Johansen approach for testing cointegration

[Dim]

Hi everyone,

I'm measuring the effect of crime on investments in Rio de Janeiro. To do so, I'm using the following investment function:

I = f(Y, K, r, E, O) ; where I = investments, Y = GDP, K = capital stock, r = interest rate, E = investor's confidence, O = openess of the economy (X+M).

In order to measure the effect of crime, I added the "c" variable (= homicide rate) into the function, yielding to: I = f(Y, K, r, E, O,c).

Technically, I proceeded like that:

1) I tested the stationarity level of each varaibel and found that they are all integrated of order 1, thus I(1).
2) I tested the lag lenght optimality (of the unrestricted VAR model using all variables as endogenous) by the following command:

var var_ndi.ls 1 12 ndi rgdp ks lrir inv_conf openess
var_ndi.laglen(12, vname)

... and conclude for 1 lag (as optimal number of lag (following the SBC and the AIC).

3) I tried to select the optimal model (with/without trend, with/without intercept) by applying the Pantula's principle...
4) Then, I will run the cointegration test with this code :

coint.(s,1) lndi lrgdp lks lrir linv_conf lopeness hom

... determining the cointegration time series

5) correcting cointegration by a VECM.


MY QUESTIONS:

1) How to apply the Pantula's Principle. I mean, what is the code for programing?!?
2) How to insert (by coding) the VECM in my initial regression code?!?

Thank you in advance guys!

D.