Estimate the Foster et al. (1984) poverty class and its components
svyfgtdec(formula, design, ...)
# S3 method for survey.design
svyfgtdec(
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
svyfgtdec(
formula,
design,
g,
type_thresh = "abs",
abs_thresh = NULL,
percent = 0.6,
quantiles = 0.5,
na.rm = FALSE,
thresh = FALSE,
return.replicates = FALSE,
...
)
# S3 method for DBIsvydesign
svyfgtdec(formula, design, ...)a formula specifying the income variable
a design object of class survey.design or class svyrep.design from the survey library.
additional arguments. Currently not used.
If g=2 estimates the average squared normalised poverty gap. This function is defined for g >= 2 only,
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.
poverty threshold value if type_thresh is "abs"
the multiple of the the quantile or mean used in the poverty threshold definition
the quantile used used in the poverty threshold definition
Should cases with missing values be dropped?
return the poverty threshold value
Return the replicate estimates?
Object of class "cvydstat", with estimates for the FGT(g), FGT(0), FGT(1), income gap ratio and GEI(income gaps; epsilon = g) with a "var" attribute giving the variance-covariance matrix.
A "statistic" attribute giving the name of the statistic.
you must run the convey_prep function on your survey design object immediately after creating it with the svydesign or svrepdesign function.
This function is experimental and is subject to change in later versions.
Oihana Aristondo, Cassilda Lasso De La vega and Ana Urrutia (2010). A new multiplicative decomposition for the Foster-Greer-Thorbecke poverty indices. Bulletin of Economic Research, Vol.62, No.3, pp. 259-267. University of Wisconsin. <doi:10.1111/j.1467-8586.2009.00320.x>
James Foster, Joel Greer and Erik Thorbecke (1984). A class of decomposable poverty measures. Econometrica, Vol.52, No.3, pp. 761-766.
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/en/catalogue/12-001-X19990024882.
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
svyfgtdec(~eqincome, des_eusilc, g=2, abs_thresh=10000)
#> Warning: The svyfgtdec function is experimental and is subject to changes in later versions.
#> fgt2 decomposition SE
#> fgt2 0.016189 0.0007
#> fgt0 0.114440 0.0027
#> fgt1 0.032085 0.0011
#> igr 0.280369 0.0063
#> gei(poor;epsilon=2) 0.399834 0.0132
# poverty threshold equal to arpt
svyfgtdec(~eqincome, des_eusilc, g=2, type_thresh= "relq" , thresh = TRUE)
#> Warning: The svyfgtdec function is experimental and is subject to changes in later versions.
#> fgt2 decomposition SE
#> fgt2 0.019186 0.0008
#> fgt0 0.144442 0.0028
#> fgt1 0.039809 0.0011
#> igr 0.275608 0.0053
#> gei(poor;epsilon=2) 0.374324 0.0107
# poverty threshold equal to 0.6 times the mean
svyfgtdec(~eqincome, des_eusilc, g=2, type_thresh= "relm" , thresh = TRUE)
#> Warning: The svyfgtdec function is experimental and is subject to changes in later versions.
#> fgt2 decomposition SE
#> fgt2 0.023702 0.0008
#> fgt0 0.188180 0.0028
#> fgt1 0.051187 0.0011
#> igr 0.272010 0.0045
#> gei(poor;epsilon=2) 0.351163 0.0089
# using svrep.design:
# absolute poverty threshold
svyfgtdec(~eqincome, des_eusilc_rep, g=2, abs_thresh=10000)
#> Warning: The svyfgtdec function is experimental and is subject to changes in later versions.
#> fgt2 decomposition SE
#> fgt2 0.016189 0.0007
#> fgt0 0.114440 0.0027
#> fgt1 0.032085 0.0010
#> igr 0.280369 0.0059
#> gei(poor;epsilon=2) 0.399834 0.0129
# poverty threshold equal to arpt
svyfgtdec(~eqincome, des_eusilc_rep, g=2, type_thresh= "relq" , thresh = TRUE)
#> Warning: The svyfgtdec function is experimental and is subject to changes in later versions.
#> fgt2 decomposition SE
#> fgt2 0.019186 0.0007
#> fgt0 0.144442 0.0031
#> fgt1 0.039809 0.0010
#> igr 0.275608 0.0049
#> gei(poor;epsilon=2) 0.374324 0.0108
# poverty threshold equal to 0.6 times the mean
svyfgtdec(~eqincome, des_eusilc_rep, g=2, type_thresh= "relm" , thresh = TRUE)
#> Warning: The svyfgtdec function is experimental and is subject to changes in later versions.
#> fgt2 decomposition SE
#> fgt2 0.023702 0.0008
#> fgt0 0.188180 0.0035
#> fgt1 0.051187 0.0012
#> igr 0.272010 0.0040
#> gei(poor;epsilon=2) 0.351163 0.0075
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
svyfgtdec(~eqincome, dbd_eusilc, g=2, abs_thresh=10000)
# poverty threshold equal to arpt
svyfgtdec(~eqincome, dbd_eusilc, g=2, type_thresh= "relq" , thresh = TRUE)
# poverty threshold equal to 0.6 times the mean
svyfgtdec(~eqincome, dbd_eusilc, g=2, type_thresh= "relm" , thresh = TRUE)
dbRemoveTable( conn , 'eusilc' )
dbDisconnect( conn , shutdown = TRUE )
}