FD is FE’s cousin, but in Stata, reg d.y d.x (manual first-differencing) gives different standard errors than xtreg, fd due to how Stata handles time gaps. For T=2, FD=FE. For T>2, FD is less efficient if errors are serially uncorrelated. But if errors follow a random walk, FD beats FE. Most Stata users never check.
If your diagnostics reveal heteroskedasticity or serial correlation, standard errors will be deflated, leading to false statistical significance. Fix this by adding vce(robust) or vce(cluster id) to your estimator: stata panel data
Run these after your main estimation.
Use xtdescribe to visualize the participation pattern of your cross-sectional units over time. It provides a clean text-based matrix showing which periods contain data for your entities. Summary Statistics FD is FE’s cousin, but in Stata, reg d