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Last data update: 2014.03.03

R: Decomposition by Groups for GEI

decompGEI

R Documentation

Decomposition by Groups for GEI

Description

Decomposes by population subgroups a generalized entropy inequality measure within a vector.

Usage

decompGEI(x, z, w = NULL, alpha = 1, ELMO = TRUE)

Arguments

`x`	Numeric vector with non-negative values (strictly positive when `alpha`=0 or `alpha`=1).
`z`	Factor who determines the subgroups.
`w`	Numeric vector of sampling weigths (optional).
`alpha`	Parameter of the generalized entropy index. Theil index (TT) is calculated for `alpha`=1, the mean log deviation (TL) for `alpha`=0.
`ELMO`	When `ELMO` is `TRUE`, a "maximum" between-group inequality index is estimated using the Elbers and alii method (2005).

Value

A list of class "ICI" with components:

`ineq`	a list with components `GEI` (value of inequality index) and `alpha` (value of parameter).
`decomp`	a list with components `within` (value of within-group inequality), `between` (value of between-group inequality) and, if `ELMO` is `TRUE`, `betweenELMO` (value of maximum between-group inequality).
`intra`	a list with components `GEIGroups` (the subgroup values of inequality index) and `contribGEIGroups` (the contribution of each subgroup to the total within-groups inequality).
`ws`	a list with components `wIntra` (the subgroup weights) and `sIntra` (the subgroup shares of `x`).
`nas`	a list with `NA` counts, including components `xNA`, `zNA`, `wNA` and `totalNA`.

References

Cowell F.A. (2000) Measurement of Inequality. In Atkinson A.B., Bourguignon F. (Eds.) Handbook of Income Distribution. Elsevier, Vol. 1, pp. 87-166.

Elbers C., Lanjouw P., Mistiaen J.A., Ozler B. (2005) Re-Interpreting Sub-Group Inequality Decompositions. World Bank, World Bank Policy Research Working Paper 3687, 42 p.

Examples

data(hhbudgets)

decompGEI(hhbudgets[,"ingreso"], hhbudgets[,"estructura"], alpha=4)
summary(hhbudgets[,"tenencia"]) #35 NA's
decompGEI(x=hhbudgets[,"transporte"], z=hhbudgets[,"tenencia"], w=hhbudgets[,"factor"], ELMO=FALSE)
summary(decompGEI(x=hhbudgets[,"transporte"], z=hhbudgets[,"tenencia"], w=hhbudgets[,"factor"], alpha=1.5))

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(IC2)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/IC2/decompGEI.Rd_%03d_medium.png", width=480, height=480)
> ### Name: decompGEI
> ### Title: Decomposition by Groups for GEI
> ### Aliases: decompGEI
> 
> ### ** Examples
> 
> data(hhbudgets)
> 
> decompGEI(hhbudgets[,"ingreso"], hhbudgets[,"estructura"], alpha=4)
$ineq
$ineq$index
     GEI 
128.0722 

$ineq$parameter
alpha 
    4 


$decomp
$decomp$within
[1] 128.0624

$decomp$between
[1] 0.00984258

$decomp$betweenELMO
[1] 23.42324


$intra
$intra$GEIGroups
unipersonal     nuclear    ampliado   compuesto coresidente 
  3.9893931 181.5403932   4.8945765   0.7425743   0.1760261 

$intra$contribGEIGroups
 unipersonal      nuclear     ampliado    compuesto  coresidente 
  0.12572964 126.50647452   1.39971064   0.01596111   0.01448319 


$ws
$ws$wIntra
unipersonal     nuclear    ampliado   compuesto coresidente 
0.114476790 0.614083399 0.263965382 0.003540519 0.003933910 

$ws$sIntra
unipersonal     nuclear    ampliado   compuesto coresidente 
0.082922195 0.633804602 0.269302892 0.005557520 0.008412791 


$nas
$nas$xNA
[1] 0

$nas$zNA
[1] 0

$nas$wNA
NULL

$nas$totalNA
[1] 0


attr(,"class")
[1] "ICI"
> summary(hhbudgets[,"tenencia"]) #35 NA's
       rentada       prestada propia_pagando         propia        litigio 
           501            432            159           1343             63 
          otra           NA's 
             9             35 
> decompGEI(x=hhbudgets[,"transporte"], z=hhbudgets[,"tenencia"], w=hhbudgets[,"factor"], ELMO=FALSE)
NULL
> summary(decompGEI(x=hhbudgets[,"transporte"], z=hhbudgets[,"tenencia"], w=hhbudgets[,"factor"], alpha=1.5))
    GEI          alpha        
0.61155        1.50000        

Decomposition:
  within   between  
0.599633  0.011912  
betweenELMO  
    0.42559  
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>