A framework to calculate Multidimensional Poverty Index (MPI) by using Alkire-Foster method
Given N individuals, each person has D indicators of deprivation, the package compute MPI value to represent the degree of poverty in a population.
The inputs are
The main output is the MPI value, which has the range between zero and one. MPI value is approaching one if almost all people are deprived in all indicators, and it is approaching zero if almost no people are deprived in any indicator.
You can install the newest version from Github.
devtools::install_github('9POINTEIGHT/MPI')
First we will use simulation poverty data from build-in package. Which contains 30 rows of individuals, 16 columns of deprivatied dimensions (1 is deprived and 0 is not deprived), and simulated forth-level administrative division of France.
MPI::examplePovertydf
We use the following function to compute MPI.
out_seq <- AF_Seq(df = examplePovertydf, g = "Region", k = 3)
Input will be...
df A poverty data frameg 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.(default as NULL)w An indicator weight vectors (default as 1)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)Output will be list of lists separated into group, and each list contains...
groupname A Grouped value from column input g
total Number of population in each grouppoors Number of deprived people in each groupH Head count Ratio, the proportion of the population that is multidimensionally deprived calculated by dividing the number of poor people with the total number of people.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.M0 Multidimensional Poverty Index, calculated by H times A.[[1]]
[[1]]$groupname
[1] "Bastia"
[[1]]$total
[1] 2
[[1]]$poors
[1] 2
[[1]]$H
[1] 1
[[1]]$A
[1] 0.4090909
[[1]]$M0
[1] 0.4090909
DimentionalContribution
indnames The poverty indicatorsdiCont 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.
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 (1 and 0). 1 indicates that a person does not meet the threshold (poor person) and 0 indicates 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.
Alkire S., Chatterjee, M., Conconi, A., Seth, S. and Ana Vaz (2014) Global Multidimensional Poverty Index 2014. OPHI Briefing 21, Oxford: University of Oxford.
Please, visit Global Multidimensional Poverty Index 2014