Multidimensional Poverty Index (Alkire-Foster Method)

Source: R/mpi.R

This function computes the Multidimensional Poverty Index (MPI) using the Alkire-Foster methodology. It takes as input a data frame of binary deprivation indicators, a vector of weights, and a global poverty cutoff `k`.

mpi(data, weights, k)

Arguments

data

A data.frame where each column is a binary deprivation indicator (0 = not deprived, 1 = deprived).

weights

A numeric vector of weights corresponding to each indicator. Its length must equal the number of columns in `data`.

k

The global poverty cutoff (between 0 and 1), above which an individual is considered multidimensionally poor.

Value

A list containing:

  • data : The original data.frame, augmented with two new columns: the weighted deprivation score and the binary poverty status.

  • summary : A data.frame summarizing the Headcount Ratio (H), Intensity (A), and the MPI value.

  • plot : A `plotly` interactive bar chart showing the percentage of poor and non-poor individuals.

Details

It also returns an interactive `plotly` bar chart showing the proportions of poor and non-poor individuals.

Examples

data <- data.frame(
  edu = c(1, 0, 1, 1, 0),
  health = c(0, 1, 1, 1, 0),
  water = c(1, 0, 1, 1, 1)
)
weights <- c(0.4, 0.3, 0.3)
k <- 0.33
res <- mpi(data, weights, k)
head(res$data)
#>   edu health water DeprivationScore IsPoor
#> 1   1      0     1              0.7      1
#> 2   0      1     0              0.3      0
#> 3   1      1     1              1.0      1
#> 4   1      1     1              1.0      1
#> 5   0      0     1              0.3      0
res$summary
#>                                 Metric Value
#> 1                  Headcount Ratio (H)  0.60
#> 2                        Intensity (A)  0.90
#> 3 Multidimensional Poverty Index (MPI)  0.54
res$plot