Thanks for the help that sorted it
Kind regards,
Philip Braithwaite
________________________________________
From: gretl-users-bounces(a)lists.wfu.edu [gretl-users-bounces(a)lists.wfu.edu] on behalf of
Allin Cottrell [cottrell(a)wfu.edu]
Sent: 19 February 2012 22:30
To: Gretl list
Subject: Re: [Gretl-users] ADF Test
On Sun, 19 Feb 2012, artur.tarassow(a)googlemail.com wrote:
 The answer is simple: for the s variable no lags are included.
 Hence, there is no need to add lagged first difference(s). 
To expand on Artur's comment just a little: the results shown by
Philip pertain to an ADF test run with the --test-down option.
When this option is selected, lags of the first difference of the
variable to be tested are included only if they are statistically
significant (on a criterion explained in the manual). So it appears
that lag 1 of the first difference was significant for one of the
series under test ("u") but not for the other ("s").
The inclusion of lagged differences in the test regression is not
essential to the logic of the Dickey-Fuller test, but it's advisable
if the series exhibits higher-order serial correlation.
Allin Cottrell
 -original message-
 Subject: [Gretl-users] ADF Test
 From: "(s) Philip Braithwaite"
<philip.braithwaite(a)students.plymouth.ac.uk>
 Date: 18/02/2012 18:23
 Hi,
 I've been running the ADF test for 2 variables, however when I view the regression
results of the ADF test, it appears to perform it differently for each variable. The
outputs for each variable are pasted below. The first one tests the differenced u variable
against u_1 and d_u_1 (plus seasonal dummies), which you would expect for the test.
However for s, it leaves out the d_s_1 element. I've found this happening with a
number of other variables in different models.
 Is this still performing a correct ADF test or should I be doing something differently?
 Any information you could offer would be hugely appreciated
 Augmented Dickey-Fuller test for u
 including one lag of (1-L)u (max was 1)
 sample size 93
 unit-root null hypothesis: a = 1
   test with constant plus seasonal dummies
   model: (1-L)y = b0 + (a-1)*y(-1) + ... + e
   1st-order autocorrelation coeff. for e: -0.023
   estimated value of (a - 1): -0.121213
   test statistic: tau_c(1) = -1.98793
   asymptotic p-value 0.2924
 Augmented Dickey-Fuller regression
 OLS, using observations 1980:03-1987:11 (T = 93)
 Dependent variable: d_u
             coefficient   std. error   t-ratio    p-value
  ---------------------------------------------------------
  const       0.0512208    0.00498901    10.27    3.37e-016 ***
  u_1        -0.121213     0.0609744       -1.988   0.2924
  d_u_1      -0.290699     0.106952      -2.718   0.0081    ***
  dm1        -0.0616078    0.00781483    -7.883   1.47e-011 ***
  dm2        -0.0914671    0.00835130   -10.95    1.64e-017 ***
  dm3        -0.0703498    0.00808719    -8.699   3.77e-013 ***
  dm4        -0.0598935    0.00699811    -8.559   7.09e-013 ***
  dm5        -0.0549386    0.00698092    -7.870   1.56e-011 ***
  dm6        -0.0216324    0.00692478    -3.124   0.0025    ***
  dm7        -0.0375700    0.00692756    -5.423   6.20e-07  ***
  dm8        -0.0733871    0.00660600   -11.11    8.23e-018 ***
  dm9        -0.0622728    0.00756849    -8.228   3.13e-012 ***
  dm10       -0.0360162    0.00685525    -5.254   1.23e-06  ***
  dm11       -0.0341986    0.00663768    -5.152   1.85e-06  ***
  AIC: -536.222   BIC: -500.766   HQC: -521.906
 Dickey-Fuller test for s
 sample size 95
 unit-root null hypothesis: a = 1
   test with constant plus seasonal dummies
   model: (1-L)y = b0 + (a-1)*y(-1) + e
   1st-order autocorrelation coeff. for e: -0.008
   estimated value of (a - 1): -1.26693
   test statistic: tau_c(1) = -11.9177
   p-value 0.002828
 Dickey-Fuller regression
 OLS, using observations 1980:02-1987:12 (T = 95)
 Dependent variable: d_s
             coefficient   std. error   t-ratio    p-value
  ---------------------------------------------------------
  const        0.378700    0.0383446      9.876   1.31e-015 ***
  s_1         -1.26693         0.106307     -11.92    0.0028    ***
  dm1         -0.424225    0.0774678     -5.476   4.64e-07  ***
  dm2         -0.462089    0.0504077     -9.167   3.35e-014 ***
  dm3         -0.381479    0.0512581     -7.442   8.79e-011 ***
  dm4         -0.338558    0.0526217     -6.434   7.84e-09  ***
  dm5         -0.113624    0.0535687     -2.121   0.0369    **
  dm6         -0.182175    0.0651366     -2.797   0.0064    ***
  dm7         -0.439919    0.0575612     -7.643   3.55e-011 ***
  dm8         -0.432768    0.0505549     -8.560   5.39e-013 ***
  dm9         -0.500302    0.0516082     -9.694   3.01e-015 ***
  dm10        -0.543976    0.0504374    -10.79    2.14e-017 ***
  dm11        -0.547869    0.0503964    -10.87    1.45e-017 ***
  AIC: -154.374   BIC: -121.173   HQC: -140.958
 Thanks
 Philip Braithwaite
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--
Allin Cottrell
Department of Economics
Wake Forest University
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