Hello everyone,

I try to estimate a generalized structural equation model. I have multilevel data (individuals nested within municipality). My dependent variable is the individual feeling of fear that I estimate by individual (sex, age, education, work) and municipality level factors (homicide rate, security and justice spendings, gini index and its square form (possible non-linear effect)). I'm particularly interested in the impact of the gini index, that I suspect to be endogenous. gini_90 is my instrument variable. My code is as following:

Code:
gsem (fear <- sex age educ work homicide_rate security justice gini gini_sqr M1[municipality]) (gini <- gini_90 homicide_rate security justice)(gini_sqr <- gini_90 homicide_rate security justice), cov(e.fear*e.gini) cov(e.fear*e.gini_sqr) latent(M1) vce(cluster municipality)
However, this model fails to converge. I noticed that it gave some results when I remove one of the cov options, leaving only
Code:
cov(e.fear*e.gini)
or
Code:
cov(e.fear*e.gini_sqr)
.
Could someone explain me why this problem emerge and how I could solve it ?

Thank you so much,
Lucie