Hi all,
I have some douts about time lagging for my independent variables in multi-way FE panel data (reghddfe). I have this panel model with a health outcome (ho) as my dependent variable and socioeconomic and health services system indicators (hi, hi_1, hi_2 and hi_3) as independent variables. As one of my IV's is the unemployment rate (ur), and presumably with lagged effect over my DP, I also suppose that the present unemployment rate also affect the health outcome, in a cummulative or interactive way?!?

Let's say that my model is :

reghdfe ho ur gdp gini hi hi_1 hi_2 hi_3, absorb(state) vce(cluster state#year),

Suppose that I have ur (actual unemployment rate) and ur_1, ur_2 and ur_3 as unemployment rates lagged in 1, 2 and 3 years in my data set, and I want to observe te effect of three consecutive years of unemployment (or occupation rate) over health outcome (ho my DP).

Would it be correct to model:

reghdfe ho gdp gini hi hi_1 hi_2 hi_3 c.ur#c.ur_1#c.ur_2#c.ur_3, absorb(state) vce(cluster state#year)

, or, instead of using my own lagged data, to use the Stata “L" command for time lagged associated with unempolyment factor variable? So:


reghdfe ho gdp gini hi hi_1 hi_2 hi_3 c.ur#L1.c.ur#L2.c.ur#L3.c.ur, absorb(state) vce(cluster state#year)


Any suggestion for this model.

Thanks in advance.

Alexandre Bugelli