laeken (version 0.3.2)

gpg: Gender pay (wage) gap.

Description

Estimate the gender pay (wage) gap.

Usage

gpg(inc, gender = NULL, method = c("mean", "median"), 
    weights = NULL, sort = NULL, years = NULL, breakdown = NULL, 
    design = NULL, data = NULL, var = NULL, alpha = 0.05, 
    na.rm = FALSE, ...)

Arguments

inc

either a numeric vector giving the equivalized disposable income, or (if data is not NULL) a character string, an integer or a logical vector specifying the corresponding column of data.

gender

either a factor giving the gender, or (if data is not NULL) a character string, an integer or a logical vector specifying the corresponding column of data.

method

a character string specifying the method to be used. Possible values are "mean" for the mean, and "median" for the median. If weights are provided, the weighted mean or weighted median is estimated.

weights

optional; either a numeric vector giving the personal sample weights, or (if data is not NULL) a character string, an integer or a logical vector specifying the corresponding column of data.

sort

optional; either a numeric vector giving the personal IDs to be used as tie-breakers for sorting, or (if data is not NULL) a character string, an integer or a logical vector specifying the corresponding column of <

years

optional; either a numeric vector giving the different years of the survey, or (if data is not NULL) a character string, an integer or a logical vector specifying the corresponding column of data. If

breakdown

optional; either a numeric vector giving different strata, or (if data is not NULL) a character string, an integer or a logical vector specifying the corresponding column of data. If supplied, the val

design

optional and only used if var is not NULL; either an integer vector or factor giving different strata for stratified sampling designs, or (if data is not NULL) a character string, an integ

data

an optional data.frame.

var

a character string specifying the type of variance estimation to be used, or NULL to omit variance estimation. See variance for possible values.

alpha

numeric; if var is not NULL, this gives the significance level to be used for computing the confidence interval (i.e., the confidence level is $1 -$alpha).

na.rm

a logical indicating whether missing values should be removed.

...

if var is not NULL, additional arguments to be passed to variance.

Value

• A list of class "gpg" (which inherits from the class "indicator") with the following components:
• value
  a numeric vector containing the overall value(s).
• valueByStratum
  a data.frame containing the values by stratum, or NULL.
• varMethod
  a character string specifying the type of variance estimation used, or NULL if variance estimation was omitted.
• var
  a numeric vector containing the variance estimate(s), or NULL.
• varByStratum
  a data.frame containing the variance estimates by stratum, or NULL.
• ci
  a numeric vector or matrix containing the lower and upper endpoints of the confidence interval(s), or NULL.
• ciByStratum
  a data.frame containing the lower and upper endpoints of the confidence intervals by stratum, or NULL.
• alpha
  a numeric value giving the significance level used for computing the confidence interv al(s) (i.e., the confidence level is $1 -$alpha), or NULL.
• years
  a numeric vector containing the different years of the survey.
• strata
  a character vector containing the different strata of the breakdown.

Details

The implementation strictly follows the Eurostat definition (with default method "mean" and alternative method "median"). If weights are provided, the weighted mean or weighted median is estimated.

References

Working group on Statistics on Income and Living Conditions (2004) Common cross-sectional EU indicators based on EU-SILC; the gender pay gap. EU-SILC 131-rev/04, Eurostat.

See Also

variance, qsr, gini

Examples

data(eusilc)
### clearly, children and elder people may not work in Austria:
eusilc <- eusilc[eusilc$age > 17 & eusilc$age < 66, ]
### full time workers:
eusilc <- eusilc[eusilc$pl030 == 1, ]
### employees's cash income:
### py010n
eusilc <- eusilc[!is.na(eusilc$py010n), ]
### for estimation of the GPG, use hourly rates of people 
### who earn money and NOT just yearly income as done in 
### the following examples!

median_no_breakdown <- gpg("py010n", "rb090", method = "median", 
    weights = "rb050", data = eusilc)
mean_no_breakdown <- gpg("py010n", "rb090", method = "mean", 
    weights = "rb050", data = eusilc)

variance("py010n", gender = "rb090", method = "median", 
    weights = "rb050", design = "db040", data = eusilc, 
    indicator = median_no_breakdown, bootType = "naive", 
    seed = 123)

variance("py010n", gender = "rb090", method = "mean", 
    weights = "rb050", design = "db040", data = eusilc, 
    indicator = mean_no_breakdown, bootType = "naive", 
    seed = 123)


median_breakdown_area <- gpg("py010n", "rb090", 
    method = "median", breakdown = "db040", 
    weights = "rb050", data = eusilc)

variance("py010n", gender = "rb090", method = "median", 
    breakdown = "db040", weights = "rb050", design = "db040", 
    data = eusilc, indicator = median_breakdown_area, 
    bootType = "naive", seed = 123)


mean_breakdown_area <- gpg("py010n", "rb090", method = "mean", 
    breakdown = "db040", weights = "rb050", data = eusilc)

variance("py010n", gender = "rb090", method = "mean", 
    breakdown = "db040", weights = "rb050", design = "db040", 
    data = eusilc, indicator = mean_breakdown_area, 
    bootType = "naive", seed = 123)