README.md

In a-benini/mdepriv: Synthetic Indicators of Multiple Deprivation

mdepriv: Synthetic scores of multiple deprivation

Purpose

mdepriv is a R package for combining binary, continuous and suitably transformed ordinal items/indicators of deprivation into synthetic measures of deprivation. As such, it is a tool of poverty analysis. It is suitable also for generating composite measures of severity and vulnerability in the humanitarian realm. The R implementation translates the original Stata version by Pi Alperin & Van Kerm (2009), with additional features (notably, non-integer sampling weights are admitted).

mdepriv returns unit-level synthetic scores of multiple deprivation and their statistical summaries. It offers several methods for determining item/indicator weights in response to user preferences for rewarding better discrimination and penalizing redundancy.

mdepriv is particularly appropriate in situations where the underlying concept of deprivation / severity / vulnerability is intuitively multi-dimensional, but the structure of dimensions is poorly understood; plausibly they overlap, i.e. they reinforce each other to unknown degrees.

Also, the measures produced under mdepriv do not presume normative standards (e.g., poverty lines). There are no a-priori cut-offs of the kind that are fundamental to multi-dimensional poverty measures in the Alkire-Foster tradition. Shortfall indicators (e.g., years of basic education missed) can be used the same way as non-normative ones (e.g., workdays lost to illness).

Installation

# install package remotes if not yet installed
# install.packages("remotes")

# install fast from GitHub without vignettes (not recommended)
# remotes::install_github("a-benini/mdepriv")

# recommended: installation from GitHub including vignettes:
remotes::install_github(
  "a-benini/mdepriv",
  build_vignettes = TRUE,
  dependencies = c("Imports", "Suggests")
  )

Usage

library(mdepriv)

Usage Example

head(simul_data, 3) # demo dataset included in the mdepriv package
#>   id y1 y2 y3  y4    y5    y6    y7 sampl_weights
#> 1  1  0  0  0 0.0 0.369 0.174 0.196         0.556
#> 2  2  1  0  1 0.2 0.762 0.832 1.000         1.500
#> 3  3  0  1  1 0.4 0.708 0.775 0.833         0.973

mdepriv(data = simul_data,                  # a dataset ...
        items = c("y1", "y3", "y4", "y7"),  # from which items/indicators ...
        sampling_weights = "sampl_weights", # and optionally sampl. weights are selected ....
        method = "ds")                      # to be analyzed according to a chosen standard method (= weighting scheme)
#> $weighting_scheme
#> [1] "Desai & Shah (1988) weighting scheme"
#> 
#> $aggregate_deprivation_level
#> [1] 0.3243723
#> 
#> $summary_by_item
#>    Item     Index    Weight     Contri     Share
#> 1    y1 0.1501043 0.3352740 0.05032605 0.1551491
#> 2    y3 0.5402995 0.1813465 0.09798143 0.3020648
#> 3    y4 0.2683779 0.2886164 0.07745828 0.2387944
#> 4    y7 0.5062895 0.1947631 0.09860649 0.3039918
#> 5 Total        NA 1.0000000 0.32437225 1.0000000
#> 
#> $summary_scores
#>   N_Obs.      Mean Std._Dev. Min Max
#> 1    100 0.3266375 0.2320696   0   1

The above example demonstrates a simple case with four specified arguments of the mdepriv package’s core function and four default output elements, which are gathered in a list. However, this function offers several more arguments and outputs. The vignette Get Started with mdepriv walks one through these manifold options.

References

Alkire, S., J. Foster, S. Seth, J. M. Roche and M. E. Santos (2015). Multidimensional poverty measurement and analysis, Oxford University Press, USA.

Pi Alperin, M. N. and Van Kerm, P. (2009), ‘mdepriv - Synthetic indicators of multiple deprivation’, v2.0 (revised March 2014), CEPS/INSTEAD, Esch/Alzette, Luxembourg. http://medim.ceps.lu/stata/mdepriv_v3.pdf (2020-01-02).

a-benini/mdepriv documentation built on Jan. 27, 2024, 3:28 a.m.