926 |
40 | 3.5 | 2.47407407407407 | 1.02592592592593 |
41 | 3.6 | 2.47407407407407 | 1.12592592592593 |
42 | 4.4 | 2.47407407407407 | 1.92592592592593 |
43 | 4.1 | 2.47407407407407 | 1.62592592592593 |
44 | 5.1 | 2.47407407407407 | 2.62592592592593 |
45 | 5.8 | 2.47407407407407 | 3.32592592592593 |
46 | 5.9 | 2.47407407407407 | 3.42592592592593 |
47 | 5.4 | 2.47407407407407 | 2.92592592592593 |
48 | 5.5 | 2.47407407407407 | 3.02592592592593 |
49 | 4.8 | 2.47407407407407 | 2.32592592592593 |
50 | 3.2 | 2.47407407407407 | 0.725925925925926 |
51 | 2.7 | 2.47407407407407 | 0.225925925925926 |
52 | 2.1 | 2.47407407407407 | -0.374074074074074 |
53 | 1.9 | 2.47407407407407 | -0.574074074074074 |
54 | 0.6 | 2.47407407407407 | -1.87407407407407 |
55 | 0.7 | 2.47407407407407 | -1.77407407407407 |
56 | -0.2 | 2.47407407407407 | -2.67407407407407 |
57 | -1 | 2.47407407407407 | -3.47407407407407 |
58 | -1.7 | 2.47407407407407 | -4.17407407407407 |
59 | -0.7 | 2.47407407407407 | -3.17407407407407 |
60 | -1 | 2.47407407407407 | -3.47407407407407 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
5 | 0.0148471473105150 | 0.0296942946210300 | 0.985152852689485 |
6 | 0.00712176315164228 | 0.0142435263032846 | 0.992878236848358 |
7 | 0.00148914821848367 | 0.00297829643696734 | 0.998510851781516 |
8 | 0.000282980742703436 | 0.000565961485406871 | 0.999717019257297 |
9 | 8.62068375277507e-05 | 0.000172413675055501 | 0.999913793162472 |
10 | 2.37142053068401e-05 | 4.74284106136803e-05 | 0.999976285794693 |
11 | 1.11213024583831e-05 | 2.22426049167663e-05 | 0.999988878697542 |
12 | 6.13621006065755e-06 | 1.22724201213151e-05 | 0.99999386378994 |
13 | 1.63514824760816e-06 | 3.27029649521633e-06 | 0.999998364851752 |
14 | 3.4989362679033e-07 | 6.9978725358066e-07 | 0.999999650106373 |
15 | 1.00669082576210e-07 | 2.01338165152421e-07 | 0.999999899330917 |
16 | 2.73770813866171e-08 | 5.47541627732342e-08 | 0.999999972622919 |
17 | 7.09143345714384e-09 | 1.41828669142877e-08 | 0.999999992908567 |
18 | 1.89934692735003e-09 | 3.79869385470006e-09 | 0.999999998100653 |
19 | 3.48674400143995e-10 | 6.9734880028799e-10 | 0.999999999651326 |
20 | 8.76708169097404e-11 | 1.75341633819481e-10 | 0.99999999991233 |
21 | 1.48077311051323e-11 | 2.96154622102647e-11 | 0.999999999985192 |
22 | 2.57682505134154e-12 | 5.15365010268308e-12 | 0.999999999997423 |
23 | 5.0822573453605e-13 | 1.0164514690721e-12 | 0.999999999999492 |
24 | 4.29231533160146e-13 | 8.58463066320292e-13 | 0.99999999999957 |
25 | 7.81642937451154e-13 | 1.56328587490231e-12 | 0.999999999999218 |
26 | 2.76958291020261e-13 | 5.53916582040522e-13 | 0.999999999999723 |
27 | 7.05741766811054e-14 | 1.41148353362211e-13 | 0.99999999999993 |
28 | 6.8669777446128e-14 | 1.37339554892256e-13 | 0.999999999999931 |
29 | 3.59891999722198e-14 | 7.19783999444396e-14 | 0.999999999999964 |
30 | 1.68716283761260e-14 | 3.37432567522521e-14 | 0.999999999999983 |
31 | 7.24654924290656e-15 | 1.44930984858131e-14 | 0.999999999999993 |
32 | 2.06059776094847e-14 | 4.12119552189693e-14 | 0.99999999999998 |
33 | 3.59938477203944e-14 | 7.19876954407888e-14 | 0.999999999999964 |
34 | 8.06824261346828e-15 | 1.61364852269366e-14 | 0.999999999999992 |
35 | 1.86609812632569e-15 | 3.73219625265138e-15 | 0.999999999999998 |
36 | 4.13357516356128e-16 | 8.26715032712256e-16 | 1 |
37 | 2.94960222944211e-16 | 5.89920445888422e-16 | 1 |
38 | 1.11808767164257e-15 | 2.23617534328514e-15 | 0.999999999999999 |
39 | 2.46938831972150e-15 | 4.93877663944299e-15 | 0.999999999999998 |
40 | 8.98375204738692e-15 | 1.79675040947738e-14 | 0.99999999999999 |
41 | 1.80965549389571e-14 | 3.61931098779141e-14 | 0.999999999999982 |
42 | 3.07740191073765e-13 | 6.15480382147531e-13 | 0.999999999999692 |
43 | 6.4945000692612e-13 | 1.29890001385224e-12 | 0.99999999999935 |
44 | 2.23531161926481e-11 | 4.47062323852962e-11 | 0.999999999977647 |
45 | 3.24446566878358e-09 | 6.48893133756716e-09 | 0.999999996755534 |
46 | 2.54308988515684e-07 | 5.08617977031368e-07 | 0.999999745691011 |
47 | 4.59265107849147e-06 | 9.18530215698294e-06 | 0.999995407348921 |
48 | 0.000205337938783162 | 0.000410675877566324 | 0.999794662061217 |
49 | 0.00493904229365506 | 0.00987808458731012 | 0.995060957706345 |
50 | 0.0182437260212939 | 0.0364874520425877 | 0.981756273978706 |
51 | 0.0627864425277107 | 0.125572885055421 | 0.93721355747229 |
52 | 0.166186907826078 | 0.332373815652157 | 0.833813092173922 |
53 | 0.481876291315236 | 0.963752582630471 | 0.518123708684764 |
54 | 0.581617157009702 | 0.836765685980597 | 0.418382842990298 |
55 | 0.817890946290641 | 0.364218107418718 | 0.182109053709359 |
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
Description | # significant tests | % significant tests | OK/NOK |
1% type I error level | 43 | 0.843137254901961 | NOK |
5% type I error level | 46 | 0.901960784313726 | NOK |
10% type I error level | 46 | 0.901960784313726 | NOK |