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convey (version 0.2.5)

svyrich: Richness measures (EXPERIMENTAL)

Description

Estimate Peichl, Schaefer and Scheicher (2010) richness measures.

Usage

svyrich(formula, design, ...)

# S3 method for survey.design svyrich( formula, design, type_measure, g, type_thresh = "abs", abs_thresh = NULL, times = 1, quantiles = 0.5, na.rm = FALSE, thresh = FALSE, ... )

# S3 method for svyrep.design svyrich( formula, design, type_measure, g, type_thresh = "abs", abs_thresh = NULL, times = 1, quantiles = 0.5, na.rm = FALSE, thresh = FALSE, ... )

# S3 method for DBIsvydesign svyrich(formula, design, ...)

Value

Object of class "cvystat", which are vectors with a "var" attribute giving the variance and a "statistic" attribute giving the name of the statistic.

Arguments

formula

a formula specifying the income variable

design

a design object of class survey.design or class svyrep.design from the survey library.

...

passed to svyarpt

type_measure

A string "Cha", "FGTT1" or "FGTT2" defining the richness measure.

g

Richness preference parameter.

type_thresh

type of richness threshold. If "abs" the threshold is fixed and given the value of abs_thresh; if "relq" it is given by times times the quantile; if "relm" it is times times the mean.

abs_thresh

richness threshold value if type_thresh is "abs"

times

the multiple of the quantile or mean used in the richness threshold definition

quantiles

the quantile used used in the richness threshold definition

na.rm

Should cases with missing values be dropped?

thresh

return the richness threshold value

Author

Guilherme Jacob, Djalma Pessoa and Anthony Damico

Details

you must run the convey_prep function on your survey design object immediately after creating it with the svydesign or svrepdesign function.

References

Michal Brzezinski (2014). Statistical Inference for Richness Measures. Applied Economics, Vol. 46, No. 14, pp. 1599-1608, <doi:10.1080/00036846.2014.880106>

Andreas Peichl, Thilo Schaefer, and Christoph Scheicher (2010). Measuring richness and poverty: A micro data application to Europe and Germany. Review of Income and Wealth, Vol. 56, No.3, pp. 597-619.

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.

See Also

svyfgt

Examples

Run this code
library(survey)
library(laeken)
data(eusilc) ; names( eusilc ) <- tolower( names( eusilc ) )

# linearized design

des_eusilc <- svydesign( ids = ~rb030 , strata = ~db040 ,  weights = ~rb050 , data = eusilc )
des_eusilc <- convey_prep( des_eusilc )

# replicate-weighted design
des_eusilc_rep <- as.svrepdesign( des_eusilc , type = "bootstrap" )
des_eusilc_rep <- convey_prep( des_eusilc_rep )

# concave FGT-like richness measure
# headcount ratio, richness threshold fixed
svyrich(~eqincome, des_eusilc, type_measure = "FGTT1" , g=0,  abs_thresh=30000)
# richness gap index, richness threshold fixed
svyrich(~eqincome, des_eusilc, type_measure = "FGTT1" , g=1,  abs_thresh=30000)
# headcount ratio, richness threshold equal to the median
svyrich(~eqincome, des_eusilc, type_measure = "FGTT1" , g=0, type_thresh= "relq" )
# richness gap index, richness threshold equal to the median
svyrich(~eqincome, des_eusilc, type_measure = "FGTT1" , g=1, type_thresh= "relq" )
# headcount ratio, richness threshold equal to the mean
svyrich(~eqincome, des_eusilc, type_measure = "FGTT1" , g=0, type_thresh= "relm" )
# richness gap index, richness threshold equal to the mean
svyrich(~eqincome, des_eusilc, type_measure = "FGTT1" , g=1, type_thresh= "relm" )

#  using svrep.design:
# headcount ratio, richness threshold fixed
svyrich(~eqincome, des_eusilc_rep, type_measure = "FGTT1" , g=0, abs_thresh=30000 )
# richness gap index, richness threshold fixed
svyrich(~eqincome, des_eusilc_rep, type_measure = "FGTT1" , g=1, abs_thresh=30000 )
# headcount ratio, richness threshold equal to the median
svyrich(~eqincome, des_eusilc_rep, type_measure = "FGTT1" , g=0, type_thresh= "relq" )
# richness gap index, richness threshold equal to the median
svyrich(~eqincome, des_eusilc_rep, type_measure = "FGTT1" , g=1, type_thresh= "relq" )
# headcount ratio, richness threshold equal to the mean
svyrich(~eqincome, des_eusilc_rep, type_measure = "FGTT1" , g=0, type_thresh= "relm" )
# richness gap index, richness threshold equal to the mean
svyrich(~eqincome, des_eusilc_rep, type_measure = "FGTT1" , g=1, type_thresh= "relm" )

if (FALSE) {

# database-backed design
library(RSQLite)
library(DBI)
dbfile <- tempfile()
conn <- dbConnect( RSQLite::SQLite() , dbfile )
dbWriteTable( conn , 'eusilc' , eusilc )

dbd_eusilc <-
	svydesign(
		ids = ~rb030 ,
		strata = ~db040 ,
		weights = ~rb050 ,
		data="eusilc",
		dbname=dbfile,
		dbtype="SQLite"
	)


dbd_eusilc <- convey_prep( dbd_eusilc )

# headcount ratio, richness threshold fixed
svyrich(~eqincome, dbd_eusilc, type_measure = "FGTT1" , g=0, abs_thresh=30000 )
# richness gap index, richness threshold fixed
svyrich(~eqincome, dbd_eusilc, type_measure = "FGTT1" , g=1, abs_thresh=30000 )
# headcount ratio, richness threshold equal to the median
svyrich(~eqincome, dbd_eusilc, type_measure = "FGTT1" , g=0, type_thresh= "relq" )
# richness gap index, richness threshold equal to the median
svyrich(~eqincome, dbd_eusilc, type_measure = "FGTT1" , g=1, type_thresh= "relq" )
# headcount ratio, richness threshold equal to the mean
svyrich(~eqincome, dbd_eusilc, type_measure = "FGTT1" , g=0, type_thresh= "relm" )
# richness gap index, richness threshold equal to the mean
svyrich(~eqincome, dbd_eusilc, type_measure = "FGTT1" , g=1, type_thresh= "relm" )

dbRemoveTable( conn , 'eusilc' )

dbDisconnect( conn , shutdown = TRUE )

}

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