ARMA model coefficient Interpretation How do I interpret the phi and theta in the $SARIMA$ model? I know that they are both parameters of the model, but I am having a hard time trying to interpret them.
For example, the phi in the $AR(1)$ model equals $0.3467$, can I interpret it as that for every 1 unit increase in $X_{t-1}$, $X_t$ would increase by $0.3467$?
If Yes, how should I interpret the MA model coefficients as the pure $MA$ model depends only on the errors of the previous forecast?
If that's not the case, how should I interpret them?

Thanks so much.
 A: "For example, the phi in the AR(1) model equals 0.3467, can I interpret it as that for every 1 unit increase in Xt-1, Xt would increase by 0.3467?"
only if there is no differencing , no ma structure and no power transform .
You need to 1) either do a lot of algebra and re-present the model as a pure AR MODEL
OR 2) use software that delivers that feature to you.
A: 
ARMA model coefficient Interpretation

Regarding the AR part, in my view, them have a purely correlational interpretation only. Therefore them are transformation of total or partial linear correlation coefficients and maintain them interpretation too. In the case of $MA$ part a non observable series is involved (errors) and I'm not sure if the same interpretation hold. However remember that any stationary and invertible $ARMA$ have a pure $AR$ representation too.

For example, the phi in the $AR(1)$ model equals $0.3467$, can I interpret
it as that for every 1 unit increase in $X_{t-1}$, $X_t$ would increase by
$0.3467$?

This statement is usually affirmed for any regression. It can be literally correct but can be misleading too. The word "increase" is ambiguous, what it mean? It is an observed fact or imply some intervention?
If you intend an observed fact the interpretation is correct and it is purely correlational. If you have in mind an intervention the interpretation is surely wrong because $AR$ model are "free of theory" model, it avoid causal reasoning. This my question is related: Structural equation and causal model in economics
