Hi there,

I am struggling to understand something relating to causal effects with panel data.

I have an unbalanced panel data set on the individual level (t=2008-2017).

I need to estimate three causal (or as causal as possible) effects
  1. having a job -> mental health
  2. finding a job -> mental health
  3. losing a job -> mental health
What models should I use to estimate these 3 different effects?

One thing I don't understand is that FE only uses within-unit variation. Could FE then estimate the 1st effect? Since it's time demeaning the data, but at the same time it feels wrong.

Finding/losing a job needs a difference in employment between 2 consecutive years. Let's say an individual has 2 observations: in 2010 he is not employed, in 2014 he is. Could you use this individual in the estimation of the 2nd effect? He goes from having no job to having a job, but it's unclear whether he became employed in 2014 or for example in 2011. If he became employed in 2011, including this individual would actually estimate the effect of becoming employed in year t (2011) on mental health in year t+3 (2014). Am I seeing this correctly? And is this something you should take into account, or does it not really matter?


Thank you in advance (: