# svychu: CHU class of poverty measures (EXPERIMENTAL) In convey: Income Concentration Analysis with Complex Survey Samples

 svychu R Documentation

## 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 class '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 class '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 class 'DBIsvydesign'
svychu(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. `...` 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

### 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 "`cvystat`", which are vectors with a "`var`" attribute giving the variance and 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

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.

`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)

## 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
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 )

## End(Not run)

```

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