I am estimating this model:
But I want to do some analysis of the variables before. In particular, I am interested in fitting some ARIMA models. First, I am doing it for the inflation rate in Mexico.
- For the ARIMA model, do I need to take into account the other variables or only the values of variation of inflation in previous periods?
What does it mean to have a lag at 0.5 ? Since I cannot introduce an MA(.5), should I care about it or only take into account lags at t=1 and t=2?
When I look at the PACF it looks like this:
Again, what does it mean to have considerable autocorrelation at t=.5 and t=.8? Since I cannot have an AR(.5), should I pay attention to this lags or only to lags at t=1 and t=2? Why?
- When I use the
auto.arimafunction in R, it produces a model ARIMA(0,0,2), so that is no AR term, but is this not a contradiction with the PACF graph? What should I do? Why?
- In order to evaluate the goodness of fit I am using
Box.test(fit_resid,lag=10,type="Ljung-Box"), but that gives me a p-value of very small, then is that a good fit or not?
- Finally, should I repeat that for every variable in the model or not? Why?