# 1. US economy in 90s US90<-read.table("US90.txt", header=T) attach(US90) # D <-read.csv("giffen.csv", header=T) # if you have a csv file summary(US90) summary(gdpgr) mean(inf) sd(inf) var(inf) plot(year,gdpgr,pch="*") points(year,inf,col="red",pch="+") plot(year,gdpgr,pch="*",main="GDP growth rate",xlab="year",ylab="GDP growth") abline(3,0,col="blue") par(mfrow=c(2,2)) plot(year, gdpgr, pch="*") plot(year, consgr, pch="#") plot(year, gdpcapgr, pch="%") plot(year, invgr, pch="&") # 2. More on plots x <- seq(0,2*pi,0.1) plot(x,cos(x),type="l") lines(x,sin(x),col="red",lwd=1) abline(h=0,lty=2) # 3. Regression lm(gdpgr~invgr) summary(lm(gdpgr~invgr)) lm(gdpgr~ 0 + invgr) lm(log(gdpgr)~log(consgr)+log(invgr)+log(producgr)) a <- lm(log(gdpgr)~log(consgr)+log(invgr)+log(producgr)) coef(a) fitted(a) resid(a) vcov(a) # Residual plots and GFW thm. m1 <- lm(gdpgr ~ inf + invgr + producgr + unemp + year) My <- lm(gdpgr ~ invgr + producgr + unemp + year) Mx <- lm(inf ~ invgr + producgr + unemp + year) aa <- lm(resid(My) ~ 0 + resid(Mx)) plot(resid(My),resid(Mx)) abline(aa) abline(v=0,lty=2) abline(h=0,lty=2) # Digression : quantile regression library(quantreg) # make sure that you install "quantreg" package first rq(gdpgr ~ inf) rq(log(gdpgr) ~ log(invgr)+log(unemp),tau=c(.25,.5,.75)) # Box-Cox Transformation library(MASS) # "MASS" package is already included in R. You need not install it g<-boxcox(gdpgr ~ invgr + unemp) g<-boxcox(gdpgr ~ invgr + producgr + unemp + year, lambda = seq(-.5,1.45,length=20))