linqsr: Linearization of the Quintile Share Ratio

In vardpoor: Variance Estimation for Sample Surveys by the Ultimate Cluster Method

Description

Estimate the Quintile Share Ratio, which is defined as the ratio of the sum of equalized disposable income received by the top 20% to the sum of equalized disposable income received by the bottom 20%, and its linearization.

Usage

linqsr(
  Y,
  id = NULL,
  weight = NULL,
  sort = NULL,
  Dom = NULL,
  period = NULL,
  dataset = NULL,
  alpha = 20,
  var_name = "lin_qsr",
  checking = TRUE
)

Arguments

Y	Study variable (for example equalized disposable income). One dimensional object convertible to one-column data.table or variable name as character, column number.
id	Optional variable for unit ID codes. One dimensional object convertible to one-column data.table or variable name as character, column number.
weight	Optional weight variable. One dimensional object convertible to one-column data.table or variable name as character, column number.
sort	Optional variable to be used as tie-breaker for sorting. One dimensional object convertible to one-column data.table or variable name as character, column number.
Dom	Optional variables used to define population domains. If supplied, linearization of the income quantile share ratio is done for each domain. An object convertible to data.table or variable names as character vector, column numbers.
period	Optional variable for survey period. If supplied, linearization of the income quantile share ratio is done for each time period. Object convertible to data.table or variable names as character, column numbers.
dataset	Optional survey data object convertible to data.table.
alpha	a numeric value in range [0,100] for the order of the Quintile Share Ratio.
var_name	A character specifying the name of the linearized variable.
checking	Optional variable if this variable is TRUE, then function checks data preparation errors, otherwise not checked. This variable by default is TRUE.

Value

A list with two objects are returned by the function:

• value - a data.table containing the estimated Quintile Share Ratio by G. Osier and Eurostat papers.

• lin - a data.table containing the linearized variables of the Quintile Share Ratio by G. Osier paper.

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.
Guillaume Osier (2009). Variance estimation for complex indicators of poverty and inequality. Journal of the European Survey Research Association, Vol.3, No.3, pp. 167-195, ISSN 1864-3361, URL https://ojs.ub.uni-konstanz.de/srm/article/view/369.
Jean-Claude Deville (1999). Variance estimation for complex statistics and estimators: linearization and residual techniques. Survey Methodology, 25, 193-203, URL https://www150.statcan.gc.ca/n1/pub/12-001-x/1999002/article/4882-eng.pdf.

See Also

incPercentile, varpoord, vardcrospoor, vardchangespoor

Examples

library("data.table")
library("laeken")
data("eusilc")
dataset1 <- data.table(IDd = paste0("V", 1 : nrow(eusilc)), eusilc)

# Full population
dd <- linqsr(Y = "eqIncome", id = "IDd",
             weight = "rb050", Dom = NULL,
             dataset = dataset1, alpha = 20)
dd$value
 
## Not run: 
# By domains
dd <- linqsr(Y = "eqIncome", id = "IDd",
             weight = "rb050", Dom = "db040",
             dataset = dataset1, alpha = 20)
dd$value
## End(Not run)

vardpoor documentation built on Nov. 30, 2020, 5:08 p.m.