IT Lab Session 8

Analyze the data set "Produc" in "plm" package

Pooled Affect Model

pool<-plm(log(pcap)~log(hwy) + log(water) + log(util) + log(pc) + log(gsp) + log(emp) + log(unemp), data=Produc, model=("pooling"), index = c("state", "year"))

Fixed Affect Model

fixed<-plm(log(pcap)~log(hwy) + log(water) + log(util) + log(pc) + log(gsp) + log(emp) + log(unemp), data=Produc, model=("within"), index = c("state", "year"))

Random Affect Model

random<-plm(log(pcap)~log(hwy) + log(water) + log(util) + log(pc) + log(gsp) + log(emp) + log(unemp), data=Produc, model=("random"), index = c("state", "year")) 

pFtest

 We cannot reject null hypothesis, so fixed is better

plmtest

We cannot reject null hypothesis, so pool is better


phtest

 
We should null hypothesis, so fixed is better

So by consolidating all the results, fixed affect model is better for "Produc" data