I have a question regarding the heterogeneous treatment effects. For example, I want to estimate the heterogeneous treatment effects of informal caregiving on caregivers' health by household income. Let y denote the binary health outcome (1=good; 0=poor), CG is the caregiving status (1=caregivers; 0 otherwise), Z1 is an instrumental variable for CG and is a continuous variable taking values from [0,1], HHinc is a binary indicating whether the HH is rich or poor (1=rich; 0 otherwise), I also have age and edu as additional covariates.
My primary purpose is to estimate the heterogeneous treatment effects by HH income. CG is a binary variable but I used c.CG instead of i.CG because I have just one instrumental variable. I wanted to confirm if this is the right way to go about it. I have also controlled for HHinc.
ivregress 2sls y (CG c.CG#i.HHinc = Z1 c.Z1#i.HHinc) age edu HHinc, robust
I'd appreciate your help. Thanks!
(similar question was posted by somebody in 2021 but wasnt answered)
My primary purpose is to estimate the heterogeneous treatment effects by HH income. CG is a binary variable but I used c.CG instead of i.CG because I have just one instrumental variable. I wanted to confirm if this is the right way to go about it. I have also controlled for HHinc.
ivregress 2sls y (CG c.CG#i.HHinc = Z1 c.Z1#i.HHinc) age edu HHinc, robust
I'd appreciate your help. Thanks!
(similar question was posted by somebody in 2021 but wasnt answered)
