Poverty Probability Index (PPI) lookup table for Myanmar

Poverty Probability Index (PPI) lookup table for Myanmar

Usage

ppiMMR2019

Format

A data frame with 20 columns and 101 rows:

score

PPI score

nl100

National poverty line (100)

extreme

National poverty line (150)

nl150

National poverty line (200)

nl200

Below $1.90 per day purchasing power parity (2011)

ppp100

Below $3.20 per day purchasing power parity (2011)

ppp190

Below $5.50 per day purchasing power parity (2011)

ppp320

Below $8.00 per day purchasing power parity (2011)

ppp550

Below $11.00 per day purchasing power parity (2011)

ppp800

Below $15.00 per day purchasing power parity (2011)

ppp1100

Below $21.70 per day purchasing power parity (2011)

ppp1500

Below 20th percentile poverty line

ppp2170

Below 40th percentile poverty line

ppp125

Below 50th percentile poverty line

ppp250

Below 60th percentile poverty line

ppp500

Below 80th percentile poverty line

percentile20

NA

percentile40

NA

percentile60

NA

percentile80

NA

Source

https://www.povertyindex.org

Examples

  # Access Myanmar PPI table
  ppiMMR2019
#> # 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     0  95.2    84.1  98.6  99.6  11.6    80.9   93.7   99.2   99.6    99.9
#>  2     1  94.8    82.8  98.5  99.6  10.8    79.4   93.2   99.2   99.6    99.9
#>  3     2  94.4    81.5  98.4  99.6  10.0    77.8   92.7   99.1   99.6    99.9
#>  4     3  93.9    80.1  98.3  99.5   9.27   76.0   92.1   99.0   99.5    99.9
#>  5     4  93.4    78.5  98.1  99.5   8.59   74.2   91.5   98.9   99.5    99.8
#>  6     5  92.9    77.0  98.0  99.5   7.95   72.3   90.9   98.8   99.4    99.8
#>  7     6  92.3    75.3  97.8  99.4   7.36   70.3   90.2   98.7   99.4    99.8
#>  8     7  91.7    73.5  97.7  99.4   6.81   68.2   89.5   98.6   99.4    99.8
#>  9     8  91.1    71.7  97.5  99.3   6.30   66.1   88.7   98.5   99.3    99.8
#> 10     9  90.4    69.8  97.3  99.2   5.82   63.8   87.9   98.4   99.3    99.8
#> # 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
  ppiMMR2019[ppiMMR2019$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  24.5    5.01  58.9  79.9  0.199   3.13   21.3   70.2   85.4    94.5
#> # 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(ppiMMR2019, 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  24.5    5.01  58.9  79.9  0.199   3.13   21.3   70.2   85.4    94.5
#> # 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 USAID
  # extreme poverty definition
  ppiScore <- 50
  ppiMMR2019[ppiMMR2019$score == ppiScore, "extreme"]
#> # A tibble: 1 × 1
#>   extreme
#>     <dbl>
#> 1    5.01