Dear Sven,
There is no wrong side here
The distribution of ADF statistics is skewed towards left
for tau = -0.12 it is less than for tau = 0.12 as should be
You can test against other soft you will get the same
Explosive behavior is ruled out from the start:
To this end one uses 1): logs
2) integration order 2
There are no ADF tests against explosion
Only a=0 versus a<0
I think, the best way to convince you is
to reproduce the same in another soft
To develop ADFGLS I studied the surface
response methodology
MacKinnon's p-values are very reliable from 5*10^-5 to 1-5*10^5
At far tails they are skewed towards ends, say instead of 10^-7
one can get 10^-15 but this never can difference for inference
Oleh






5 листопада 2018, 20:20:59, від "Sven Schreiber" <svetosch@gmx.net>:

Am 05.11.18 um 19:11 schrieb oleg_komashko@ukr.net:
Dear Sven,
To reproduce the best GUI option
with a script, use

open wgmacro.gdt
y = log(income)
maxlag = 12*(nobs(y)/100)^0.25
adf maxlag y --c --ct --test-down

# now no signs of explosion

Oleh, that's not the point. It's just an example I came across where the estimate is on the "wrong" side. It's clear that it doesn't happen very often with actual data, but it can happen. I would be curious to hear your opinion about what the correct p-value for a DF test (with as many lags as you like) is when the test statistic is positive instead of negative.
cheers,
sven

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