convey (version 0.2.5)

svychu: CHU class of poverty measures (EXPERIMENTAL)

Description

Estimate the Clark, Hemming and Ulph (1981) class of poverty measures

Usage

svychu(formula, design, ...)
# S3 method for survey.design
svychu(
  formula,
  design,
  g,
  type_thresh = "abs",
  abs_thresh = NULL,
  percent = 0.6,
  quantiles = 0.5,
  na.rm = FALSE,
  thresh = FALSE,
  ...
)
# S3 method for svyrep.design
svychu(
  formula,
  design,
  g,
  type_thresh = "abs",
  abs_thresh = NULL,
  percent = 0.6,
  quantiles = 0.5,
  na.rm = FALSE,
  thresh = FALSE,
  ...
)
# S3 method for DBIsvydesign
svychu(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 svyarpr and svyarpt

g

A parameter where (1 - g) defines the inequality aversion among the poor. If g = 0, the CHU class becomes a monotonic transform of the Watts poverty measure.

type_thresh

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

abs_thresh

poverty threshold value if type_thresh is "abs"

percent

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

quantiles

the quantile used used in the poverty threshold definition

na.rm

Should cases with missing values be dropped?

thresh

return the poverty 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

Vijay Verma and Gianni Betti (2011). Taylor linearization sampling errors and design effects for poverty measures and other complex statistics. Journal Of Applied Statistics, Vol.38, No.8, pp. 1549-1576, <doi:10.1080/02664763.2010.515674>

Anthony B. Atkinson (1987). On the measurement of poverty. Econometrica, Vol.55, No.4, (Jul., 1987), pp. 749-764, URL https://www.jstor.org/stable/1911028.

Stephen Clark, Richard Hemming and David Ulph (1981). On Indices for the Measurement of Poverty. The Economic Journal, Vol.91, No.362, (Jun., 1981), pp. 515-526, URL https://www.jstor.org/stable/2232600.

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

svywatts

Examples

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 )

# absolute poverty threshold
svychu(~eqincome, des_eusilc, g=1,  abs_thresh=10000)
# poverty threshold equal to arpt
svychu(~eqincome, des_eusilc, g=1, type_thresh= "relq" , thresh = TRUE)
# poverty threshold equal to 0.6 times the mean
svychu(~eqincome, des_eusilc, g=1, type_thresh= "relm" , thresh = TRUE)

#  using svrep.design:
# absolute poverty threshold
svychu(~eqincome, des_eusilc_rep, g=1,  abs_thresh=10000)
# poverty threshold equal to arpt
svychu(~eqincome, des_eusilc_rep, g=1, type_thresh= "relq" , thresh = TRUE)
# poverty threshold equal to 0.6 times the mean
svychu(~eqincome, des_eusilc_rep, g=1, type_thresh= "relm" , thresh = TRUE)

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 )

# absolute poverty threshold
svychu(~eqincome, dbd_eusilc, g=1,  abs_thresh=10000)
# poverty threshold equal to arpt
svychu(~eqincome, dbd_eusilc, g=1, type_thresh= "relq" , thresh = TRUE)
# poverty threshold equal to 0.6 times the mean
svychu(~eqincome, dbd_eusilc, g=1, type_thresh= "relm" , thresh = TRUE)

dbRemoveTable( conn , 'eusilc' )

dbDisconnect( conn , shutdown = TRUE )

}