I want to test if
model_1 <- feols(auth ~ dummy_past1 + dummy_past2 + dummy_past3
| region + date_f, # Fixed Effects
data=df)
is just as good as
model_2 <- feols(auth ~ i(dummy_past1,specific_regions) + i(dummy_past2,specific_regions) + i(dummy_past3, specific_regions) # interaction(dummies * specific regions)
| region + date_f, # Fixed Effects
data=df)
If this was a normal linear regression I would conduct a lrtest (likelihood ratio test). As I heard that a waldtest can also be applied to panel data (?) I conducted a waldtest
waldtest(model_1, model_2). Yet, when doing that I get the warning: "Error in solve.default(vc[ovar, ovar]) : system is computationally singular: reciprocal condition number = 2.10749e-44"
Does someone know if doing a waldtest is the correct approach here, or if there are any other tests that I could do on plm or feols regressions? Or it would also be very helpful if you have ideas on how I could get the waldtest working.