## Econometrics Task 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)