I have a data set of identical twins, such that the data can be considered as paired observations. The data is composed of a survey that was conducted on two separate years, and all twins answer the survey questions in both years. The variables I have are
Stress1: is the stress score of the individual in Year 1 ranging from 1 to 3 with 1 being least stress.
Stress2: is the stress score of the individual in Year 2 ranging from 1 to 3 with 1 being least stress.
WorkStat1: is the work status of the individual in Year 1 and includes 2 categories (1: entrepreneur, 0: not entrepreneur)
WorkStat2: is the work status of the individual in Year 2 and includes 2 categories (1: entrepreneur, 0: not entrepreneur)
I want to study the effect of a change in
WorkStat on the change in
If I understand correctly, the change in
WorkStat in the two years translates into a control group (0: Never_Been_Entrepreneur) and 3 treatment groups (1: Became_Entrepreneur, 2: Always_Entrepreneur, and 3: Left_Entrepreneur).
My first question: Is my understanding of the problem in the context of a Diff-in-Diff model correct?
The question that i'm trying to answer is whether becoming an entrepreneur increases stress. so I'm interested in the first treatment group (1: Became_Entrepreneur). How can I conduct this analysis in Stata given that my data is paired (i'm dealing with twins). For example, I have two individuals with
twin_id = 1 and
person_id equal 1 and 2 respectively for each individual in the twin pair.