[R] Serious difference between the result of ADF test in R and Eviews
RON70
ron_michael70 at yahoo.com
Wed Jan 21 04:51:17 CET 2009
I found there is serious difference between the result of ADF test in R and
Eviews, for this data :
> dat
V1
1 -0.075851693
2 -0.046125504
3 -0.009117161
4 0.025569817
5 0.034882743
6 0.073671497
7 0.063805297
8 0.062306796
9 0.072343820
10 0.058354121
11 -0.007635359
12 0.086790779
13 0.085487789
14 0.113577103
15 0.021293381
16 0.089423068
17 0.090485998
18 0.128847827
19 0.011859335
20 0.058794744
21 0.065909368
22 0.020887431
23 0.085387467
24 0.097375525
25 0.108981417
26 0.044289044
27 0.071428571
28 0.052430556
29 0.056307049
30 0.041957314
R results says, Unit root hypothesis can not be rejected :
> adf.test(dat, k=1)
Augmented Dickey-Fuller Test
data: dat
Dickey-Fuller = -3.5458, Lag order = 1, p-value = 0.0554
alternative hypothesis: stationary
However below the Eviews result
Null Hypothesis: SERIES02 has a unit root
Exogenous: Constant
Lag Length: 1 (Fixed)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -3.992560 0.0048
Test critical values: 1% level -3.689194
5% level -2.971853
10% level -2.625121
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(SERIES02)
Method: Least Squares
Date: 01/21/09 Time: 09:16
Sample (adjusted): 3 30
Included observations: 28 after adjustments
Variable Coefficient Std. Error t-Statistic Prob.
SERIES02(-1) -0.728468 0.182456 -3.992560 0.0005
D(SERIES02(-1)) -0.182826 0.154154 -1.185993 0.2468
C 0.046094 0.012152 3.793043 0.0008
R-squared 0.510689 Mean dependent var 0.003146
Adjusted R-squared 0.471545 S.D. dependent var 0.047487
S.E. of regression 0.034520 Akaike info criterion -3.793578
Sum squared resid 0.029791 Schwarz criterion -3.650842
Log likelihood 56.11010 F-statistic 13.04615
Durbin-Watson stat 2.127111 Prob(F-statistic) 0.000132
Therefore Eviews rejects the null of unit root.
Have you face this kind of problem earlier or I am missing something?
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