Poverty Probability Index (PPI) lookup table for Malawi

Poverty Probability Index (PPI) lookup table for Malawi

Usage

ppiMWI2020

Format

A data frame with 16 columns and 101 rows:

score

PPI score

nl100

National poverty line (100%)

extreme

Extreme poverty line

nl150

National poverty line (150%)

nl200

National poverty line (200%)

ppp100

Below $1.00 per day purchasing power parity (2011)

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)

ppp125

Below $1.25 per day purchasing power parity (2005)

ppp250

Below $2.50 per day purchasing power parity (2005)

ppp500

Below $5.00 per day purchasing power parity (2005)

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
  ppiMWI2020
#> # A tibble: 100 × 16
#>    score nl100 extreme nl150 nl200 ppp100 ppp190 ppp320 ppp550 ppp125 ppp250
#>    <dbl> <dbl>   <dbl> <dbl> <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
#>  1     1  96.3    80.3  99.0  99.6   89.8   98.7   99.9   100.   95.4   99.5
#>  2     2  95.9    78.6  98.9  99.6   88.8   98.6   99.9   100.   94.9   99.5
#>  3     3  95.5    76.8  98.8  99.6   87.8   98.5   99.9   100.   94.4   99.4
#>  4     4  95.1    74.8  98.7  99.6   86.6   98.4   99.9   100.   93.9   99.4
#>  5     5  94.6    72.8  98.6  99.5   85.4   98.2   99.8   100.   93.3   99.3
#>  6     6  94.1    70.7  98.5  99.5   84.1   98.1   99.8   100.   92.7   99.3
#>  7     7  93.6    68.4  98.3  99.4   82.8   97.9   99.8   100.   92.0   99.2
#>  8     8  93.0    66.1  98.2  99.4   81.3   97.7   99.8   100.   91.3   99.2
#>  9     9  92.3    63.7  98.0  99.3   79.7   97.6   99.8   100.   90.5   99.1
#> 10    10  91.6    61.2  97.9  99.3   78.0   97.3   99.8   100.   89.6   99.0
#> # ℹ 90 more rows
#> # ℹ 5 more variables: ppp500 <dbl>, percentile20 <dbl>, 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
  ppiMWI2020[ppiMWI2020$score == ppiScore, ]
#> # A tibble: 1 × 16
#>   score nl100 extreme nl150 nl200 ppp100 ppp190 ppp320 ppp550 ppp125 ppp250
#>   <dbl> <dbl>   <dbl> <dbl> <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
#> 1    50  19.4    2.27  62.3  83.3   6.00   56.1   92.4   99.3   15.2   79.7
#> # ℹ 5 more variables: ppp500 <dbl>, percentile20 <dbl>, percentile40 <dbl>,
#> #   percentile60 <dbl>, percentile80 <dbl>

  # Use subset() function to get the row of poverty probabilities corresponding
  # to specific PPI score
  ppiScore <- 50
  subset(ppiMWI2020, score == ppiScore)
#> # A tibble: 1 × 16
#>   score nl100 extreme nl150 nl200 ppp100 ppp190 ppp320 ppp550 ppp125 ppp250
#>   <dbl> <dbl>   <dbl> <dbl> <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
#> 1    50  19.4    2.27  62.3  83.3   6.00   56.1   92.4   99.3   15.2   79.7
#> # ℹ 5 more variables: ppp500 <dbl>, percentile20 <dbl>, 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
  ppiMWI2020[ppiMWI2020$score == ppiScore, "nl100"]
#> # A tibble: 1 × 1
#>   nl100
#>   <dbl>
#> 1  19.4