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

Usage

ppiIDN2023

Format

A data frame with 10 columns and 101 rows:

score

PPI score

nl100

National poverty line (100%)

ppp365

Below $3.65 per day purchasing power parity (2017)

ppp685

Below $6.85 per day purchasing power parity (2017)

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

Examples

  # Access Indonesia PPI table
  ppiIDN2023
#> # A tibble: 101 × 10
#>    score nl100 ppp365 ppp685 ppp320 ppp550 percentile20 percentile40
#>    <dbl> <dbl>  <dbl>  <dbl>  <dbl>  <dbl>        <dbl>        <dbl>
#>  1     0  84.3   84.7   97.0   80.8   94.6         84.7         93.1
#>  2     1  82.8   83.6   96.9   79.6   94.3         83.7         92.7
#>  3     2  81.2   82.6   96.7   78.3   93.9         82.7         92.2
#>  4     3  79.5   81.5   96.4   76.9   93.6         81.5         91.7
#>  5     4  77.6   80.3   96.2   75.4   93.2         80.4         91.2
#>  6     5  75.7   79.0   96.0   73.9   92.7         79.1         90.7
#>  7     6  73.6   77.8   95.7   72.4   92.3         77.9         90.1
#>  8     7  71.4   76.4   95.5   70.8   91.8         76.5         89.5
#>  9     8  69.1   75.0   95.2   69.1   91.4         75.1         88.9
#> 10     9  66.7   73.6   94.9   67.4   90.8         73.7         88.2
#> # ℹ 91 more rows
#> # ℹ 2 more variables: 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
  ppiIDN2023[ppiIDN2023$score == ppiScore, ]
#> # A tibble: 1 × 10
#>   score nl100 ppp365 ppp685 ppp320 ppp550 percentile20 percentile40 percentile60
#>   <dbl> <dbl>  <dbl>  <dbl>  <dbl>  <dbl>        <dbl>        <dbl>        <dbl>
#> 1    50  2.17   10.9   57.4   7.40   42.4         11.0         34.1         60.3
#> # ℹ 1 more variable: percentile80 <dbl>

  # Use subset() function to get the row of poverty probabilities corresponding
  # to specific PPI score
  ppiScore <- 50
  subset(ppiIDN2023, score == ppiScore)
#> # A tibble: 1 × 10
#>   score nl100 ppp365 ppp685 ppp320 ppp550 percentile20 percentile40 percentile60
#>   <dbl> <dbl>  <dbl>  <dbl>  <dbl>  <dbl>        <dbl>        <dbl>        <dbl>
#> 1    50  2.17   10.9   57.4   7.40   42.4         11.0         34.1         60.3
#> # ℹ 1 more variable: 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
  ppiIDN2023[ppiIDN2023$score == ppiScore, "nl100"]
#> # A tibble: 1 × 1
#>   nl100
#>   <dbl>
#> 1  2.17