convey (version 0.2.2)

svybcc: Bourguignon-Chakravarty multidimensional poverty class (EXPERIMENTAL)

Description

Estimate indices from the Bourguignon-Chakravarty class, a class of poverty measures.

Usage

svybcc(formula, design, ...)
# S3 method for survey.design
svybcc(
  formula,
  design,
  theta = 0.5,
  alpha = 0.5,
  cutoffs,
  dimw = NULL,
  na.rm = FALSE,
  ...
)
# S3 method for svyrep.design
svybcc(
  formula,
  design,
  theta = 0.5,
  alpha = 0.5,
  cutoffs,
  dimw = NULL,
  na.rm = FALSE,
  ...
)
# S3 method for DBIsvydesign
svybcc(formula, design, ...)

Arguments

formula

a formula specifying the variables. Variables can be numeric or ordered factors.

design

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

...

future expansion

theta

a scalar defining the elasticity of substitution between the normalized gaps of the attributes.

alpha

a scalar that can be interpreted as the society's aversion to poverty.

cutoffs

a list defining each variable's deprivation limit.

dimw

a vector defining the weight of each dimension in the multidimensional deprivation sum.

na.rm

Should cases with missing values be dropped?

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.

Details

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

References

Francois Bourguignon and Satya R. Chakravarty (2003). The measurement of multidimensional poverty. Journal of Economic Inequality, v. 1, n. 1, April 2003, pp. 1-25. URL http://dx.doi.org/10.1023/A:1023913831342.

Maria Casilda Lasso de la Vega, Ana Urrutia and Henar Diez (2009). The Bourguignon and Chakravarty multidimensional poverty family: a characterization. Working Papers 109, ECINEQ, Society for the Study of Economic Inequality.

See Also

svyafc

Examples

# NOT RUN {
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)
des_eusilc <- update(des_eusilc, pb220a = ordered( pb220a ) )

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

# cutoffs
cos <- list( 10000, 5000 )

# variables without missing values
svybcc( ~ eqincome + hy050n , design = des_eusilc , cutoffs = cos )
svybcc( ~ eqincome + hy050n , design = des_eusilc_rep , cutoffs = cos )

# subsetting:
sub_des_eusilc <- subset( des_eusilc, db040 == "Styria")
sub_des_eusilc_rep <- subset( des_eusilc_rep, db040 == "Styria")

svybcc( ~ eqincome + hy050n , design = sub_des_eusilc , cutoffs = cos )
svybcc( ~ eqincome + hy050n , design = sub_des_eusilc_rep , cutoffs = cos )

# }
# NOT RUN {
# including factor variable with missings
cos <- list( 10000, 5000, "EU" )
svybcc(~eqincome+hy050n+pb220a, des_eusilc, cutoffs = cos, na.rm = FALSE )
svybcc(~eqincome+hy050n+pb220a, des_eusilc, cutoffs = cos, na.rm = TRUE )
svybcc(~eqincome+hy050n+pb220a, des_eusilc_rep, cutoffs = cos, na.rm = FALSE )
svybcc(~eqincome+hy050n+pb220a, des_eusilc_rep, cutoffs = cos, na.rm = TRUE )

# 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 )
dbd_eusilc <- update( dbd_eusilc, pb220a = ordered( pb220a ) )

# cutoffs
cos <- list( 10000 , 5000 )

# variables without missing values
svybcc(~eqincome+hy050n, design = dbd_eusilc, cutoffs = cos )

# subsetting:
sub_dbd_eusilc <- subset( dbd_eusilc, db040 == "Styria")
svybcc(~eqincome+hy050n, design = sub_dbd_eusilc, cutoffs = cos )

# cutoffs
cos <- list( 10000, 5000, "EU" )

# including factor variable with missings
svybcc(~eqincome+hy050n+pb220a, dbd_eusilc, cutoffs = cos, na.rm = FALSE )
svybcc(~eqincome+hy050n+pb220a, dbd_eusilc, cutoffs = cos, na.rm = TRUE )

dbRemoveTable( conn , 'eusilc' )

dbDisconnect( conn , shutdown = TRUE )

# }
# NOT RUN {
# }