On Fri, 28 Apr 2017, T.Riedle wrote:
Dear all,
I am trying to run an ADF test using the adf.test() function in the
tseries package and the ur.df() function in the urca package. The
results I get contrast sharply. Whilst the adf.test() indicates
stationarity which is in line with the corresponding graph, the ur.df()
indicates non-stationarity.
Why does this happen?
This is likely due to different setting for the deterministic part of the
model and/or the number of lags tested. The defaults of ur.df() are often
not suitable for many practical applications which might to spurious
significant results.
Could anybody explain the adf.test() function in more detail? How does
adf.test() select the number of lags is it AIC or BIC and how does it
take an intercept and/or a trend into account?
There is a deterministic trend and the default number of lags is selected
by a heuristic.
At
https://stats.stackexchange.com/questions/168332/r-augmented-dickey-fuller-adf-test/168355#168355
I've summarized an overview that I had written for my students. It might
also be helpful for you.
hth,
Z
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