I have the following question or problem. I am currently using panel data to predict the hourly wage. I have only used the variable "union" as an influence variable from the initial model, but I assume an overestimation (Model 1). For this reason, I have now also included the variables educ and exp, but the coefficient of union has only changed slightly (Model 2). Since I have panel data, it makes sense to consider fixed effects. In model 3 I have included fixed time effects, but the coefficient has still hardly changed (model 3). But if I now include fixed individual effects, then it changes significantly, it almost halves (model 4). Now to the question. How do I know if fixed time or fixed individual effects make more sense? I would say purely intuitively that the consideration of fixed individual effects make more sense, because there the coefficient changes significantly more, but I am not sure? Which modeling would you prefer? Model 3 or Model 4? And why?
This is my code:
reg lnwage union, r *Model1 reg lnwage union exp educ, r * Model2 reg lnwage union exp educ i.year, r * Model3 xtreg lnwage union exp educ i.year, fe r *Model4