#Import Grunfeld data

data("Grunfeld", package = "AER")

library("plm")

pg <- plm.data(subset(Grunfeld, firm != "American Steel"), c("firm", "year"))



#Fixed Effects

fm_fe <- plm(invest ~ value + capital, model = "within", data = pg)

summary(fm_fe)



#Random Effects

fm_reswar <- plm(invest ~ value + capital, data = pg, model = "random", random.method = "swar")

summary(fm_reswar)



#Pooled OLS

fm_ols <- plm(invest ~ value + capital, data = pg, model = "pooling")



## testing for individual effects

plmtest(fm_ols, effect="individual", type = "bp") #breush-pagan test for individual effects



## Other random effects models

fm_ream <- plm(invest ~ value + capital, data = pg, model = "random", random.method = "amemiya")

fm_rewh <- plm(invest ~ value + capital, data = pg, model = "random", random.method = "walhus")

fm_rener <- plm(invest ~ value + capital, data = pg, model = "random", random.method = "nerlove")



## Baltagi (2005), Tab. 2.1

rbind(

"OLS(pooled)" = coef(fm_ols),

"FE" = c(NA, coef(fm_fe)),

"RE-SwAr" = coef(fm_reswar),

"RE-Amemiya" = coef(fm_ream),

"RE-WalHus" = coef(fm_rewh),

"RE-Nerlove" = coef(fm_rener))



## Hausman test

phtest(fm_fe, fm_reswar)