Poverty Probability Index (PPI) lookup table for El Salvador for 2021

Usage

ppiSLV2021

Format

A data frame with 21 columns and 101 rows:

score: PPI score
nl100: National poverty line (100%)
nl_extreme: National poverty line (extreme)
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)
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)
ppp800: Below $8.00 per day purchasing power parity (2011)
ppp1100: Below $11.00 per day purchasing power parity (2011)
ppp1500: Below $15.00 per day purchasing power parity (2011)
ppp2170: Below $21.70 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 60th percentile poverty line
percentile80: Below 80th percentile poverty line

Source

https://www.povertyindex.org

Examples

  # Access El Salvador PPI table
  ppiSLV2021
#> # A tibble: 101 × 21
#>    score nl100 nl_extreme ppp215 ppp365 ppp685 ppp100 ppp190 ppp320 ppp550
#>    <dbl> <dbl>      <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
#>  1     0  71.6       31.0   38.1   65.2   90.2  10.5    35.3   62.9   87.3
#>  2     1  70.5       29.8   36.0   63.3   89.6   9.47   33.4   61.0   86.6
#>  3     2  69.3       28.6   34.1   61.3   89.0   8.50   31.5   59.1   85.7
#>  4     3  68.2       27.4   32.2   59.4   88.3   7.63   29.7   57.1   84.9
#>  5     4  67.0       26.3   30.3   57.4   87.6   6.83   27.9   55.1   84.0
#>  6     5  65.8       25.1   28.5   55.3   86.8   6.12   26.3   53.1   83.0
#>  7     6  64.6       24.0   26.8   53.3   86.0   5.47   24.6   51.1   82.0
#>  8     7  63.3       23.0   25.2   51.2   85.2   4.89   23.1   49.1   81.0
#>  9     8  62.1       22.0   23.6   49.1   84.3   4.37   21.6   47.1   79.9
#> 10     9  60.8       21.0   22.0   47.1   83.4   3.90   20.2   45.1   78.8
#> # ℹ 91 more rows
#> # ℹ 11 more variables: ppp800 <dbl>, ppp1100 <dbl>, 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
  ppiSLV2021[ppiSLV2021$score == ppiScore, ]
#> # A tibble: 1 × 21
#>   score nl100 nl_extreme ppp215 ppp365 ppp685 ppp100 ppp190 ppp320 ppp550 ppp800
#>   <dbl> <dbl>      <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
#> 1    50  14.5       2.34  0.820   2.90   24.2 0.0320  0.752   2.95   18.1   42.4
#> # ℹ 10 more variables: ppp1100 <dbl>, 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(ppiSLV2021, score == ppiScore)
#> # A tibble: 1 × 21
#>   score nl100 nl_extreme ppp215 ppp365 ppp685 ppp100 ppp190 ppp320 ppp550 ppp800
#>   <dbl> <dbl>      <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
#> 1    50  14.5       2.34  0.820   2.90   24.2 0.0320  0.752   2.95   18.1   42.4
#> # ℹ 10 more variables: ppp1100 <dbl>, 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 USAID
  # extreme poverty definition
  ppiScore <- 50
  ppiSLV2021[ppiSLV2021$score == ppiScore, "nl_extreme"]
#> # A tibble: 1 × 1
#>   nl_extreme
#>        <dbl>
#> 1       2.34