
Econometrics Assignment Solution Using R Programming
- 7th Jan, 2022
- 23:49 PM
library(AER) library(quantmod) library(NLP) #Q1 #1 data(CASchools) str(CASchools) CA<-CASchools CA$avg_score<-(CA$read+CA$math)/2 CA$size<-CA$students/CA$teachers #2 lm1<-lm(avg_score ~ income + I(income^2), data=CA) summary(lm1) #3 str(CA) lm2<-lm(avg_score ~ income + I(income^2) + income*grades,data=CA) summary(lm2) #4 lm3<-lm(log(avg_score) ~ log(income), data=CA) summary(lm3) #5 i<-1 CA$mathx<-ifelse(CA$math>CA$read,1,0) table(CA$mathx) lm4<-glm(mathx ~ size+ grades + income + expenditure , data=CA, family=binomial(link="probit")) lm5<-glm(mathx ~ size+ grades + income + expenditure , data=CA, family="binomial") summary(lm4) summary(lm5) #Q2 data(CigarettesSW) #1 Cigs<-CigarettesSW str(Cigs) Cigs_1995<-Cigs[which(Cigs$year==1995),] str(Cigs_1995) Cigs_1995$rprice<-Cigs_1995$price/Cigs_1995$cpi Cigs_1995$salestax<-Cigs_1995$taxs-Cigs_1995$tax summary(Cigs_1995$salestax) #2 lm_1<-lm(log(packs) ~ log(rprice), data= Cigs_1995) summary(lm_1) #3 iv_1<-ivreg(log(packs)~log(rprice)|salestax, data=Cigs_1995) summary(iv_1) summary(iv_1, diagnostics=T) #Wu-Hausman Tests indicate that there is no issue of endogeniety #Q3 US<-read.csv("US_Macro.csv") str(US) US_ts<-ts(US$GDP_Growth, frequency = 4, start=c(1957,1)) ar.ols(US_ts, order=1, demean=F, intercept =T) ar.ols(US_ts, order=2, demean=F, intercept =T)