R/employment.R
In calcita/ech: Downloading and Processing Microdata from ECH-INE (Uruguay)
Defines functions
branch_ciiu
employment_restrictions
underemployment
employment
Documented in
branch_ciiu
employment
employment_restrictions
underemployment
#' This function allows you to calculate the variables: PEA, PET, PO, PD
#' @family employment
#' @param data data.frame with microdata
#' @param pobpcoac Variable name of definition of population by activity status. Default: "pobpcoac"
#' @keywords employment
#' @export
#' @importFrom dplyr mutate
#' @importFrom rlang .data
#' @details
#' Disclaimer: This script is not an official INE product.
#' Aviso: El script no es un producto oficial de INE.
#' @return data.frame, tbl and tbl_df object
#' @examples
#' \donttest{
#' toy_ech_2018 <- employment(data = ech::toy_ech_2018, pobpcoac = "pobpcoac")
#' }
employment <- function(data = ech::toy_ech_2018,
pobpcoac = "pobpcoac") {
# checks ---
assertthat::assert_that(is.data.frame(data), msg = glue::glue("Sorry... :( \n is not a data.frame"))
assertthat::assert_that(pobpcoac %in% names(data), msg = glue::glue("Sorry... :( \n {popbcoac} is not in data"))
# variables ---
data <- data %>% dplyr::mutate(pea = ifelse(pobpcoac %in% 2:5, 1, 0),
pet = ifelse(pobpcoac != 1, 1, 0),
po = ifelse(pobpcoac == 2, 1, 0),
pd = ifelse(pobpcoac %in% 3:5, 1, 0),
pea = haven::labelled(pea, labels = c("Si" = 1, "No" = 0),
label = "Poblacion economicamente activa"),
pet = haven::labelled(pet, labels = c("Si" = 1, "No" = 0),
label = "Poblacion en edad de trabajar"),
po = haven::labelled(po, labels = c("Si" = 1, "No" = 0),
label = "Poblacion ocupada"),
pd = haven::labelled(pd, labels = c("Si" = 1, "No" = 0),
label = "Poblacion desocupada")
)
message("Variables have been created: \n \t pea (Poblacion economicamente activa);
pet (Poblacion en edad de trabajar);
po (Poblacion ocupada) &
pd (Poblacion desocupada)")
return(data)
}
#' This function allows you to identify underemployed people
#' @family employment
#' @param data data.frame
#' @param pobpcoac Variable name of definition of population by activity status. Default: "pobpcoac"
#' @param f85 Variable name of number of hours worked in the main job
#' @param f98 Variable name of Number of hours worked at the secondary job
#' @param f101 Variable name of reasons why you want another job
#' @param f102 Variable name of want to work more hours
#' @param f103 Variable name of are available to work more hours at this time
#' @param f104 Variable name of reasons why you dont work more hours
#'
#' @importFrom dplyr mutate case_when
#' @importFrom haven labelled
#' @return data.frame
#' @export
#' @details
#' Disclaimer: This script is not an official INE product.
#' Aviso: El script no es un producto oficial de INE.
#'
#' @examples
#' toy_ech_2018 <- underemployment(data = ech::toy_ech_2018)
underemployment <- function(data = ech::toy_ech_2018,
pobpcoac = "pobpcoac",
f85 = "f85",
f98 = "f98",
f101 = "f101",
f102 = "f102",
f103 = "f103",
f104 = "f104"){
# checks ---
assertthat::assert_that(is.data.frame(data), msg = glue::glue("Sorry... :( \n is not a data.frame"))
assertthat::assert_that(pobpcoac %in% names(data), msg = glue::glue("Sorry... :( \n {popbcoac} is not in data"))
assertthat::assert_that(f85 %in% names(data), msg = glue::glue("Sorry... :( \n {f85} is not in data"))
assertthat::assert_that(f98 %in% names(data), msg = glue::glue("Sorry... :( \n {f98} is not in data"))
assertthat::assert_that(f101 %in% names(data), msg = glue::glue("Sorry... :( \n {f101} is not in data"))
assertthat::assert_that(f102 %in% names(data), msg = glue::glue("Sorry... :( \n {f102} is not in data"))
assertthat::assert_that(f103 %in% names(data), msg = glue::glue("Sorry... :( \n {f103} is not in data"))
assertthat::assert_that(f104 %in% names(data), msg = glue::glue("Sorry... :( \n {f104} is not in data"))
data <- data %>% dplyr::mutate(underemployment = dplyr::case_when(pobpcoac == 2 & (f85 + f98 < 40) & (f101 == 1 | f102 == 1) & (f103 == 1) & (f104 == 5) ~ 1,
TRUE ~ 0),
underemployment = haven::labelled(underemployment, labels = c("Si" = 1, "No" = 0), label = "Poblacion subempleada")
)
message("A variable has been created: \n \t underemployment (Poblacion subempleada)")
return(data)
}
#' This function allows you to identify workers with employment restrictions
#' @family employment
#' @param data data.frame
#' @param f82 Variable name of contribution to the pension fund
#' @param underemployment Variable name of underemployment
#' @return data.frame
#' @export
#' @details
#' Disclaimer: This script is not an official INE product.
#' Aviso: El script no es un producto oficial de INE.
#' @examples
#' toy_ech_2018 <- underemployment(data = ech::toy_ech_2018)
#' toy_ech_2018 <- employment_restrictions(data = toy_ech_2018)
employment_restrictions <- function(data = ech::toy_ech_2018,
f82 = "f82",
underemployment = "underemployment"){
# checks ---
assertthat::assert_that(is.data.frame(data), msg = glue::glue("Sorry... :( \n is not a data.frame"))
assertthat::assert_that(f82 %in% names(data), msg = glue::glue("Sorry... :( \n {f82} is not in data"))
assertthat::assert_that(underemployment %in% names(data), msg = glue::glue("Sorry... :( \n {underemployment} is not in data"))
data <- data %>% dplyr::mutate(employment_restrictions = dplyr::case_when(
f82 == 1 & underemployment == 0 ~ 1,
f82 == 2 & underemployment == 0 ~ 2,
f82 == 1 & underemployment == 1 ~ 3,
f82 == 2 & underemployment == 1 ~ 4),
employment_restrictions = haven::labelled(employment_restrictions,
labels = c("Sin restricciones" = 1, "Restriccion por no aporte" = 2, "Restriccion por subempleo" = 3, "Restriccion por subempleo y no aporte " = 4),
label = "Restricciones al empleo"))
message("A variable has been created: \n \t employment_restrictions (restricciones al empleo)")
return(data)
}
#' This function allows you to identify activity branches
#' @family employment
#' @param data data.frame
#' @param f72_2 Variable name of ciiu code rev.4
#' @param group logical to define 12 or 18 categories, if FALSE code 18. Default: TRUE
#' @param disaggregated logical to define disaggregated branches or not. Default: FALSE
#' @return data.frame
#' @export
#' @details
#' Disclaimer: This script is not an official INE product.
#' Aviso: El script no es un producto oficial de INE.
#' @examples
#' \donttest{
#' toy_ech_2018 <- branch_ciiu(data = ech::toy_ech_2018)
#' }
branch_ciiu <- function(data = ech::toy_ech_2018,
f72_2 = "f72_2",
group = TRUE,
disaggregated = FALSE){
# checks ---
assertthat::assert_that(is.data.frame(data), msg = glue::glue("Sorry... :( \n is not a data.frame"))
assertthat::assert_that(f72_2 %in% names(data), msg = glue::glue("Sorry... :( \n {f72_2} is not in data"))
if(is.character(data$f72_2)) data$f72_2 <- as.numeric(data$f72_2)
data <- data %>%
dplyr::mutate(branch_ciiu = dplyr::case_when(f72_2 < 1000 ~ 1, #faltan evaluar los NA
f72_2 < 4000 ~ 2,
f72_2 < 4500 ~ 3,
f72_2 < 4900 ~ 4,
f72_2 < 5500 ~ 5,
f72_2 < 5800 ~ 6,
f72_2 < 6400 ~ 7,
f72_2 < 6800 ~ 8,
f72_2 < 6900 ~ 9,
f72_2 < 7500 ~ 10,
f72_2 < 8400 ~ 11,
f72_2 < 8500 ~ 12,
f72_2 < 8600 ~ 13,
f72_2 < 9000 ~ 14,
f72_2 < 9400 ~ 15,
f72_2 < 9700 ~ 16,
f72_2 < 9900 ~ 17,
TRUE ~ 18))
if (group == TRUE){
data <- data %>%
dplyr::mutate(branch_group_ciiu = dplyr::case_when( #faltan evaluar los NA
branch_ciiu == 1 ~ "Agropecuaria, pesca, caza y explotacion de minas o conteras",
branch_ciiu == 2 ~ "Industria manufacturera, Suministro de electricidad, gas y agua",
branch_ciiu == 3 ~ "Construccion",
branch_ciiu == 4 ~ "Comercio por menor y por mayor; Alojamiento y servicio de comida",
branch_ciiu == 5 ~ "Transporte y almacenamiento",
branch_ciiu == 6 ~ "Comercio por menor y por mayor; Alojamiento y servicio de comida",
branch_ciiu == 7 ~ "Informatica y Comunicacion",
branch_ciiu == 8 ~ "Actividades financieras y de seguros",
branch_ciiu == 9 ~ "Actividades inmobiliarias",
branch_ciiu == 10 ~ "Actividades profesionales, cientificas y tecnicas",
branch_ciiu == 11 ~ "Actividades administrativas y servicio de apoyo",
branch_ciiu == 12 ~ "Administracion Publica; Defensa y Actividades de organizaciones y organos extraterritoriales",
branch_ciiu == 18 ~ "Administracion Publica; Defensa y Actividades de organizaciones y organos extraterritoriales",
branch_ciiu == 13 ~ "Ensenanza",
branch_ciiu == 14 ~ "Servicios sociales y Salud",
branch_ciiu == 15 ~ "Otras actividades de servicio; Arte, entretenimiento y recreacion",
branch_ciiu == 16 ~ "Otras actividades de servicio; Arte, entretenimiento y recreacion",
branch_ciiu == 17 ~ "Actividades de los hogares como empleadores",
TRUE ~ ""))
message("A variable has been created: \n \t branch_ciiu (Rama de actividad CIIU)
branch_group_ciiu (Rama de actividad CIIU agrupadas)")
}
if (disaggregated == TRUE){
data <- data %>%
dplyr::mutate(branch_ciiu_disaggregated = dplyr::case_when( #faltan evaluar los NA
f72_2 < 301 ~ "Agricultura, ganaderia, caza y silvicultura",
f72_2 < 500 ~ "Pesca",
f72_2 < 1000 ~ "Explotacion de minas y canteras",
f72_2 < 3500 ~ "Industrias manufactureras",
f72_2 < 4100 ~ "Suministro de electricidad, gas y agua",
f72_2 < 4500 ~ "Construccion",
f72_2 < 4900 ~ "Comercio",
f72_2 < 5800 ~ "Hoteles y restaurantes",
f72_2 < 5500 | (f72_2 >= 5800 & f72_2 <= 6400) ~ "Transporte, almacenamiento y comunicaciones",
f72_2 < 6800 ~ "Intermediacion financiera",
f72_2 < 8400 ~ "Actividades inmobiliarias, empresariales y de alquiler",
f72_2 < 8500 | f72_2 == 9900 ~ "Administracion publica y defensa, planes de seguridad social",
f72_2 < 8600 ~ "Ensenanza",
f72_2 < 9000 ~ "Servicios sociales y de salud",
f72_2 < 9700 ~ "Otros servicios sociales",
f72_2 < 9900 ~ "Hogares privados con servicio domestico",
TRUE ~ ""))
message("A variable has been created: \n \t branch_ciiu (Rama de actividad CIIU)
branch_ciiu_disaggregated (Rama de actividad CIIU desagregada)")
}
return(data)
}
calcita/ech documentation built on March 2, 2024, 7:54 a.m.
R Package Documentation
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Defines functions branch_ciiu employment_restrictions underemployment employment
Documented in branch_ciiu employment employment_restrictions underemployment
#' This function allows you to calculate the variables: PEA, PET, PO, PD
#' @family employment
#' @param data data.frame with microdata
#' @param pobpcoac Variable name of definition of population by activity status. Default: "pobpcoac"
#' @keywords employment
#' @export
#' @importFrom dplyr mutate
#' @importFrom rlang .data
#' @details
#' Disclaimer: This script is not an official INE product.
#' Aviso: El script no es un producto oficial de INE.
#' @return data.frame, tbl and tbl_df object
#' @examples
#' \donttest{
#' toy_ech_2018 <- employment(data = ech::toy_ech_2018, pobpcoac = "pobpcoac")
#' }
employment <- function(data = ech::toy_ech_2018,
pobpcoac = "pobpcoac") {
# checks ---
assertthat::assert_that(is.data.frame(data), msg = glue::glue("Sorry... :( \n is not a data.frame"))
assertthat::assert_that(pobpcoac %in% names(data), msg = glue::glue("Sorry... :( \n {popbcoac} is not in data"))
# variables ---
data <- data %>% dplyr::mutate(pea = ifelse(pobpcoac %in% 2:5, 1, 0),
pet = ifelse(pobpcoac != 1, 1, 0),
po = ifelse(pobpcoac == 2, 1, 0),
pd = ifelse(pobpcoac %in% 3:5, 1, 0),
pea = haven::labelled(pea, labels = c("Si" = 1, "No" = 0),
label = "Poblacion economicamente activa"),
pet = haven::labelled(pet, labels = c("Si" = 1, "No" = 0),
label = "Poblacion en edad de trabajar"),
po = haven::labelled(po, labels = c("Si" = 1, "No" = 0),
label = "Poblacion ocupada"),
pd = haven::labelled(pd, labels = c("Si" = 1, "No" = 0),
label = "Poblacion desocupada")
)
message("Variables have been created: \n \t pea (Poblacion economicamente activa);
pet (Poblacion en edad de trabajar);
po (Poblacion ocupada) &
pd (Poblacion desocupada)")
return(data)
}
#' This function allows you to identify underemployed people
#' @family employment
#' @param data data.frame
#' @param pobpcoac Variable name of definition of population by activity status. Default: "pobpcoac"
#' @param f85 Variable name of number of hours worked in the main job
#' @param f98 Variable name of Number of hours worked at the secondary job
#' @param f101 Variable name of reasons why you want another job
#' @param f102 Variable name of want to work more hours
#' @param f103 Variable name of are available to work more hours at this time
#' @param f104 Variable name of reasons why you dont work more hours
#'
#' @importFrom dplyr mutate case_when
#' @importFrom haven labelled
#' @return data.frame
#' @export
#' @details
#' Disclaimer: This script is not an official INE product.
#' Aviso: El script no es un producto oficial de INE.
#'
#' @examples
#' toy_ech_2018 <- underemployment(data = ech::toy_ech_2018)
underemployment <- function(data = ech::toy_ech_2018,
pobpcoac = "pobpcoac",
f85 = "f85",
f98 = "f98",
f101 = "f101",
f102 = "f102",
f103 = "f103",
f104 = "f104"){
# checks ---
assertthat::assert_that(is.data.frame(data), msg = glue::glue("Sorry... :( \n is not a data.frame"))
assertthat::assert_that(pobpcoac %in% names(data), msg = glue::glue("Sorry... :( \n {popbcoac} is not in data"))
assertthat::assert_that(f85 %in% names(data), msg = glue::glue("Sorry... :( \n {f85} is not in data"))
assertthat::assert_that(f98 %in% names(data), msg = glue::glue("Sorry... :( \n {f98} is not in data"))
assertthat::assert_that(f101 %in% names(data), msg = glue::glue("Sorry... :( \n {f101} is not in data"))
assertthat::assert_that(f102 %in% names(data), msg = glue::glue("Sorry... :( \n {f102} is not in data"))
assertthat::assert_that(f103 %in% names(data), msg = glue::glue("Sorry... :( \n {f103} is not in data"))
assertthat::assert_that(f104 %in% names(data), msg = glue::glue("Sorry... :( \n {f104} is not in data"))
data <- data %>% dplyr::mutate(underemployment = dplyr::case_when(pobpcoac == 2 & (f85 + f98 < 40) & (f101 == 1 | f102 == 1) & (f103 == 1) & (f104 == 5) ~ 1,
TRUE ~ 0),
underemployment = haven::labelled(underemployment, labels = c("Si" = 1, "No" = 0), label = "Poblacion subempleada")
)
message("A variable has been created: \n \t underemployment (Poblacion subempleada)")
return(data)
}
#' This function allows you to identify workers with employment restrictions
#' @family employment
#' @param data data.frame
#' @param f82 Variable name of contribution to the pension fund
#' @param underemployment Variable name of underemployment
#' @return data.frame
#' @export
#' @details
#' Disclaimer: This script is not an official INE product.
#' Aviso: El script no es un producto oficial de INE.
#' @examples
#' toy_ech_2018 <- underemployment(data = ech::toy_ech_2018)
#' toy_ech_2018 <- employment_restrictions(data = toy_ech_2018)
employment_restrictions <- function(data = ech::toy_ech_2018,
f82 = "f82",
underemployment = "underemployment"){
# checks ---
assertthat::assert_that(is.data.frame(data), msg = glue::glue("Sorry... :( \n is not a data.frame"))
assertthat::assert_that(f82 %in% names(data), msg = glue::glue("Sorry... :( \n {f82} is not in data"))
assertthat::assert_that(underemployment %in% names(data), msg = glue::glue("Sorry... :( \n {underemployment} is not in data"))
data <- data %>% dplyr::mutate(employment_restrictions = dplyr::case_when(
f82 == 1 & underemployment == 0 ~ 1,
f82 == 2 & underemployment == 0 ~ 2,
f82 == 1 & underemployment == 1 ~ 3,
f82 == 2 & underemployment == 1 ~ 4),
employment_restrictions = haven::labelled(employment_restrictions,
labels = c("Sin restricciones" = 1, "Restriccion por no aporte" = 2, "Restriccion por subempleo" = 3, "Restriccion por subempleo y no aporte " = 4),
label = "Restricciones al empleo"))
message("A variable has been created: \n \t employment_restrictions (restricciones al empleo)")
return(data)
}
#' This function allows you to identify activity branches
#' @family employment
#' @param data data.frame
#' @param f72_2 Variable name of ciiu code rev.4
#' @param group logical to define 12 or 18 categories, if FALSE code 18. Default: TRUE
#' @param disaggregated logical to define disaggregated branches or not. Default: FALSE
#' @return data.frame
#' @export
#' @details
#' Disclaimer: This script is not an official INE product.
#' Aviso: El script no es un producto oficial de INE.
#' @examples
#' \donttest{
#' toy_ech_2018 <- branch_ciiu(data = ech::toy_ech_2018)
#' }
branch_ciiu <- function(data = ech::toy_ech_2018,
f72_2 = "f72_2",
group = TRUE,
disaggregated = FALSE){
# checks ---
assertthat::assert_that(is.data.frame(data), msg = glue::glue("Sorry... :( \n is not a data.frame"))
assertthat::assert_that(f72_2 %in% names(data), msg = glue::glue("Sorry... :( \n {f72_2} is not in data"))
if(is.character(data$f72_2)) data$f72_2 <- as.numeric(data$f72_2)
data <- data %>%
dplyr::mutate(branch_ciiu = dplyr::case_when(f72_2 < 1000 ~ 1, #faltan evaluar los NA
f72_2 < 4000 ~ 2,
f72_2 < 4500 ~ 3,
f72_2 < 4900 ~ 4,
f72_2 < 5500 ~ 5,
f72_2 < 5800 ~ 6,
f72_2 < 6400 ~ 7,
f72_2 < 6800 ~ 8,
f72_2 < 6900 ~ 9,
f72_2 < 7500 ~ 10,
f72_2 < 8400 ~ 11,
f72_2 < 8500 ~ 12,
f72_2 < 8600 ~ 13,
f72_2 < 9000 ~ 14,
f72_2 < 9400 ~ 15,
f72_2 < 9700 ~ 16,
f72_2 < 9900 ~ 17,
TRUE ~ 18))
if (group == TRUE){
data <- data %>%
dplyr::mutate(branch_group_ciiu = dplyr::case_when( #faltan evaluar los NA
branch_ciiu == 1 ~ "Agropecuaria, pesca, caza y explotacion de minas o conteras",
branch_ciiu == 2 ~ "Industria manufacturera, Suministro de electricidad, gas y agua",
branch_ciiu == 3 ~ "Construccion",
branch_ciiu == 4 ~ "Comercio por menor y por mayor; Alojamiento y servicio de comida",
branch_ciiu == 5 ~ "Transporte y almacenamiento",
branch_ciiu == 6 ~ "Comercio por menor y por mayor; Alojamiento y servicio de comida",
branch_ciiu == 7 ~ "Informatica y Comunicacion",
branch_ciiu == 8 ~ "Actividades financieras y de seguros",
branch_ciiu == 9 ~ "Actividades inmobiliarias",
branch_ciiu == 10 ~ "Actividades profesionales, cientificas y tecnicas",
branch_ciiu == 11 ~ "Actividades administrativas y servicio de apoyo",
branch_ciiu == 12 ~ "Administracion Publica; Defensa y Actividades de organizaciones y organos extraterritoriales",
branch_ciiu == 18 ~ "Administracion Publica; Defensa y Actividades de organizaciones y organos extraterritoriales",
branch_ciiu == 13 ~ "Ensenanza",
branch_ciiu == 14 ~ "Servicios sociales y Salud",
branch_ciiu == 15 ~ "Otras actividades de servicio; Arte, entretenimiento y recreacion",
branch_ciiu == 16 ~ "Otras actividades de servicio; Arte, entretenimiento y recreacion",
branch_ciiu == 17 ~ "Actividades de los hogares como empleadores",
TRUE ~ ""))
message("A variable has been created: \n \t branch_ciiu (Rama de actividad CIIU)
branch_group_ciiu (Rama de actividad CIIU agrupadas)")
}
if (disaggregated == TRUE){
data <- data %>%
dplyr::mutate(branch_ciiu_disaggregated = dplyr::case_when( #faltan evaluar los NA
f72_2 < 301 ~ "Agricultura, ganaderia, caza y silvicultura",
f72_2 < 500 ~ "Pesca",
f72_2 < 1000 ~ "Explotacion de minas y canteras",
f72_2 < 3500 ~ "Industrias manufactureras",
f72_2 < 4100 ~ "Suministro de electricidad, gas y agua",
f72_2 < 4500 ~ "Construccion",
f72_2 < 4900 ~ "Comercio",
f72_2 < 5800 ~ "Hoteles y restaurantes",
f72_2 < 5500 | (f72_2 >= 5800 & f72_2 <= 6400) ~ "Transporte, almacenamiento y comunicaciones",
f72_2 < 6800 ~ "Intermediacion financiera",
f72_2 < 8400 ~ "Actividades inmobiliarias, empresariales y de alquiler",
f72_2 < 8500 | f72_2 == 9900 ~ "Administracion publica y defensa, planes de seguridad social",
f72_2 < 8600 ~ "Ensenanza",
f72_2 < 9000 ~ "Servicios sociales y de salud",
f72_2 < 9700 ~ "Otros servicios sociales",
f72_2 < 9900 ~ "Hogares privados con servicio domestico",
TRUE ~ ""))
message("A variable has been created: \n \t branch_ciiu (Rama de actividad CIIU)
branch_ciiu_disaggregated (Rama de actividad CIIU desagregada)")
}
return(data)
}
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