Dear All ,
I am trying to run a simultaneous equation model which is modeled as;
P*=D*+1X1+1
D*= zP*+ 2X2+2
Where each of the above two equations are ordered probit equations and P* and D* defined as, poverty and natural resources degradation are ordered latent endogenous variables which will have ordinal values between 1-4. The reason the model is formulated in this manner is because the objective of my study is to determine if the existence of each of these endogenous variables have cause and effect relationship, like the existence of poverty causes resources degradation and vice versa. More over endogneity is also expected from reviewed literature and it should be treated in a model like this.
By the time I start to work with this model with my collected cross section data , I am confused on applying 2-stage least square technique for ordered probit models
Of course I am trying to fit the model in this way;
Given the original simultaneous equation,
P*=D*+1X1+1
D*= P*+ 2X2+2
I will first regress each equation via ordered probit by GERTL software and have predicted probabilities for P* and D* i.e P^ and D^
Next stage I will undertake ordered probit regression by replacing D* and P* in the right side by P^ and D^ that is
P*=bD^+a1X1+e1
D*= cP^+ a2X2+e2
Finally interpret the output brought by the last regression(2nd stage)
Now I want to be confident on two things