Hello,

I am running a model to find the effect of corurption on GDP in across Italian regions using panel data. I have found endogeneity between corruption and GDP growth,hence I am trying to use either fixed effects with instrumental variables or OLS with dummy variables.

As for the first case, I am having difficulties when specifying the following:

--> specification 1:
GDP growth= population growth + human capital + public investment + Corruption + Corruption ^2 + log of the lagged GDP pro capite

My coding is:
xtivreg Ygrowth I H logYlevel_1 n (Cor Cor2=Cor_1 Cor_12),fe vce (robust)
where Cor2=Cor^2 and Cor_12=(Cor_1)^2
- however, STATA says that Cor^2 is omitted because of collinearity. why is that the case?


--> specification 2:
GDP growth= population growth + human capital + public investment + logCorruption + log of the lagged GDP pro capite

My coding is:
xtivreg Ygrowth I H logYlevel_1 n (logCor= logCor_1 ),fe vce (robust)
- however, this results in everything being insignificant although I had found the following specification to be significant: xtivreg Ygrowth I H logYlevel_1 n (Cor= Cor_1 ),fe vce (robust)

--> model 2:
I wanted to try the following: reg Ygrowth H logYlevel_1 n I i.Region##c.Cor##i.Year, but it gives me an error message saying I have not coded this right. How do I code a dummy interaction variable to know the effect of corruption for each region for each year?