Your title indicated -foreach- but your actually using -forval- and the
problem isn't related to doing things in a loop.
Joao Ricardo F. Lima wrote:
> How you can see, the estat ic is repeated in each looping...
>
> Can someone reproduce my problem and explain what am I doing wrong?
>
> Thanks a lot
>
>
It looks to me like you copied and pasted the output from 9.2 in both
instances. When I ran the code in Stata 10.1 (Born 11 Aug 2008) there
was a note at the bottom of the tables output by -estat-....
Note: N=Obs used in calculating BIC; see [R] BIC note
On reading this your problem became clearer and looking at the tables
again I notied that the Obs reported by -estat- did not match those
reported by -dfuller-, so I took the advice given in that note and used
thesample sizes estaimted by -dfuller- when calling -estat-...
webuse air2, clear
forvalues i=1/3 {
dfuller air, lags(`i')
estat ic, n(`r(N)')
}
...is this what you were expecting (output below)?
Neil
Augmented Dickey-Fuller test for unit root Number of obs
= 142
---------- Interpolated Dickey-Fuller
---------
Test 1% Critical 5% Critical 10%
Critical
Statistic Value Value Value
------------------------------------------------------------------------------
Z(t) -2.345 -3.496 -2.887
-2.577
------------------------------------------------------------------------------
MacKinnon approximate p-value for Z(t) = 0.1579
-----------------------------------------------------------------------------
Model | Obs ll(null) ll(model) df
AIC BIC
-------------+---------------------------------------------------------------
. | 142 . -1285.563 20 2611.125
2670.242
-----------------------------------------------------------------------------
Note: N=142 used in calculating BIC
Augmented Dickey-Fuller test for unit root Number of obs
= 141
---------- Interpolated Dickey-Fuller
---------
Test 1% Critical 5% Critical 10%
Critical
Statistic Value Value Value
------------------------------------------------------------------------------
Z(t) -1.811 -3.496 -2.887
-2.577
------------------------------------------------------------------------------
MacKinnon approximate p-value for Z(t) = 0.3751
-----------------------------------------------------------------------------
Model | Obs ll(null) ll(model) df
AIC BIC
-------------+---------------------------------------------------------------
. | 141 . -1285.563 20 2611.125
2670.1
-----------------------------------------------------------------------------
Note: N=141 used in calculating BIC
Augmented Dickey-Fuller test for unit root Number of obs
= 140
---------- Interpolated Dickey-Fuller
---------
Test 1% Critical 5% Critical 10%
Critical
Statistic Value Value Value
------------------------------------------------------------------------------
Z(t) -1.536 -3.497 -2.887
-2.577
------------------------------------------------------------------------------
MacKinnon approximate p-value for Z(t) = 0.5158
-----------------------------------------------------------------------------
Model | Obs ll(null) ll(model) df
AIC BIC
-------------+---------------------------------------------------------------
. | 140 . -1285.563 20 2611.125
2669.958
-----------------------------------------------------------------------------
Note: N=140 used in calculating BIC
--
"We should make things as simple as possible, but not simpler" - Anon (not Albert Einstein)
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