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I am trying to determine if I should include an "intercept" or a "trend and intercept" when using the Augmented Dickey-Fuller (ADF) test. I ran a regression with my dependent variable and a time trend and both the intercept and trend were statistically significant. Is this statistical significance what determines if I should include a "trend and intercept" in the ADF test? My data is unstructured/undated. The series contains 252 observations and there are about 6 observations per year from 1970-2014. Below are my regression results and a graph of the raw data.

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  • $\begingroup$ Have you checked out existing posts on Dickey-Fuller test? See, for example, here and here. $\endgroup$ – Richard Hardy Mar 3 '15 at 7:21
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library(tseries)
library(urca)
data2<-na.remove(data1$SANDP) #assumed one dataset
    data2
    c<-adf.test(data2,k=2)
    c
    summary(c$statistic)

useful command for you

summary(ur.df(data2,type=c("drift"),lags=2,selectlags =c("Fixed")))
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  • $\begingroup$ you can change type=drift /none/trend. $\endgroup$ – Harshil Gandhi Jan 29 '16 at 6:47

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