MPI_demo"

In MPI: Computation of Multidimensional Poverty Index (MPI)

Simple Simulation

library(MPI)
library(kableExtra) 

Loading Data

MPI::examplePovertydf is a simulation poverty data frame contains 16 indicators column which 1 means deprived and 0 means not deprived, and simulated forth-level administrative division of France.

data(examplePovertydf)

kable(head(examplePovertydf, n = 3), 
      "html", 
      col.names = gsub("[.]", " ", names(examplePovertydf))) %>% 
  kable_styling()

Calculation

For calculating MPI using AF_Seq for sequential run or AF_Par for parallel run.

Input will be

• df A poverty data frame
• g A column name that will be used to divide data into groups. When the value is NULL, the entire data is not separated into groups.
• w An indicator weight vectors
• k A poverty cut-off. If an aggregate value of indicators of a specific person is above or equal the value of k, then this person is considered to be a poor.(default as 1)

out_seq <- AF_Seq(examplePovertydf, g = "Region", k = 3)

Output will be list of lists separated into group, and each list contains

• groupname A Grouped value from column input g

out_seq[[1]]$groupname

• total Number of population in each group

out_seq[[1]]$total

• poors Number of deprived people in each group

out_seq[[1]]$poors

• H Head count ratio, the proportion of the population that is multidimensionally deprived calculated by divide the number of poor people with the total number of people.

out_seq[[1]]$H

• A Average deprivation share among poor people, by aggregating the proportion of total deprivations each person and dividing by the total number of poor people.

out_seq[[1]]$A

• M0 Multidimensional Poverty Index, calculated by H times A.

out_seq[[1]]$M0

• DimentionalContribution
• indnames The poverty indicators
• diCont Dimensional contributions denotes the magnitude of each indicator impacts on MPI.
• UncensoredHCount Uncensored head count of indicator denotes the population that are deprived in that indicator.
• UncensoredHRatio Uncensored head count ratio of indicator denotes the proportion of the population deprived in that indicator.
• CensoredHCount Censored head count of indicator denotes the population that are multidimensionally poor and deprived in that indicator at the same time.
• CensoredHRatio Censored head count ratio of indicator denotes the proportion that is multidimensionally poor and deprived in that indicator at the same time.

kable(out_seq[[1]]$DimentionalContribution, 
            "html",
            col.names = gsub("[.]", " ", names(out_seq[[1]]$DimentionalContribution))) %>%
  kable_styling()

• pov_df poverty data frame
• Cvector is a vector of total values of deprived indicators adjusted by weight of indicators. Each element in Cvector represents a total value of each individual.
• IsPoverty is a binary variable with only 1 and 0, with 1 indicating that person does not meet the threshold(poor person) and 0 indicating the opposite.
• Intensity The intensity of a deprived indication among impoverished people is computed by dividing the number of deprived indicators by the total number of indicators.

kable(out_seq[[1]]$pov_df, 
            "html",
            col.names = gsub("[.]", " ", names(out_seq[[1]]$pov_df))) %>%
  kable_styling()

MPI documentation built on April 5, 2022, 5:06 p.m.