Dear All,
I am estimating a model with instrumental variable / exclusion variable.
I run the model with instrument/ exclusion variable: cmp (provider_group = outside_born $controls) (nn=i.provider_group $controls) if sample!=. [pweight = fp], ind(5 4) robust
The marginal estimates of the model with command below is:
margins, dydx(i.provider_group) predict(pr eq(lf))
But if I do not use the instrumental/exclusion variable approach I get the marginal estimate of: probit nn i.provider_group $controls if sample!=. [pweight = fp], robust
margins, dydx(i.provider_group)
I know in my model instrumental variable is required due to reverse causality between nn and i.provider_group. But I am a bit concerned about such a high estimate with IV.
My question is - is it ok to have such a high marginal estimate with IV as compared to the marginal estimates without IV? Or should I be concerned about any underlying problem with the model?
I am estimating a model with instrumental variable / exclusion variable.
I run the model with instrument/ exclusion variable: cmp (provider_group = outside_born $controls) (nn=i.provider_group $controls) if sample!=. [pweight = fp], ind(5 4) robust
The marginal estimates of the model with command below is:
margins, dydx(i.provider_group) predict(pr eq(lf))
But if I do not use the instrumental/exclusion variable approach I get the marginal estimate of: probit nn i.provider_group $controls if sample!=. [pweight = fp], robust
margins, dydx(i.provider_group)
I know in my model instrumental variable is required due to reverse causality between nn and i.provider_group. But I am a bit concerned about such a high estimate with IV.
My question is - is it ok to have such a high marginal estimate with IV as compared to the marginal estimates without IV? Or should I be concerned about any underlying problem with the model?
Comment