Poverty Probability Index (PPI) lookup table for Rwanda
Format
A data frame with 20 columns and 101 rows:
scorePPI score
nl100National poverty line (100)
extremeNational poverty line (150)
nl150National poverty line (200)
nl200Below $1.90 per day purchasing power parity (2011)
ppp100Below $3.20 per day purchasing power parity (2011)
ppp190Below $5.50 per day purchasing power parity (2011)
ppp320Below $8.00 per day purchasing power parity (2011)
ppp550Below $11.00 per day purchasing power parity (2011)
ppp800Below $15.00 per day purchasing power parity (2011)
ppp1100Below $21.70 per day purchasing power parity (2011)
ppp1500Below 20th percentile poverty line
ppp2170Below 40th percentile poverty line
ppp125Below 50th percentile poverty line
ppp250Below 60th percentile poverty line
ppp500Below 80th percentile poverty line
percentile20NA
percentile40NA
percentile60NA
percentile80NA
Examples
  # Access Rwanda PPI table
  ppiRWA2019
#> # A tibble: 101 × 20
#>    score nl100 extreme nl150 nl200 ppp100 ppp190 ppp320 ppp550 ppp800 ppp1100
#>    <dbl> <dbl>   <dbl> <dbl> <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>   <dbl>
#>  1     1  95.3    83.9  98.8  99.7   86.2   98.1   99.8  100.    100.    100.
#>  2     2  94.8    82.4  98.6  99.7   84.9   97.9   99.8  100.    100.    100.
#>  3     3  94.3    80.9  98.5  99.6   83.6   97.7   99.7  100.    100.    100.
#>  4     4  93.8    79.3  98.3  99.6   82.1   97.4   99.7  100.    100.    100.
#>  5     5  93.2    77.5  98.2  99.6   80.6   97.2   99.7  100.    100.    100.
#>  6     6  92.5    75.7  98.0  99.5   79.0   96.9   99.6  100.    100.    100.
#>  7     7  91.8    73.7  97.8  99.5   77.2   96.6   99.6  100.    100.    100.
#>  8     8  91.0    71.7  97.5  99.4   75.4   96.2   99.6  100.    100.    100.
#>  9     9  90.1    69.6  97.3  99.3   73.5   95.8   99.5   99.9   100.    100.
#> 10    10  89.2    67.3  97.0  99.2   71.4   95.4   99.4   99.9   100.    100.
#> # ℹ 91 more rows
#> # ℹ 9 more variables: ppp1500 <dbl>, ppp2170 <dbl>, ppp125 <dbl>, ppp250 <dbl>,
#> #   ppp500 <dbl>, percentile20 <dbl>, percentile40 <dbl>, percentile60 <dbl>,
#> #   percentile80 <dbl>
  # Given a specific PPI score (from 0 - 100), get the row of poverty
  # probabilities from PPI table it corresponds to
  ppiScore <- 50
  ppiRWA2019[ppiRWA2019$score == ppiScore, ]
#> # A tibble: 1 × 20
#>   score nl100 extreme nl150 nl200 ppp100 ppp190 ppp320 ppp550 ppp800 ppp1100
#>   <dbl> <dbl>   <dbl> <dbl> <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>   <dbl>
#> 1    50  12.9    3.27  37.1  65.5   4.17   28.1   69.9   95.7   99.1    99.6
#> # ℹ 9 more variables: ppp1500 <dbl>, ppp2170 <dbl>, ppp125 <dbl>, ppp250 <dbl>,
#> #   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(ppiRWA2019, score == ppiScore)
#> # A tibble: 1 × 20
#>   score nl100 extreme nl150 nl200 ppp100 ppp190 ppp320 ppp550 ppp800 ppp1100
#>   <dbl> <dbl>   <dbl> <dbl> <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>   <dbl>
#> 1    50  12.9    3.27  37.1  65.5   4.17   28.1   69.9   95.7   99.1    99.6
#> # ℹ 9 more variables: ppp1500 <dbl>, ppp2170 <dbl>, ppp125 <dbl>, ppp250 <dbl>,
#> #   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 national
  # poverty line is used
  ppiScore <- 50
  ppiRWA2019[ppiRWA2019$score == ppiScore, "nl100"]
#> # A tibble: 1 × 1
#>   nl100
#>   <dbl>
#> 1  12.9
