# svyfgtdec: FGT indices decomposition (EXPERIMENTAL) In convey: Income Concentration Analysis with Complex Survey Samples

 svyfgtdec R Documentation

## FGT indices decomposition (EXPERIMENTAL)

### Description

Estimate the Foster et al. (1984) poverty class and its components

### Usage

```svyfgtdec(formula, design, ...)

## S3 method for class '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 class 'svyrep.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 class 'DBIsvydesign'
svyfgtdec(formula, design, ...)
```

### Arguments

 `formula` a formula specifying the income variable `design` a design object of class `survey.design` or class `svyrep.design` from the `survey` library. `...` additional arguments. Currently not used. `g` If g=2 estimates the average squared normalised poverty gap. This function is defined for g >= 2 only, `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

### Details

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

### Value

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.

### Note

This function is experimental and is subject to change in later versions.

### Author(s)

Guilherme Jacob, Djalma Pessoa and Anthony Damico

### References

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.

`svyfgt,svyfgt,svyfgt`

### 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
svyfgtdec(~eqincome, des_eusilc, g=2, abs_thresh=10000)
# poverty threshold equal to arpt
svywattsdec(~eqincome, des_eusilc, g=2, type_thresh= "relq" , thresh = TRUE)
# poverty threshold equal to 0.6 times the mean
svywattsdec(~eqincome, des_eusilc, g=2, type_thresh= "relm" , thresh = TRUE)

# using svrep.design:
# absolute poverty threshold
svyfgtdec(~eqincome, des_eusilc_rep, g=2, abs_thresh=10000)
# poverty threshold equal to arpt
svywattsdec(~eqincome, des_eusilc_rep, g=2, type_thresh= "relq" , thresh = TRUE)
# poverty threshold equal to 0.6 times the mean
svywattsdec(~eqincome, des_eusilc_rep, g=2, type_thresh= "relm" , thresh = TRUE)

## Not run:

# 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
svywattsdec(~eqincome, dbd_eusilc, g=2, type_thresh= "relq" , thresh = TRUE)
# poverty threshold equal to 0.6 times the mean
svywattsdec(~eqincome, dbd_eusilc, g=2, type_thresh= "relm" , thresh = TRUE)

dbRemoveTable( conn , 'eusilc' )

dbDisconnect( conn , shutdown = TRUE )

## End(Not run)

```

convey documentation built on April 28, 2022, 1:06 a.m.