Hi, I am trying to estimate my model using fixed effect . but before that i did a unit root test and all my variables are stationary only in first difference. I also did a correlation test, which shows that one of my control variable is highly correlated to my explanatory variable, so in order to estimate my model using

areg lngdppercapita dl.lnmigrationinflow dl.lnpopulation dl.lncapitalstock dl.lnhumancapital y*,absorb(countryid)vce(cluster countryid)

I was wondering if i should estimate the model using the first difference of the variables and also lagged values, because i want to deal with reverse causality present in my model.is this correct?

and also what is the solution to the serial correlation of the control with explanatory variable?
Regards

lema