Dear Statalist community,

I am analyzing the demand determinants of 3 insurance products in a pooled Heckman 2-Step regression. My outcome variable is coded as: 0=no insurance, 1 = lower premium insurance, 2 = middle premium insurance and 3 = high premium insurance. As I am controlling for social spillover effects I want to add dummies for the different places of residence. However, as in some cases there are not many observations per place of residence, resulting in lacking variance. Consequently, its marginal effects cannot be computed due to collinearity issues. This is not much of a problem for me as I just want to control for these but do not need to interpret its marginal effects. I also have another variable in there (insurer's presence, 0/1) that does not vary per residency and thus also has uncomputable marginal effects but these are of interest to me.

Instead of just ignoring the not estimable effects, I am wondering whether I can include my residency variable as a continuous one and leave the insurer's presence as a dummy. Of course, I can then not interpret the residency variable anymore but still control for it.

The regression table for using the residency variable as a continuous one looks like this:

Code:
(1) (2)
VARIABLES Insurance purchase Insurance product purchase
Peer behavior product choice(1-3) 0.3743***
(0.0895)
Peer behavior insurance uptake (0/1) 0.0037***
(0.0007)
Village fixed effects (continuous!) 0.0070* -0.0107
(0.0038) (0.0070)
Income 0.2408 0.2728
(0.2117) (0.4392)
Presence insurer (0/1) -0.0578
(0.0515)
Year 1 -0.0334 0.0446
(0.0545) (0.1029)
Year 2 0.0189 0.0897
(0.0439) (0.1030)
Year 3 0.0069 0.0959
(0.0485) (0.0908)
Year 4 -0.0516 0.0871
(0.0537) (0.1186)
Gender -0.0831* -0.1605*
(0.0435) (0.0905)
Age 0.0000 -0.0001**
(0.0000) (0.0000)
Educ 0.0023 0.0037
(0.0020) (0.0044)
HH size 0.0085 0.0213**
(0.0073) (0.0101)
Risk aversion 0.0951* -0.0750
(0.0502) (0.1114)
(0.0156) (0.0359)
imr1 0.5364*
(0.2747)
Observations 574 472
R-squared 0.1927 0.1679 
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Or do you see any objections here?

Thanks in advance!!!