############################################################################################################# # # PNAD 2009 # # 1) UF: unidade da federacao # 11 Rondônia # 12 Acre # 13 Amazonas # 14 Roraima # 15 Pará # 16 Amapá # 17 Tocantins # 21 Maranhão # 22 Piauí # 23 Ceará # 24 Rio Grande do Norte # 25 Paraíba # 26 Pernambuco # 27 Alagoas # 28 Sergipe # 29 Bahia # 31 Minas Gerais # 32 Espírito Santo # 33 Rio de Janeiro # 35 São Paulo # 41 Paraná # 42 Santa Catarina # 43 Rio Grande do Sul # 50 Mato Grosso do Sul # 51 Mato Grosso # 52 Goiás # 53 Distrito Federal # # 2) sexo: 2=masculino, 4=feminino # 3) raca/cor: 2=branca,4=preta,6=amarela,8=parda,0=indigena,9=sem declaracao # 4) hr_merc: Número de horas habitualmente trabalhadas por semana no trabalho principal da semana de referência # 5) hr_dom: Número de horas que dedicava normalmente por semana aos afazeres domésticos # 6) anos_estudo:1=sem instrucao e menos de 1 ano,2=1 ano,3=2 ano,15=14 anos,16=15 anos ou mais,17=nao determinados. # 7) rend_trab: Rendimento mensal de todos os trabalhos para pessoas de 10 anos ou mais de idade. # ############################################################################################################# pdf(file="pnad2009.pdf",width=15,height=10) setwd("/Users/hlopes/Desktop/TEACHING/2016-2to6-Econometria-graduacaoeconomia/atividade1/GenderWageGap") names = c("RO","AC","AM","RR","PA","AM","TO","MA","CE","RN","PR","PE","AL","SE","BA","MG","ES","RJ","SP","PR","SC","RS","MS","MT","GO","DF") data = read.table("pnad2009.txt",header=TRUE) data = data[data[,6]<17,] attach(data) n = nrow(data) renda =rend_trab ################################################## # Horas trabalho principal como funcao dos anos de estudo ################################################## median.hrmerc.h = rep(0,16) median.hrmerc.m = rep(0,16) for (i in 1:16){ median.hrmerc.h[i] = median(hr_merc[(anos_estudo==i)&(sexo==2)]) median.hrmerc.m[i] = median(hr_merc[(anos_estudo==i)&(sexo==4)]) } par(mfrow=c(1,2)) plot(anos_estudo,hr_merc,xlab="Anos de estudo",ylab="Horas trabalho principal",axes=FALSE,ylim=c(0,120)) axis(2);box();axis(1,at=1:16,lab=0:15) abline(lm(hr_merc[sexo==2]~anos_estudo[sexo==2]),col=2,lwd=3) abline(lm(hr_merc[sexo==4]~anos_estudo[sexo==4]),col=3,lwd=3) legend("topleft",legend=c("Homens","Mulheres"),col=2:3,lty=1,lwd=3) abline(h=40,lty=2) plot(1:16,median.hrmerc.h,xlab="Anos de estudo",ylab="Horas trabalho principal (mediana)",axes=FALSE,ylim=c(0,120),pch=16,type="b",col=2) axis(2);box();axis(1,at=1:16,lab=0:15) lines(1:16,median.hrmerc.m,col=3,type="b",pch=16) abline(h=40,lty=2) ########################################################## # Horas afazeres domésticos como funcao dos anos de estudo (por sexo) ########################################################## median.hrdom.h = rep(0,16) median.hrdom.m = rep(0,16) for (i in 1:16){ median.hrdom.h[i] = median(hr_dom[(anos_estudo==i)&(sexo==2)]) median.hrdom.m[i] = median(hr_dom[(anos_estudo==i)&(sexo==4)]) } par(mfrow=c(1,2)) plot(anos_estudo,hr_merc,xlab="Anos de estudo",ylab="Horas afazeres domésticos",axes=FALSE,ylim=c(0,120)) axis(2);box();axis(1,at=1:16,lab=0:15) abline(lm(hr_dom[sexo==2]~anos_estudo[sexo==2]),col=2,lwd=3) abline(lm(hr_dom[sexo==4]~anos_estudo[sexo==4]),col=3,lwd=3) legend("topleft",legend=c("Homens","Mulheres"),col=2:3,lty=1,lwd=3) abline(h=10,lty=2) abline(h=20,lty=2) plot(1:16,median.hrdom.h,xlab="Anos de estudo",ylab="Horas afazeres domésticos (mediana)",axes=FALSE,ylim=c(0,120),pch=16,type="b",col=2) axis(2);box();axis(1,at=1:16,lab=0:15) lines(1:16,median.hrdom.m,col=3,type="b",pch=16) abline(h=10,lty=2) abline(h=20,lty=2) #################################################### # Renda do trabalho como funcao dos anos de estudo (por sexo) #################################################### median.renda.h = rep(0,16) median.renda.m = rep(0,16) for (i in 1:16){ median.renda.h[i] = median(renda[(anos_estudo==i)&(sexo==2)]) median.renda.m[i] = median(renda[(anos_estudo==i)&(sexo==4)]) } par(mfrow=c(1,2)) plot(anos_estudo,renda,xlab="Anos de estudo",ylab="Rendimento mensal",axes=FALSE,ylim=c(0,20000)) axis(2);box();axis(1,at=1:16,lab=0:15) abline(lm(renda[(sexo==2)&(renda<20000)]~anos_estudo[(sexo==2)&(renda<20000)]),col=2,lwd=3) abline(lm(renda[(sexo==4)&(renda<20000)]~anos_estudo[(sexo==4)&(renda<20000)]),col=3,lwd=3) legend("topleft",legend=c("Homens","Mulheres"),col=2:3,lty=1,lwd=3) plot(1:16,median.renda.h,xlab="Anos de estudo",ylab="Rendimento mensal (mediano)",axes=FALSE,ylim=c(0,3000),pch=16,type="b",col=2) axis(2);box();axis(1,at=1:16,lab=0:15) lines(1:16,median.renda.m,col=3,type="b",pch=16) abline(h=500,lty=2) abline(h=1000,lty=2) abline(h=1500,lty=2) abline(h=2000,lty=2) ######################################################### # Renda do trabalho como funcao dos anos de estudo (por sexo e raca) ######################################################### quant.renda.h = array(0,c(16,2,3)) quant.renda.m = array(0,c(16,2,3)) for (i in 1:16){ quant.renda.h[i,1,] = quantile(renda[(anos_estudo==i)&(sexo==2)&(raca==2)],c(0.1,0.5,0.9)) quant.renda.h[i,2,] = quantile(renda[(anos_estudo==i)&(sexo==2)&((raca==4)|(raca==8))],c(0.1,0.5,0.9)) quant.renda.m[i,1,] = quantile(renda[(anos_estudo==i)&(sexo==4)&(raca==2)],c(0.1,0.5,0.9)) quant.renda.m[i,2,] = quantile(renda[(anos_estudo==i)&(sexo==4)&((raca==4)|(raca==8))],c(0.1,0.5,0.9)) } par(mfrow=c(2,3)) plot(1:16,quant.renda.h[,1,1],xlab="Anos de estudo",ylab="Rendimento mensal (quantil 10%)",axes=FALSE,ylim=c(400,1000),type="b",lwd=2) axis(2);box();axis(1,at=1:16,lab=0:15) lines(1:16,quant.renda.h[,2,1],col=2,type="b",lwd=2) lines(1:16,quant.renda.m[,1,1],col=3,type="b",lwd=2) lines(1:16,quant.renda.m[,2,1],col=4,type="b",lwd=2) legend("topleft",legend=c("Homen branco","Homen negro/pardo","Mulher branca","Mulher negra/parda"),col=1:4,lty=1,lwd=2) plot(1:16,quant.renda.h[,1,2],xlab="Anos de estudo",ylab="Rendimento mensal (mediano)",axes=FALSE,ylim=c(400,3000),type="b",lwd=2) axis(2);box();axis(1,at=1:16,lab=0:15) lines(1:16,quant.renda.h[,2,2],col=2,type="b",lwd=2) lines(1:16,quant.renda.m[,1,2],col=3,type="b",lwd=2) lines(1:16,quant.renda.m[,2,2],col=4,type="b",lwd=2) plot(1:16,quant.renda.h[,1,3],xlab="Anos de estudo",ylab="Rendimento mensal (quantil 90%)",axes=FALSE,ylim=c(400,8500),type="b",lwd=2) axis(2);box();axis(1,at=1:16,lab=0:15) lines(1:16,quant.renda.h[,2,3],col=2,type="b",lwd=2) lines(1:16,quant.renda.m[,1,3],col=3,type="b",lwd=2) lines(1:16,quant.renda.m[,2,3],col=4,type="b",lwd=2) plot(1:16,quant.renda.h[,1,1]/quant.renda.m[,2,1],xlab="Anos de estudo",ylab="Razao",axes=FALSE,type="b",lwd=2,ylim=c(0.9,2.5)) axis(2);box();axis(1,at=1:16,lab=0:15) lines(1:16,quant.renda.h[,2,1]/quant.renda.m[,2,1],col=2,type="b",lwd=2) lines(1:16,quant.renda.m[,1,1]/quant.renda.m[,2,1],col=3,type="b",lwd=2) abline(h=1,lty=2) abline(h=1.5,lty=2) abline(h=2,lty=2) legend("topleft",legend=c("Homen branco","Homen negro/pardo","Mulher branca"),col=1:3,lty=1,lwd=2) plot(1:16,quant.renda.h[,1,2]/quant.renda.m[,2,2],xlab="Anos de estudo",ylab="Razao",axes=FALSE,type="b",lwd=2,ylim=c(0.9,2.5)) axis(2);box();axis(1,at=1:16,lab=0:15) lines(1:16,quant.renda.h[,2,2]/quant.renda.m[,2,2],col=2,type="b",lwd=2) lines(1:16,quant.renda.m[,1,2]/quant.renda.m[,2,2],col=3,type="b",lwd=2) abline(h=1,lty=2) abline(h=1.5,lty=2) abline(h=2,lty=2) plot(1:16,quant.renda.h[,1,3]/quant.renda.m[,2,3],xlab="Anos de estudo",ylab="Razao",axes=FALSE,type="b",lwd=2,ylim=c(0.9,2.5)) axis(2);box();axis(1,at=1:16,lab=0:15) lines(1:16,quant.renda.h[,2,3]/quant.renda.m[,2,3],col=2,type="b",lwd=2) lines(1:16,quant.renda.m[,1,3]/quant.renda.m[,2,3],col=3,type="b",lwd=2) abline(h=1,lty=2) abline(h=1.5,lty=2) abline(h=2,lty=2) ##################################################################### # Renda do trabalho como funcao dos anos de estudo (por sexo e unidade da federacao) ##################################################################### estado = c("Amazonas","Pará","Pernambuco","Bahia","Rio de Janeiro","São Paulo", "Santa Catarina","Rio Grande do Sul","Mato Grosso do Sul","Distrito Federal") uf = c(13,15,26,29,33,35,42,43,50,53) quant.renda.h = array(0,c(10,16,3)) quant.renda.m = array(0,c(10,16,3)) for (i in 1:10) for (j in 1:16){ quant.renda.h[i,j,] = quantile(renda[((UF==uf[i])&(anos_estudo==j)&(sexo==2))],c(0.25,0.5,0.75)) quant.renda.m[i,j,] = quantile(renda[((UF==uf[i])&(anos_estudo==j)&(sexo==4))],c(0.25,0.5,0.75)) } par(mfrow=c(2,5)) for (i in 1:10){ plot(1:16,quant.renda.h[i,,2],xlab="Anos de estudo",ylab="Rendimento mensal mediano",axes=FALSE,ylim=c(450,5000)) axis(2);box();axis(1,at=seq(1,16,by=2),lab=seq(0,15,by=2)) points(1:16+0.1,quant.renda.m[i,,2],col=2) title(estado[i]) if(i==1){ legend("topleft",legend=c("Homens","Mulheres"),col=1:2,lty=1,lwd=3) } } par(mfrow=c(1,1)) plot(quant.renda.h[3,,2]/quant.renda.m[3,,2],type="b",ylim=c(0.8,3),lwd=2,xlab="Anos de estudo",ylab="Razao homen/mulher",main="Razao do rendimento mensal mediano",axes=FALSE,col=3) axis(2);box();axis(1,at=1:16,lab=0:15) for (i in 4:6) lines(quant.renda.h[i,,2]/quant.renda.m[i,,2],type="b",col=i,lwd=2) legend("topleft",legend=estado[3:6],col=3:6,lty=1,lwd=3) abline(h=1,lty=2) dev.off()