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Apply OECD Equivalence Scale to a Variable

apply_oecd_equivalisation.Rd

This function adjusts a household-level variable (such as income or consumption) using either the standard or modified OECD equivalence scale. It accounts for household composition by assigning different weights to additional adults and children.

Usage

apply_oecd_equivalisation(data_list, var_name, modified = TRUE)

Arguments

data_list

A named list of data frames, from LIS or LWS microdata.

var_name

A string. The name of the variable to be equivalised.

modified

Logical. If TRUE (default), the modified OECD scale is used (0.5 for additional adults, 0.3 for children). If FALSE, the original OECD scale is applied (0.7 for additional adults, 0.5 for children).

Value

A list of data frames with the equivalised variable.

Details

The OECD equivalence scale adjusts household income or consumption to reflect differences in household needs. It requires:

  • nhhmem: total number of household members, (always loaded by default already)

  • nhhmem13: number of household members under 14 years old

The scale is computed as:

  • Standard: 1 + 0.7 × (additional adults) + 0.5 × (children under 14)

  • Modified: 1 + 0.5 × (additional adults) + 0.3 × (children under 14)

Examples

if (FALSE) { # \dontrun{
# Import data, ideally at the level of the variable of interest.
# The variable "nhhmem13" must be imported in advance in order to apply OECD-type equivalisation methods.
data_hhd_with_nhhmem13 <- lissyrtools::lissyuse("it", vars = c("dhi", "nhhmem13"), from = 2010)

# No equivalisation case
data_hhd  %>%
 purrr::map(~ .x %>% filter(!is.na(dhi))) %>%
 run_weighted_mean("dhi", "hpopwgt")  

# Default case: modified OECD scale equivalisation
data_hhd_with_nhhmem13  %>%
 purrr::map(~ .x %>% filter(!is.na(dhi))) %>%
 apply_oecd_equivalisation("dhi") %>% 
 run_weighted_mean("dhi", "hpopwgt")  

# Standard OECD scale equivalisation
data_hhd_with_nhhmem13  %>%
 purrr::map(~ .x %>% filter(!is.na(dhi))) %>%
 apply_oecd_equivalisation("dhi", modified = FALSE) %>% 
 run_weighted_mean("dhi", "hpopwgt") 
} # }