Dear Statalisters,

I am currently working on the life satisfaction of potential caregivers. More precisely, I analyse whether providing care would increase or decrease their level of life satisfaction.
As shown in the care literature, it exists a selection bias as people who turn caregivers and keep on providing support over time are usually women, poorer and have lower opportunity costs. To what I know, there is no clear consensus on the impact of life satisfation in selection into caregiving. In other words, I wonder whether more satisfied (or less) have higher (or lower) propensities to provide care.

I use panel data (LISS) from 2008 to 2018 (with a gap in 2016) gathering information on socio-demographic characteristics, life satisfaction and care patterns of Dutch potential cargeivers. I have estimated the effect of providing care (or not: dummy) on the life satisfaction level (from 0 to 10) using an OLS with pooled data, then a OLS with FE and then a2 step system GMM approach (introducing lags of the independent variable and of the endogenous variables) to deal with endogeneity issues, namely simultaneity, dynamic endogeneity and unobserved heterogeneity.
As I am also interested in a potential selection of caregivers in my sample, I wanted to perform a match between those who provide help (the treated) and those who do not (untreated) and then compare the differences. However, my difficulty comes from the application of such a method. As I have panel data on 9 years, I have first reshape my sample from long to wide but still stuck here... Indeed, an individual might decide to provide care in 2008 and 2009 then stop during few years and care again in 2017 and I am not sure how to deal with it.
I wonder whether I can match individuals per year ? If yes, I do not know how to aggreagte them then.

I hope that my explanation is clear enough.
Any kind of help would be appreciated, thanks a lot,

Bests
Marie