Poverty Probability Index (PPI) lookup table for Malawi for 2023

Usage

ppiMWI2023

Format

A data frame with 13 columns and 101 rows:

score: PPI score
nl100: National poverty line (100%)
food: Food poverty line
ppp215: Below $2.15 per day purchasing power parity (2017)
ppp365: Below $3.65 per day purchasing power parity (2017)
ppp685: Below $6.85 per day purchasing power parity (2017)
ppp190: Below $1.90 per day purchasing power parity (2011)
ppp320: Below $3.20 per day purchasing power parity (2011)
ppp550: Below $5.50 per day purchasing power parity (2011)
percentile20: Below 20th percentile poverty line
percentile40: Below 40th percentile poverty line
percentile60: Below 50th percentile poverty line
percentile80: Below 60th percentile poverty line

Source

https://www.povertyindex.org

Examples

  # Access Malawi PPI table
  ppiMWI2023
#> # A tibble: 101 × 13
#>    score nl100  food ppp215 ppp365 ppp685 ppp190 ppp320 ppp550 percentile20
#>    <dbl> <dbl> <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>        <dbl>
#>  1     0  95.1  69.6   99.1   99.9   100.   98.6   99.9   100.         75.0
#>  2     1  94.6  67.0   99.0   99.9   100.   98.5   99.9   100.         72.8
#>  3     2  94.0  64.4   98.9   99.9   100.   98.3   99.9   100.         70.5
#>  4     3  93.4  61.7   98.8   99.9   100.   98.1   99.9   100.         68.1
#>  5     4  92.8  58.9   98.6   99.9   100.   97.9   99.8   100.         65.6
#>  6     5  92.0  56.0   98.5   99.9   100.   97.7   99.8   100.         63.0
#>  7     6  91.2  53.1   98.3   99.9   100.   97.4   99.8   100.         60.3
#>  8     7  90.3  50.1   98.1   99.8   100.   97.1   99.8   100.         57.6
#>  9     8  89.4  47.2   97.9   99.8   100.   96.8   99.7   100.         54.8
#> 10     9  88.3  44.3   97.6   99.8   100.   96.4   99.7   100.         52.0
#> # ℹ 91 more rows
#> # ℹ 3 more variables: percentile40 <dbl>, percentile60 <dbl>,
#> #   percentile80 <dbl>

  # Given a specific PPI score (from 0 - 100), get the row of poverty
  # probabilities from PPI table it corresponds to
  ppiScore <- 50
  ppiMWI2023[ppiMWI2023$score == ppiScore, ]
#> # A tibble: 1 × 13
#>   score nl100  food ppp215 ppp365 ppp685 ppp190 ppp320 ppp550 percentile20
#>   <dbl> <dbl> <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>        <dbl>
#> 1    50  9.27 0.638   28.4   78.5   96.7   22.2   70.3   94.3         1.05
#> # ℹ 3 more variables: percentile40 <dbl>, percentile60 <dbl>,
#> #   percentile80 <dbl>

  # Use subset() function to get the row of poverty probabilities corresponding
  # to specific PPI score
  ppiScore <- 50
  subset(ppiMWI2023, score == ppiScore)
#> # A tibble: 1 × 13
#>   score nl100  food ppp215 ppp365 ppp685 ppp190 ppp320 ppp550 percentile20
#>   <dbl> <dbl> <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>        <dbl>
#> 1    50  9.27 0.638   28.4   78.5   96.7   22.2   70.3   94.3         1.05
#> # ℹ 3 more variables: percentile40 <dbl>, percentile60 <dbl>,
#> #   percentile80 <dbl>

  # Given a specific PPI score (from 0 - 100), get a poverty probability
  # based on a specific poverty definition. In this example, the USAID
  # extreme poverty definition
  ppiScore <- 50
  ppiMWI2023[ppiMWI2023$score == ppiScore, "nl100"]
#> # A tibble: 1 × 1
#>   nl100
#>   <dbl>
#> 1  9.27