I am running the 3 models of the ADF (Augmented Dickey Fuller) test on a (ln total fertility rate) variable. The results:
Intercept only: (lag difference = 0) at level; p-value for Z(t) = 0.9672.
This means that the variable is non-stationary, right? Coefficient of
lnTFR.L1= 0.00072 2-
I read that if the coefficient of L1 is not negative, the model is invalid. What does that mean?
Intercept + trend: (lag difference = 0) at level; p-value for Z(t) = 0.9409.
Does this mean that the variable TFR is also non-stationary when including trend? Coefficient of
lnTFR.L1= -0.04623; now the coefficient is negative, so is the model valid?
No intercept + no trend: (lag difference=0) at level; the test statistic (12.762) is much higher than the 1% critical value (2.642) and 5% critical value (1.95). Does this mean that the variable is stationary with no trend and intercept? In this case what should I do?
When I tried a lag difference = 1 at level I found that the variable became stationary in the model intercept + trend! Should I take the first difference, or only conclude that the variable at level is stationary with 1 lag difference? Thanks! :)