Country fixed effects

Question

I am trying to estimate country fixed effect with country dummies.

fe1b <- plm( 
  bond_GDP_local ~ real_r + equity_volatility, model = 'within', data = panel_eme_filtered
)

This gives me same coefficients with below one:

fe1bc <- plm( 
  bond_GDP_local ~ real_r + equity_volatility +country_code, model = 'within', data = panel_eme_filtered
)

Even though I enter country dummies into my equation, I cannot see it in results. Does it mean that first model already incorporates it?

Thank you

Both of them are giving me this:

Oneway (individual) effect Within Model

Call:
plm(formula = bond_GDP_local ~ real_r + equity_volatility, data = panel_eme_filtered, 
    model = "within")

Balanced Panel: n=8, T=60, N=480

Residuals :
   Min. 1st Qu.  Median 3rd Qu.    Max. 
-2.7200 -0.3450 -0.0927  0.2200  5.6200 

Coefficients :
                       Estimate    Std. Error t-value Pr(>|t|)  
real_r            -0.0331088985  0.0171886368  -1.926   0.0547 .
equity_volatility -0.0000003838  0.0000006396  -0.600   0.5488  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Total Sum of Squares:    345.7
Residual Sum of Squares: 342.7
R-Squared:      0.008731
Adj. R-Squared: -0.01025
F-statistic: 2.06979 on 2 and 470 DF, p-value: 0.1274

Another Question: How can estimate robust panel time series data standard errors in this model?

Answer 1

Presumably panel_eme_filtered is a pdata.frame indexed with country_code ? If that is the case, then including country_code in the regression equation does not matter. An alternative way to do this is with lfe .

library(lfe)

fe2 <- felm(
  bond_GDP_local ~ real_r + equity_volatility | country_code,
  data = panel_eme_filtered
  )
summary(fe2, robust = T) # heteroskedastic robust SE's

You can also get clustered standard errors with

fe3 <- felm(
  bond_GDP_local ~ real_r + equity_volatility | country_code | 0 | country_code,
  data = panel_eme_filtered
  )
summary(fe3)