install.packages("plm")
#https://cran.r-project.org/web/packages/plm/vignettes/plmPackage.html
 library(plm)
## R da bulunan panel veri setleri 
  
data("EmplUK", package="plm")
data("Produc", package="plm")
data("Grunfeld", package="plm")
data("Wages", package="plm")

str(EmplUK) 
str(Produc) 
str(Grunfeld) 
head(Grunfeld)
tail(Grunfeld)
E <- pdata.frame(EmplUK, index=c("firm","year"), drop.index=TRUE, row.names=TRUE)
head(E)
head(attr(E, "index"))
summary(E$emp)
head(as.matrix(E$emp))
head(lag(E$emp, 0:2))
head(diff(E$emp), 10)
head(lag(E$emp, 2), 10)
head(Within(E$emp))
head(between(E$emp), 4)
head(Between(E$emp), 10)



#Several models can be estimated with plm by filling the model argument:
  
#the fixed effects model ("within"),
#the pooling model ("pooling"),
#the first-difference model ("fd"),
#the between model ("between"),
#the error components model ("random").



emp ~ wage + capital | lag(wage,1) + capital
emp ~ wage + capital | . -wage + lag(wage,1)
grun.fe <- plm(inv~value+capital, data = Grunfeld, model = "within")
grun.re <- plm(inv~value+capital, data = Grunfeld, model = "random")
summary(grun.re)
fixef(grun.fe, type = "dmean")
summary(fixef(grun.fe, type = "dmean"))

?plm
grun.twfe <- plm(inv~value+capital, data=Grunfeld, model="within", effect="twoways")
fixef(grun.twfe, effect="time")
grun.amem <- plm(inv~value+capital, data=Grunfeld,
                 model="random", random.method="amemiya")

ercomp(inv~value+capital, data=Grunfeld, method = "amemiya", effect = "twoways")

grun.tways <- plm(inv~value+capital, data = Grunfeld, effect = "twoways",
                  model = "random", random.method = "amemiya")
summary(grun.tways)

data("Hedonic", package = "plm")
Hed <- plm(mv~crim+zn+indus+chas+nox+rm+age+dis+rad+tax+ptratio+blacks+lstat,
           data = Hedonic, model = "random", index = "townid")
summary(Hed)


gw <- plm(inv~value+capital, data=Grunfeld, model="within")
gr <- plm(inv~value+capital, data=Grunfeld, model="random")
phtest(gw, gr)
pwtest(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp, data=Produc)
pcdtest(inv~value+capital, data=Grunfeld)
pcdtest(inv~value+capital, data=Grunfeld, model="within")