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CSO-measure-09-19.Rmd
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---
title: "CSO-measure-09-19"
author: "Millon, Ma Emilia"
date: "27/5/2021"
output: html_document
---
---
title: "Statistic Annex"
output: github_document
---
*The chart and tables correspond to the work publish in ....*
## Participation of Classes Socio Ocupational (CSO) throughtout the period 2009-2019 for Argentina
The source is Encuesta Permanente de Hogares (EPH), compiled by Instituto Nacional de Estadísticas y Censos de Argentina (INDEC)
### CSO 2019
```{r echo=FALSE, message=FALSE, warning=FALSE}
library(dplyr)
library(readxl)
library(xtable)
library(ggplot2)
library(scales)
library(eph)
eph4_2009 <- get_microdata(year = 2019,
trimester = 4,
type= "individual",
vars ="all" )
eph4_2009 <- as.data.frame(eph4_2009)
## Paso las variables a texto y corrijo
eph4_2009$PP04D_COD<- as.character(eph4_2009$PP04D_COD)
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="1"]="00001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="1001"]="01001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="2001"]="02001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="3001"]="03001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="4001"]="04001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="5001"]="05001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="5002"]="05002"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="6001"]="06001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="7001"]="07001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99999"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99998"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99997"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99993"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99991"]=""
eph4_2009$PP11D_COD<- as.character(eph4_2009$PP11D_COD)
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="1"]="00001"
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="1001"]="01001"
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="5002"]="05002"
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="7001"]="07001"
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99999"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99998"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99997"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99993"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99991"]=""
eph4_2009<-rename(eph4_2009, PARENTESCO=CH03, EDAD=CH06, COD_OCUPACION=PP04D_COD, NUM_EMP=PP04C, GENERO=CH04 ,
EQUIPO=PP05C_1 , LOCAL=PP05C_2, VEHICULO=PP05C_3, COD_OCUPACION2=PP11D_COD, NUM_EMP2=PP11C)
############ Armo ID de jefes de familia y un nuevo pondera e ITF ####
eph4_2009<-mutate(eph4_2009, hogar_id=paste(eph4_2009$CODUSU,eph4_2009$NRO_HOGAR, sep=""))
eph4_2009<- eph4_2009 %>%
group_by(hogar_id) %>%
mutate(CASOS= sum(PONDERA))
eph4_2009<- eph4_2009 %>%
group_by(hogar_id) %>%
mutate(IPCF_SUM= sum(IPCF))
### CODIGO DE OCUPACION CNO
eph4_2009<- eph4_2009 %>% mutate(CARACTEROCUP=substr(COD_OCUPACION, star=1, stop=2))
eph4_2009$CARACTEROCUP[eph4_2009$CARACTEROCUP==""]=NA
eph4_2009<- eph4_2009 %>% mutate(CARACTEROCUP2=substr(COD_OCUPACION2, star=1, stop=2))
eph4_2009$CARACTEROCUP2[eph4_2009$CARACTEROCUP2==""]=NA
eph4_2009<-mutate(eph4_2009, CARACTER_OCUP= ifelse( is.na(CARACTEROCUP), CARACTEROCUP2,CARACTEROCUP))
eph4_2009<- eph4_2009 %>% mutate(JERARQUIA=substr(COD_OCUPACION, star=3, stop=3))
eph4_2009$JERARQUIA[eph4_2009$JERARQUIA==""]<- NA
eph4_2009$JERARQUIA[eph4_2009$JERARQUIA=="9"]<- NA
eph4_2009<- eph4_2009 %>% mutate(JERARQUIA2=substr(COD_OCUPACION2, star=3, stop=3))
eph4_2009$JERARQUIA2[eph4_2009$JERARQUIA2==""]<- NA
eph4_2009$JERARQUIA2[eph4_2009$JERARQUIA2=="9"]<- NA
eph4_2009<-mutate(eph4_2009, jerarquia= ifelse( is.na(JERARQUIA), JERARQUIA2,JERARQUIA))
eph4_2009$jerarquia<- as.numeric(eph4_2009$jerarquia)
eph4_2009<- eph4_2009 %>% mutate(CALIFICACION=substr(COD_OCUPACION, star=5, stop=5))
eph4_2009$CALIFICACION[eph4_2009$CALIFICACION==""]<- NA
eph4_2009$CALIFICACION[eph4_2009$CALIFICACION=="9"]<- NA
eph4_2009$CALIFICACION[eph4_2009$CALIFICACION=="8"]<- NA
eph4_2009$CALIFICACION[eph4_2009$CALIFICACION=="7"]<- NA
eph4_2009<- eph4_2009 %>% mutate(CALIFICACION2=substr(COD_OCUPACION2,
star=5, stop=5))
eph4_2009$CALIFICACION2[eph4_2009$CALIFICACION2==""]<- NA
eph4_2009$CALIFICACION2[eph4_2009$CALIFICACION2=="9"]<- NA
eph4_2009$CALIFICACION2[eph4_2009$CALIFICACION2=="8"]<- NA
eph4_2009$CALIFICACION2[eph4_2009$CALIFICACION2=="7"]<- NA
eph4_2009<-mutate(eph4_2009, calificacion= ifelse( is.na(CALIFICACION), CALIFICACION2,CALIFICACION))
eph4_2009$calificacion<- as.numeric(eph4_2009$calificacion)
#table(eph4_2009$calificacion, exclude=NULL)
######### ESTADO SEGUN MERCADO LABORAL
eph4_2009$ESTADO<-as.factor(eph4_2009$ESTADO)
eph4_2009$ESTADO=factor(eph4_2009$ESTADO, labels=c("Sin entrevista", "Ocupado", "Desocupado","Inactivo","Menor"))
eph4_2009$CAT_OCUP[eph4_2009$CAT_OCUP==9]<- 0
eph4_2009<- eph4_2009 %>% mutate(CAT_OCUP2=CAT_OCUP)
eph4_2009$CAT_OCUP2<-as.factor(eph4_2009$CAT_OCUP2)
eph4_2009$CAT_OCUP2=factor(eph4_2009$CAT_OCUP2, labels=c(NA, "Patron", "Cuenta Propia", "Obrero",
"Trab_flia"))
############## EMPRESA ( NUM_EMP )
eph4_2009<- eph4_2009 %>% mutate(EMPRESA= ifelse(NUM_EMP>0 & NUM_EMP<6, 1
, ifelse(NUM_EMP>5 & NUM_EMP<99, 2, 0)))
eph4_2009$EMPRESA[eph4_2009$NUM_EMP==99 & eph4_2009$PP04C99==1]=1
eph4_2009$EMPRESA[eph4_2009$NUM_EMP==99 & eph4_2009$PP04C99==2]=2
eph4_2009$EMPRESA[eph4_2009$NUM_EMP==99 & eph4_2009$PP04C99==3]=2
eph4_2009$EMPRESA[eph4_2009$NUM_EMP==99 & eph4_2009$PP04C99==9]=0
eph4_2009$EMPRESA[eph4_2009$NUM_EMP==99 & eph4_2009$PP04C99==9]=0
eph4_2009$EMPRESA[is.na(eph4_2009$EMPRESA)]=0
eph4_2009<- eph4_2009 %>% mutate(EMPRESA2= ifelse(NUM_EMP2>0 & NUM_EMP2<6, 1
, ifelse(NUM_EMP2>5 & NUM_EMP2<99, 2, 0)))
eph4_2009$EMPRESA2[eph4_2009$NUM_EMP2==99 & eph4_2009$PP11C99==1]=1
eph4_2009$EMPRESA2[eph4_2009$NUM_EMP2==99 & eph4_2009$PP11C99==2]=2
eph4_2009$EMPRESA2[eph4_2009$NUM_EMP2==99 & eph4_2009$PP11C99==3]=2
eph4_2009$EMPRESA2[eph4_2009$NUM_EMP2==99 & eph4_2009$PP11C99==9]=0
eph4_2009$EMPRESA2[is.na(eph4_2009$EMPRESA2)]=0
eph4_2009<- eph4_2009 %>% mutate(empresa= EMPRESA+EMPRESA2)
############## SERVICIO DOMESTICO
eph4_2009<- eph4_2009 %>% mutate(SERV_DOM= ifelse(CARACTER_OCUP=="55", 1
, ifelse( is.na(CARACTER_OCUP), NA, 2)))
########## MEDIOS DE PRODUCCIÓN
####creo variable propietario de al menos un item PROP_MEDIO
eph4_2009<- eph4_2009 %>% mutate(PROP_MEDIO= ifelse(EQUIPO==1 | LOCAL==1 | VEHICULO==1, 1 ,
ifelse(EQUIPO==2 | LOCAL==2 | VEHICULO==2, 1 ,
ifelse(EQUIPO==3 | LOCAL==3 | VEHICULO==3, 2 ,
NA))) )
#Si tiene o le prestan alguno de los tres se lo considera propietario
########## ******** CLASES SOCIALES ********
############# PROPIETARIAS/OS ##################
eph4_2009<- eph4_2009 %>% mutate( PROPIETARIO= ifelse(CAT_OCUP==1 & empresa==1, 1,
ifelse(CAT_OCUP==1 & empresa==2, 2,
ifelse(CAT_OCUP==1 & empresa==0,
3 , NA))) )
############# DIRECTIVOS/AS ########################
eph4_2009<- eph4_2009 %>% mutate( DIRECCION= ifelse(CAT_OCUP==3 & SERV_DOM!=1 &
jerarquia==0 & empresa==1, 1,
ifelse(CAT_OCUP==3 & SERV_DOM!=1 &
jerarquia==0 & empresa==2,
2 ,
ifelse(CAT_OCUP==3 & SERV_DOM!=1 &
jerarquia==0 & empresa==0,
3, NA))) )
############# ASALARIADAS/OS ########################
eph4_2009<- eph4_2009 %>% mutate( ASALARIAD= ifelse(CAT_OCUP==3 & SERV_DOM!=1 &
jerarquia==2 , 1,
ifelse(CAT_OCUP==3 & SERV_DOM!=1 & jerarquia==3 &
calificacion==1, 2,
ifelse(CAT_OCUP==3 & SERV_DOM!=1 & jerarquia==3 &
calificacion==2, 3,
ifelse(CAT_OCUP==3 & SERV_DOM!=1 & jerarquia==3 &
calificacion==3, 4,
ifelse(CAT_OCUP==3 & SERV_DOM!=1 & jerarquia==3 &
calificacion==4, 5,
NA )))) ) )
eph4_2009$ASALARIAD[eph4_2009$CAT_OCUP==3 & eph4_2009$SERV_DOM!=1 &
is.na(eph4_2009$jerarquia) & is.na(eph4_2009$calificacion)]=6
eph4_2009$ASALARIAD[eph4_2009$CAT_OCUP==3 & eph4_2009$SERV_DOM!=1 &
is.na(eph4_2009$jerarquia) & (eph4_2009$calificacion==1 |
eph4_2009$calificacion==2 | eph4_2009$calificacion==3 |
eph4_2009$calificacion==4) ]=6
eph4_2009$ASALARIAD[eph4_2009$CAT_OCUP==3 & eph4_2009$SERV_DOM!=1 &
eph4_2009$jerarquia==3 & is.na(eph4_2009$calificacion)]=7
# el 6 son los empleados sin jerarqui ni calificaicon especificada
# el 7 son los asalariados empleados sin calificar.
############# AUTONOMAS/OS ########################
eph4_2009<- eph4_2009 %>% mutate( AUTONOM= ifelse(CAT_OCUP==2 & SERV_DOM!=1 , 4,
NA ))
eph4_2009$AUTONOM[eph4_2009$CAT_OCUP==2 & eph4_2009$SERV_DOM!=1 &
eph4_2009$PROP_MEDIO==1 ]=2
eph4_2009$AUTONOM[eph4_2009$CAT_OCUP==2 & eph4_2009$SERV_DOM!=1 &
eph4_2009$PROP_MEDIO==2 ]=3
eph4_2009$AUTONOM[eph4_2009$CAT_OCUP==2 & eph4_2009$SERV_DOM!=1 & eph4_2009$calificacion==1]=1
#1 es autonomo profesional
#2 es autonomo con medio produccion
#3 es autonomo SIN medio produccion
#4 es autonomo pero no sabemos si tiene medios de produccion
########### Tabla resumen 1 ###############
eph4_2009<- eph4_2009 %>% mutate( CS= PROPIETARIO)
eph4_2009$CS[eph4_2009$PROPIETARIO==3]=NA
eph4_2009$CS[eph4_2009$DIRECCION==1]=1
eph4_2009$CS[eph4_2009$DIRECCION==2]=3
eph4_2009$CS[eph4_2009$ASALARIAD==1]=4
eph4_2009$CS[eph4_2009$ASALARIAD==2]=5
eph4_2009$CS[eph4_2009$ASALARIAD==3]=6
eph4_2009$CS[eph4_2009$ASALARIAD==4]=7
eph4_2009$CS[eph4_2009$ASALARIAD==5]=8
eph4_2009$CS[eph4_2009$AUTONOM==1]=9
eph4_2009$CS[eph4_2009$AUTONOM==2]=10
eph4_2009$CS[eph4_2009$AUTONOM==2 & is.na(eph4_2009$calificacion)]=NA
eph4_2009$CS[eph4_2009$AUTONOM==3]=11
eph4_2009$CS[eph4_2009$AUTONOM==3 & is.na(eph4_2009$calificacion)]=NA
eph4_2009$CS[eph4_2009$AUTONOM==4]=11
eph4_2009$CS[eph4_2009$AUTONOM==4 & is.na(eph4_2009$calificacion)]=NA
eph4_2009$CS[eph4_2009$SERV_DOM==1]=12
weighted.sd<-function(x, w) ( (sum(w*x*x)/sum(w)) - weighted.mean(x,w)^2 )^.5
eph4_2009<- eph4_2009 %>% mutate( IT= P47T*PONDII)
eph4_2009 <- eph4_2009 %>%
group_by(hogar_id) %>%
mutate(CS_total= CS[which(PARENTESCO==1)] )
eph4_2009<- eph4_2009 %>% mutate( IOP= ifelse( PARENTESCO==1, P21, NA ))
##### Armo cuadro final
cuadro_final <- eph4_2009 %>% group_by(CS_total) %>%
summarise( N = sum(PONDERA, na.rm = TRUE),
N2 = sum(PONDIH, na.rm = TRUE),
mean=weighted.mean(IPCF,PONDIH),
mean2=weighted.mean(ITF,PONDIH),
mean3=weighted.mean(P47T,PONDII, na.rm = TRUE),
mean4=weighted.mean(IOP,PONDIIO, na.rm = TRUE),
sd=weighted.sd(IPCF,PONDIH),
n=n(),
sum_ing = sum(IT, na.rm = TRUE) )
cuadro_final <- cuadro_final %>% filter(!is.na(CS_total)) %>%
mutate( Part.= (N/sum(N, na.rm = TRUE))*100)
cuadro_final <- cuadro_final %>% filter(!is.na(CS_total)) %>%
mutate( Part.2= (N2/sum(N2, na.rm = TRUE))*100)
cuadro_final <- cuadro_final %>% filter(!is.na(CS_total)) %>%
mutate( Part_ing= (sum_ing/sum(sum_ing, na.rm = TRUE))*100)
cuadro_final <- cuadro_final %>%
mutate( CV_N=ifelse( N<100001 , "20" ,
ifelse( N>99999 & N<150000 , "19.8" ,
ifelse( N>149999 & N<200000 , "14.5" ,
ifelse( N>199999 & N<250000 , "11.6" ,
ifelse( N>249999 & N<300000 , "9.8" ,
ifelse( N>299999 & N<350000 , "8.5" ,
ifelse( N>349999 & N<400000 , "7.5" ,
ifelse( N>399999 & N<450000 , "6.8" ,
ifelse( N>449999 & N<500000 , "6.2" ,
ifelse( N>499999 & N<550000 , "5.7" ,
ifelse( N>549999 & N<600000 , "5.3" ,
ifelse( N>599999 & N<650000 , "5.0" ,
ifelse( N>649999 & N<700000 , "4.7" ,
ifelse( N>699999 & N<750000 , "4.4" ,
ifelse( N>749999 & N<800000 , "4.2" ,
ifelse( N>799999 & N<850000 , "4.0" ,
ifelse( N>849999 & N<900000 , "3.8" ,
ifelse( N>899999 & N<950000 , "3.6" ,
ifelse( N>949999 & N<1000000 , "3.5" ,
ifelse( N>999999 & N<1050000 , "3.4" ,
ifelse( N>1049999 & N<1100000 , "3.2" ,
ifelse( N>1099999 & N<1150000 , "3.1" ,
ifelse( N>1149999 & N<1200000 , "3.0" ,
ifelse( N>1199999 & N<1300000 , "2.9" ,
ifelse( N>1299999 & N<1400000 , "2.7" ,
ifelse( N>1399999 & N<1500000 , "2.6" ,
ifelse( N>1499999 & N<1600000 , "2.5" ,
ifelse( N>1599999 & N<1700000 , "2.3" ,
ifelse( N>1699999 & N<1800000 , "2.2" ,
ifelse( N>1799999 & N<1900000 , "2.1" ,
ifelse( N>1899999 & N<2100000 , "2.0" ,
ifelse( N>2199999 & N<2300000 , "1.9" ,
ifelse( N>2299999 & N<2500000 , "1.8" ,
ifelse( N>2499999 & N<2700000 , "1.7" ,
ifelse( N>2649999 & N<2900000 , "1.6" ,
ifelse( N>2900000, "1.5", NA
) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) )
##################### coef act ###################
read<- "https://infra.datos.gob.ar/catalog/sspm/dataset/25/distribution/25.2/download/indice-precios-implicitos-oferta-demanda-globales-valores-trimestrales-base-2004.csv"
DPBI<- read.csv(read, header = TRUE)
DPBI<- data.frame(DPBI[,c(1:2)])
coef_act<- DPBI[67,2]/DPBI[64,2]-1
cuadro_final$mean <- cuadro_final$mean*(1+coef_act)
cuadro_final$mean2 <- cuadro_final$mean2*(1+coef_act)
cuadro_final$mean3 <- cuadro_final$mean3*(1+coef_act)
cuadro_final$mean4 <- cuadro_final$mean4*(1+coef_act)
cuadro_final<- as.data.frame(cuadro_final)
Total<- c(14, sum(cuadro_final$N, na.rm = TRUE),sum(cuadro_final$N2, na.rm = TRUE), weighted.mean(cuadro_final$mean,cuadro_final$N2), weighted.mean(cuadro_final$mean2,cuadro_final$N2),weighted.mean(cuadro_final$mean3,cuadro_final$N2), weighted.mean(cuadro_final$mean4,cuadro_final$N2), weighted.mean(cuadro_final$sd,cuadro_final$N2) , sum(cuadro_final$n, na.rm = TRUE),sum(cuadro_final$sum_ing, na.rm = TRUE), sum(cuadro_final$Part., na.rm = TRUE), sum(cuadro_final$Part.2, na.rm = TRUE), sum(cuadro_final$Part_ing, na.rm = TRUE), "" )
cuadro_final[nrow(cuadro_final) + 1, ] <- Total
cuadro_final<- as.data.frame(apply(cuadro_final, MARGIN=2, FUN=as.numeric ))
cuadro_final$CS_total<-as.factor(cuadro_final$CS_total)
cuadro_final$CS_total=factor(cuadro_final$CS_total, labels=c("Owner or director of a Small or Medium-Sized enterprise",
"Owner of a big firm",
"Director/Manager of big firm",
"Chief/Supervision (Salaried)",
"Salaried Professional",
"Salaried Technician",
"Autonomous Professional",
"Salaried Operative" ,
"Salaried Low Qualification",
"Autonomous worker with means of production",
"Autonomous worker without means of production",
"Household Employee for Care and reproductive work", "Total"))
## pongo los formatos que quiero
cuadro_final$CV<- sprintf("%.2f%%", cuadro_final$CV )
cuadro_final$Part.<- sprintf("%.2f%%", cuadro_final$Part. )
cuadro_final$Part_ing <- sprintf("%.2f%%", cuadro_final$Part_ing )
cuadro_final$N <- format(cuadro_final$N, digits=0, decimal.mark=".", big.mark=",", scientific = FALSE )
cuadro_final$mean <- format(cuadro_final$mean, digits=0, decimal.mark=".", big.mark=",", scientific = FALSE )
cuadro_final$mean2 <- format(cuadro_final$mean2, digits=0, decimal.mark=".", big.mark=",", scientific = FALSE )
cuadro_final$mean3 <- format(cuadro_final$mean3, digits=0, decimal.mark=".", big.mark=",", scientific = FALSE )
cuadro_final$mean4 <- format(cuadro_final$mean4, digits=0, decimal.mark=".", big.mark=",", scientific = FALSE )
## ordeno cuadro final de salida
cuadro_CS419<- cuadro_final[, c( "CS_total", "N", "Part.", "CV_N" , "mean","mean2", "Part_ing", "n" ) ]
colnames(cuadro_CS419)<- c("CSO", "People", "% Part.", "Income percapita", "Income household", "% Part. Income", "Coefficient of Variation CSO", "sample" )
cuadro_CS419
#write.table(eph4_2019, file = "G:/Mi unidad/INVESTIGACION/clases sociales/bases de datos/eph419_CSO.csv", sep = ",", col.names = TRUE, row.names = FALSE)
```
### CSO 2018
```{r echo=FALSE, message=FALSE, warning=FALSE}
library(dplyr)
library(readxl)
library(xtable)
library(ggplot2)
library(scales)
library(eph)
eph4_2009 <- get_microdata(year = 2018,
trimester = 4,
type= "individual",
vars ="all" )
eph4_2009 <- as.data.frame(eph4_2009)
## Paso las variables a texto y corrijo
#eph4_2009$PP04D_COD<- as.character(eph4_2009$PP04D_COD)
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="1"]="00001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="1001"]="01001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="2001"]="02001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="3001"]="03001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="4001"]="04001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="5001"]="05001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="5002"]="05002"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="6001"]="06001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="7001"]="07001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99999"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99998"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99997"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99993"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99994"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99991"]=""
#eph4_2009$PP11D_COD<- as.character(eph4_2009$PP11D_COD)
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="1"]="00001"
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="1001"]="01001"
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="5002"]="05002"
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="7001"]="07001"
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99999"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99998"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99997"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99993"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99992"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99991"]=""
eph4_2009<-rename(eph4_2009, PARENTESCO=CH03, EDAD=CH06, COD_OCUPACION=PP04D_COD, NUM_EMP=PP04C, GENERO=CH04 ,
EQUIPO=PP05C_1 , LOCAL=PP05C_2, VEHICULO=PP05C_3, COD_OCUPACION2=PP11D_COD, NUM_EMP2=PP11C)
############ Armo ID de jefes de familia y un nuevo pondera e ITF ####
eph4_2009<-mutate(eph4_2009, hogar_id=paste(eph4_2009$CODUSU,eph4_2009$NRO_HOGAR, sep=""))
eph4_2009<- eph4_2009 %>%
group_by(hogar_id) %>%
mutate(CASOS= sum(PONDERA))
eph4_2009<- eph4_2009 %>%
group_by(hogar_id) %>%
mutate(IPCF_SUM= sum(IPCF))
### CODIGO DE OCUPACION CNO
eph4_2009<- eph4_2009 %>% mutate(CARACTEROCUP=substr(COD_OCUPACION, star=1, stop=2))
eph4_2009$CARACTEROCUP[eph4_2009$CARACTEROCUP==""]=NA
eph4_2009<- eph4_2009 %>% mutate(CARACTEROCUP2=substr(COD_OCUPACION2, star=1, stop=2))
eph4_2009$CARACTEROCUP2[eph4_2009$CARACTEROCUP2==""]=NA
eph4_2009<-mutate(eph4_2009, CARACTER_OCUP= ifelse( is.na(CARACTEROCUP), CARACTEROCUP2,CARACTEROCUP))
#table(eph4_2009$CARACTER_OCUP, exclude=NULL)
eph4_2009<- eph4_2009 %>% mutate(JERARQUIA=substr(COD_OCUPACION, star=3, stop=3))
eph4_2009$JERARQUIA[eph4_2009$JERARQUIA==""]<- NA
eph4_2009$JERARQUIA[eph4_2009$JERARQUIA=="9"]<- NA
eph4_2009<- eph4_2009 %>% mutate(JERARQUIA2=substr(COD_OCUPACION2, star=3, stop=3))
eph4_2009$JERARQUIA2[eph4_2009$JERARQUIA2==""]<- NA
eph4_2009$JERARQUIA2[eph4_2009$JERARQUIA2=="9"]<- NA
eph4_2009<-mutate(eph4_2009, jerarquia= ifelse( is.na(JERARQUIA), JERARQUIA2,JERARQUIA))
eph4_2009$jerarquia<- as.numeric(eph4_2009$jerarquia)
#table(eph4_2009$jerarquia, exclude=NULL)
eph4_2009<- eph4_2009 %>% mutate(CALIFICACION=substr(COD_OCUPACION, star=5, stop=5))
eph4_2009$CALIFICACION[eph4_2009$CALIFICACION==""]<- NA
eph4_2009$CALIFICACION[eph4_2009$CALIFICACION=="9"]<- NA
eph4_2009$CALIFICACION[eph4_2009$CALIFICACION=="8"]<- NA
eph4_2009$CALIFICACION[eph4_2009$CALIFICACION=="7"]<- NA
eph4_2009<- eph4_2009 %>% mutate(CALIFICACION2=substr(COD_OCUPACION2,
star=5, stop=5))
eph4_2009$CALIFICACION2[eph4_2009$CALIFICACION2==""]<- NA
eph4_2009$CALIFICACION2[eph4_2009$CALIFICACION2=="9"]<- NA
eph4_2009$CALIFICACION2[eph4_2009$CALIFICACION2=="8"]<- NA
eph4_2009$CALIFICACION2[eph4_2009$CALIFICACION2=="7"]<- NA
eph4_2009<-mutate(eph4_2009, calificacion= ifelse( is.na(CALIFICACION), CALIFICACION2,CALIFICACION))
eph4_2009$calificacion<- as.numeric(eph4_2009$calificacion)
######### ESTADO SEGUN MERCADO LABORAL
eph4_2009$ESTADO<-as.factor(eph4_2009$ESTADO)
eph4_2009$ESTADO=factor(eph4_2009$ESTADO, labels=c("Sin entrevista", "Ocupado", "Desocupado","Inactivo","Menor"))
eph4_2009$CAT_OCUP[eph4_2009$CAT_OCUP==9]<- 0
eph4_2009<- eph4_2009 %>% mutate(CAT_OCUP2=CAT_OCUP)
eph4_2009$CAT_OCUP2<-as.factor(eph4_2009$CAT_OCUP2)
eph4_2009$CAT_OCUP2=factor(eph4_2009$CAT_OCUP2, labels=c(NA, "Patron", "Cuenta Propia", "Obrero",
"Trab_flia"))
############## EMPRESA ( NUM_EMP )
eph4_2009<- eph4_2009 %>% mutate(EMPRESA= ifelse(NUM_EMP>0 & NUM_EMP<6, 1
, ifelse(NUM_EMP>5 & NUM_EMP<99, 2, 0)))
eph4_2009$EMPRESA[eph4_2009$NUM_EMP==99 & eph4_2009$PP04C99==1]=1
eph4_2009$EMPRESA[eph4_2009$NUM_EMP==99 & eph4_2009$PP04C99==2]=2
eph4_2009$EMPRESA[eph4_2009$NUM_EMP==99 & eph4_2009$PP04C99==3]=2
eph4_2009$EMPRESA[eph4_2009$NUM_EMP==99 & eph4_2009$PP04C99==9]=0
eph4_2009$EMPRESA[eph4_2009$NUM_EMP==99 & eph4_2009$PP04C99==9]=0
eph4_2009$EMPRESA[is.na(eph4_2009$EMPRESA)]=0
eph4_2009<- eph4_2009 %>% mutate(EMPRESA2= ifelse(NUM_EMP2>0 & NUM_EMP2<6, 1
, ifelse(NUM_EMP2>5 & NUM_EMP2<99, 2, 0)))
eph4_2009$EMPRESA2[eph4_2009$NUM_EMP2==99 & eph4_2009$PP11C99==1]=1
eph4_2009$EMPRESA2[eph4_2009$NUM_EMP2==99 & eph4_2009$PP11C99==2]=2
eph4_2009$EMPRESA2[eph4_2009$NUM_EMP2==99 & eph4_2009$PP11C99==3]=2
eph4_2009$EMPRESA2[eph4_2009$NUM_EMP2==99 & eph4_2009$PP11C99==9]=0
eph4_2009$EMPRESA2[is.na(eph4_2009$EMPRESA2)]=0
eph4_2009<- eph4_2009 %>% mutate(empresa= EMPRESA+EMPRESA2)
############## SERVICIO DOMESTICO
eph4_2009<- eph4_2009 %>% mutate(SERV_DOM= ifelse(CARACTER_OCUP=="55", 1
, ifelse( is.na(CARACTER_OCUP), NA, 2)))
########## MEDIOS DE PRODUCCIÓN
####creo variable propietario de al menos un item PROP_MEDIO
eph4_2009<- eph4_2009 %>% mutate(PROP_MEDIO= ifelse(EQUIPO==1 | LOCAL==1 | VEHICULO==1, 1 ,
ifelse(EQUIPO==2 | LOCAL==2 | VEHICULO==2, 1 ,
ifelse(EQUIPO==3 | LOCAL==3 | VEHICULO==3, 2 ,
NA))) )
#Si tiene o le prestan alguno de los tres se lo considera propietario
########## ******** CLASES SOCIALES ********
############# PROPIETARIAS/OS ##################
eph4_2009<- eph4_2009 %>% mutate( PROPIETARIO= ifelse(CAT_OCUP==1 & empresa==1, 1,
ifelse(CAT_OCUP==1 & empresa==2, 2,
ifelse(CAT_OCUP==1 & empresa==0,
3 , NA))) )
############# DIRECTIVOS/AS ########################
eph4_2009<- eph4_2009 %>% mutate( DIRECCION= ifelse(CAT_OCUP==3 & SERV_DOM!=1 &
jerarquia==0 & empresa==1, 1,
ifelse(CAT_OCUP==3 & SERV_DOM!=1 &
jerarquia==0 & empresa==2,
2 ,
ifelse(CAT_OCUP==3 & SERV_DOM!=1 &
jerarquia==0 & empresa==0,
3, NA))) )
############# ASALARIADAS/OS ########################
eph4_2009<- eph4_2009 %>% mutate( ASALARIAD= ifelse(CAT_OCUP==3 & SERV_DOM!=1 &
jerarquia==2 , 1,
ifelse(CAT_OCUP==3 & SERV_DOM!=1 & jerarquia==3 &
calificacion==1, 2,
ifelse(CAT_OCUP==3 & SERV_DOM!=1 & jerarquia==3 &
calificacion==2, 3,
ifelse(CAT_OCUP==3 & SERV_DOM!=1 & jerarquia==3 &
calificacion==3, 4,
ifelse(CAT_OCUP==3 & SERV_DOM!=1 & jerarquia==3 &
calificacion==4, 5,
NA )))) ) )
eph4_2009$ASALARIAD[eph4_2009$CAT_OCUP==3 & eph4_2009$SERV_DOM!=1 &
is.na(eph4_2009$jerarquia) & is.na(eph4_2009$calificacion)]=6
eph4_2009$ASALARIAD[eph4_2009$CAT_OCUP==3 & eph4_2009$SERV_DOM!=1 &
is.na(eph4_2009$jerarquia) & (eph4_2009$calificacion==1 |
eph4_2009$calificacion==2 | eph4_2009$calificacion==3 |
eph4_2009$calificacion==4) ]=6
eph4_2009$ASALARIAD[eph4_2009$CAT_OCUP==3 & eph4_2009$SERV_DOM!=1 &
eph4_2009$jerarquia==3 & is.na(eph4_2009$calificacion)]=7
# el 6 son los empleados sin jerarqui ni calificaicon especificada
# el 7 son los asalariados empleados sin calificar.
############# AUTONOMAS/OS ########################
eph4_2009<- eph4_2009 %>% mutate( AUTONOM= ifelse(CAT_OCUP==2 & SERV_DOM!=1 , 4,
NA ))
eph4_2009$AUTONOM[eph4_2009$CAT_OCUP==2 & eph4_2009$SERV_DOM!=1 &
eph4_2009$PROP_MEDIO==1 ]=2
eph4_2009$AUTONOM[eph4_2009$CAT_OCUP==2 & eph4_2009$SERV_DOM!=1 &
eph4_2009$PROP_MEDIO==2 ]=3
eph4_2009$AUTONOM[eph4_2009$CAT_OCUP==2 & eph4_2009$SERV_DOM!=1 & eph4_2009$calificacion==1]=1
#1 es autonomo profesional
#2 es autonomo con medio produccion
#3 es autonomo SIN medio produccion
#4 es autonomo pero no sabemos si tiene medios de produccion
########### Tabla resumen 1 ###############
eph4_2009<- eph4_2009 %>% mutate( CS= PROPIETARIO)
eph4_2009$CS[eph4_2009$PROPIETARIO==3]=NA
eph4_2009$CS[eph4_2009$DIRECCION==1]=1
eph4_2009$CS[eph4_2009$DIRECCION==2]=3
eph4_2009$CS[eph4_2009$ASALARIAD==1]=4
eph4_2009$CS[eph4_2009$ASALARIAD==2]=5
eph4_2009$CS[eph4_2009$ASALARIAD==3]=6
eph4_2009$CS[eph4_2009$ASALARIAD==4]=7
eph4_2009$CS[eph4_2009$ASALARIAD==5]=8
eph4_2009$CS[eph4_2009$AUTONOM==1]=9
eph4_2009$CS[eph4_2009$AUTONOM==2]=10
eph4_2009$CS[eph4_2009$AUTONOM==2 & is.na(eph4_2009$calificacion)]=NA
eph4_2009$CS[eph4_2009$AUTONOM==3]=11
eph4_2009$CS[eph4_2009$AUTONOM==3 & is.na(eph4_2009$calificacion)]=NA
eph4_2009$CS[eph4_2009$AUTONOM==4]=11
eph4_2009$CS[eph4_2009$AUTONOM==4 & is.na(eph4_2009$calificacion)]=NA
eph4_2009$CS[eph4_2009$SERV_DOM==1]=12
weighted.sd<-function(x, w) ( (sum(w*x*x)/sum(w)) - weighted.mean(x,w)^2 )^.5
eph4_2009<- eph4_2009 %>% mutate( IT= P47T*PONDII)
eph4_2009 <- eph4_2009 %>%
group_by(hogar_id) %>%
mutate(CS_total= CS[which(PARENTESCO==1)] )
eph4_2009<- eph4_2009 %>% mutate( IOP= ifelse( PARENTESCO==1, P21, NA ))
##### GUARDO BS
#write.table(eph4_2009, file = "G:/Mi unidad/INVESTIGACION/clases sociales/bases de datos/eph418_CSO.csv", sep = ",", col.names = TRUE, row.names = FALSE)
cuadro_final <- eph4_2009 %>% group_by(CS_total) %>%
summarise( N = sum(PONDERA, na.rm = TRUE),
N2 = sum(PONDIH, na.rm = TRUE),
mean=weighted.mean(IPCF,PONDIH),
mean2=weighted.mean(ITF,PONDIH),
mean3=weighted.mean(P47T,PONDII, na.rm = TRUE),
mean4=weighted.mean(IOP,PONDIIO, na.rm = TRUE),
sd=weighted.sd(IPCF,PONDIH),
n=n(),
sum_ing = sum(IT, na.rm = TRUE) )
cuadro_final <- cuadro_final %>% filter(!is.na(CS_total)) %>%
mutate( Part.= (N/sum(N, na.rm = TRUE))*100)
cuadro_final <- cuadro_final %>% filter(!is.na(CS_total)) %>%
mutate( Part.2= (N2/sum(N2, na.rm = TRUE))*100)
cuadro_final <- cuadro_final %>% filter(!is.na(CS_total)) %>%
mutate( Part_ing= (sum_ing/sum(sum_ing, na.rm = TRUE))*100)
cuadro_final <- cuadro_final %>%
mutate( CV_N=ifelse( N<100001 , "20" ,
ifelse( N>99999 & N<150000 , "19.8" ,
ifelse( N>149999 & N<200000 , "14.5" ,
ifelse( N>199999 & N<250000 , "11.6" ,
ifelse( N>249999 & N<300000 , "9.8" ,
ifelse( N>299999 & N<350000 , "8.5" ,
ifelse( N>349999 & N<400000 , "7.5" ,
ifelse( N>399999 & N<450000 , "6.8" ,
ifelse( N>449999 & N<500000 , "6.2" ,
ifelse( N>499999 & N<550000 , "5.7" ,
ifelse( N>549999 & N<600000 , "5.3" ,
ifelse( N>599999 & N<650000 , "5.0" ,
ifelse( N>649999 & N<700000 , "4.7" ,
ifelse( N>699999 & N<750000 , "4.4" ,
ifelse( N>749999 & N<800000 , "4.2" ,
ifelse( N>799999 & N<850000 , "4.0" ,
ifelse( N>849999 & N<900000 , "3.8" ,
ifelse( N>899999 & N<950000 , "3.6" ,
ifelse( N>949999 & N<1000000 , "3.5" ,
ifelse( N>999999 & N<1050000 , "3.4" ,
ifelse( N>1049999 & N<1100000 , "3.2" ,
ifelse( N>1099999 & N<1150000 , "3.1" ,
ifelse( N>1149999 & N<1200000 , "3.0" ,
ifelse( N>1199999 & N<1300000 , "2.9" ,
ifelse( N>1299999 & N<1400000 , "2.7" ,
ifelse( N>1399999 & N<1500000 , "2.6" ,
ifelse( N>1499999 & N<1600000 , "2.5" ,
ifelse( N>1599999 & N<1700000 , "2.3" ,
ifelse( N>1699999 & N<1800000 , "2.2" ,
ifelse( N>1799999 & N<1900000 , "2.1" ,
ifelse( N>1899999 & N<2100000 , "2.0" ,
ifelse( N>2199999 & N<2300000 , "1.9" ,
ifelse( N>2299999 & N<2500000 , "1.8" ,
ifelse( N>2499999 & N<2700000 , "1.7" ,
ifelse( N>2649999 & N<2900000 , "1.6" ,
ifelse( N>2900000, "1.5", NA
) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) )
##################### coef act ###################
read<- "https://infra.datos.gob.ar/catalog/sspm/dataset/25/distribution/25.2/download/indice-precios-implicitos-oferta-demanda-globales-valores-trimestrales-base-2004.csv"
DPBI<- read.csv(read, header = TRUE)
DPBI<- data.frame(DPBI[,c(1:2)])
coef_act<- DPBI[67,2]/DPBI[60,2]-1
cuadro_final$mean <- cuadro_final$mean*(1+coef_act)
cuadro_final$mean2 <- cuadro_final$mean2*(1+coef_act)
cuadro_final$mean3 <- cuadro_final$mean3*(1+coef_act)
cuadro_final$mean4 <- cuadro_final$mean4*(1+coef_act)
cuadro_final<- as.data.frame(cuadro_final)
Total<- c(14, sum(cuadro_final$N, na.rm = TRUE),sum(cuadro_final$N2, na.rm = TRUE), weighted.mean(cuadro_final$mean,cuadro_final$N2), weighted.mean(cuadro_final$mean2,cuadro_final$N2),weighted.mean(cuadro_final$mean3,cuadro_final$N2), weighted.mean(cuadro_final$mean4,cuadro_final$N2), weighted.mean(cuadro_final$sd,cuadro_final$N2) , sum(cuadro_final$n, na.rm = TRUE),sum(cuadro_final$sum_ing, na.rm = TRUE), sum(cuadro_final$Part., na.rm = TRUE), sum(cuadro_final$Part.2, na.rm = TRUE), sum(cuadro_final$Part_ing, na.rm = TRUE), "" )
cuadro_final[nrow(cuadro_final) + 1, ] <- Total
cuadro_final<- as.data.frame(apply(cuadro_final, MARGIN=2, FUN=as.numeric ))
cuadro_final$CS_total<-as.factor(cuadro_final$CS_total)
cuadro_final$CS_total=factor(cuadro_final$CS_total, labels=c("Owner or director of a Small or Medium-Sized enterprise",
"Owner of a big firm",
"Director/Manager of big firm",
"Chief/Supervision (Salaried)",
"Salaried Professional",
"Salaried Technician",
"Autonomous Professional",
"Salaried Operative" ,
"Salaried Low Qualification",
"Autonomous worker with means of production",
"Autonomous worker without means of production",
"Household Employee for Care and reproductive work", "Total"))
## pongo los formatos que quiero
cuadro_final$CV<- sprintf("%.2f%%", cuadro_final$CV )
cuadro_final$Part.<- sprintf("%.2f%%", cuadro_final$Part. )
cuadro_final$Part_ing <- sprintf("%.2f%%", cuadro_final$Part_ing )
cuadro_final$N <- format(cuadro_final$N, digits=0, decimal.mark=".", big.mark=",", scientific = FALSE )
cuadro_final$mean <- format(cuadro_final$mean, digits=0, decimal.mark=".", big.mark=",", scientific = FALSE )
cuadro_final$mean2 <- format(cuadro_final$mean2, digits=0, decimal.mark=".", big.mark=",", scientific = FALSE )
cuadro_final$mean3 <- format(cuadro_final$mean3, digits=0, decimal.mark=".", big.mark=",", scientific = FALSE )
cuadro_final$mean4 <- format(cuadro_final$mean4, digits=0, decimal.mark=".", big.mark=",", scientific = FALSE )
## ordeno cuadro final de salida
cuadro_CS419<- cuadro_final[, c( "CS_total", "N", "Part.", "CV_N" , "mean","mean2", "Part_ing", "n" ) ]
colnames(cuadro_CS419)<- c("CSO", "People", "% Part.", "Income percapita", "Income household", "% Part. Income", "Coefficient of Variation CSO", "sample" )
cuadro_CS419
```
### CSO 2017
```{r echo=FALSE, message=FALSE, warning=FALSE}
library(dplyr)
library(readxl)
library(xtable)
library(ggplot2)
library(scales)
library(eph)
eph4_2009 <- get_microdata(year = 2017,
trimester = 4,
type= "individual",
vars ="all" )
eph4_2009 <- as.data.frame(eph4_2009)
## Paso las variables a texto y corrijo
#eph4_2009$PP04D_COD<- as.character(eph4_2009$PP04D_COD)
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="1"]="00001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="1001"]="01001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="2001"]="02001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="3001"]="03001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="4001"]="04001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="5001"]="05001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="5002"]="05002"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="6001"]="06001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="7001"]="07001"
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99999"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99998"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99997"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99993"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99994"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99992"]=""
eph4_2009$PP04D_COD[eph4_2009$PP04D_COD=="99991"]=""
#eph4_2009$PP11D_COD<- as.character(eph4_2009$PP11D_COD)
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="1"]="00001"
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="1001"]="01001"
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="5002"]="05002"
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="7001"]="07001"
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99999"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99998"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99997"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99993"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99992"]=""
eph4_2009$PP11D_COD[eph4_2009$PP11D_COD=="99991"]=""
eph4_2009<-rename(eph4_2009, PARENTESCO=CH03, EDAD=CH06, COD_OCUPACION=PP04D_COD, NUM_EMP=PP04C, GENERO=CH04 ,
EQUIPO=PP05C_1 , LOCAL=PP05C_2, VEHICULO=PP05C_3, COD_OCUPACION2=PP11D_COD, NUM_EMP2=PP11C)
############ Armo ID de jefes de familia y un nuevo pondera e ITF ####
eph4_2009<-mutate(eph4_2009, hogar_id=paste(eph4_2009$CODUSU,eph4_2009$NRO_HOGAR, sep=""))
eph4_2009<- eph4_2009 %>%