vardpoor (version 0.2.0.8.1)

linarpt: Linearization of the at-risk-of-poverty threshold

Description

Estimate the at-risk-of-poverty threshold and its linearization. The standard definition is to use 60% of the weighted median equivalized disposable income.

Usage

linarpt(inc, id = NULL, weight = NULL, sort = NULL,
        Dom = NULL, period=NULL, dataset = NULL, percentage = 60,
        order_quant=50, na.rm = FALSE, var_name="lin_arpt")

Arguments

inc

either a numeric vector, 1 column data.frame, matrix, data.table giving the equivalized disposable income, or (if dataset is not NULL) a character string, an integer or a logical vector (length is the same as 'dataset

id

optional; either 1 column data.frame, matrix, data.table giving the personal IDs, or (if dataset is not NULL) a character string, an integer or a logical vector (length is the same as 'dataset' column count) specifyin

weight

optional; either a numeric vector, 1 column data.frame, matrix, data.table giving the personal sample weights, or (if dataset is not NULL) a character string, an integer or a logical vector (length is the same as 'dat

sort

optional; either a numeric vector, 1 column data.frame, matrix, data table giving the personal IDs to be used as tie-breakers for sorting, or (if dataset is not NULL) a character string, an integer or a logical vector

Dom

optional; either a data.frame, matrix, data.table with column names giving different domains, or (if dataset is not NULL) character strings, integers or a logical vectors (length is the same as 'dataset' column count)

period

optional; either a data.frame, matrix, data.table with column names giving different periods, or (if dataset is not NULL) character strings, integers or a logical vectors (length is the same as 'dataset' column coun

dataset

an optional; name of the individual dataset data.frame.

percentage

a numeric value in $[0,100]$ giving the percentage of the income quantile to be used for the at-risk-of-poverty threshold (see linarpt).

order_quant

a numeric value in $[0,100]$ giving the order of the income quintale (in percentage) to be used for the at-risk-of-poverty threshold (see linarpt).

na.rm

a logical indicating whether missing values should be removed.

var_name

a character string specifying the name of the linearized variable.

Value

• The function returns three values:
• quantile
  a data.frame containing the estimate(s) the value(s) of the quintale by domain or (if Dom is NULL)) totals.
• value
  a data.frame containing the estimate(s) the at-risk-of-poverty threshold by domain or (if Dom is NULL)) totals.
• lin
  a data.frame containing the values of linearized variables of the poverty threshold (in precentage) by domains or (if Dom is NULL) totals.

Details

The implementation strictly follows the Eurostat definition.

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. Deville, J. C. (1999). Variance estimation for complex statistics and estimators: linearization and residual techniques. Survey Methodology, 25, 193-203, URL http://www5.statcan.gc.ca/bsolc/olc-cel/olc-cel?lang=eng&catno=12-001-X19990024882.

See Also

linarpr, incPercentile, varpoord, var_srs

Examples

data(eusilc)
dati=data.frame(1:nrow(eusilc),eusilc)
colnames(dati)[1]<-"IDd"
d<-linarpt("eqIncome", id="IDd", weight = "rb050", Dom = NULL,
            dataset = dati, percentage = 60, order_quant=50, na.rm = FALSE)
dd<-linarpt("eqIncome", id="IDd", weight = "rb050", Dom = "db040",
             dataset = dati, percentage = 60, order_quant=50, na.rm = FALSE)