Poverty Probability Index (PPI) lookup table for Rwanda
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 $21.70 per day purchasing power parity (2011)
ppp1500
Below 20th percentile poverty line
ppp2170
Below 40th percentile poverty line
ppp125
Below 50th percentile poverty line
ppp250
Below 60th percentile poverty line
ppp500
Below 80th percentile poverty line
percentile20
NA
percentile40
NA
percentile60
NA
percentile80
NA
Examples
# Access Rwanda PPI table
ppiRWA2019
#> # A tibble: 101 × 20
#> score nl100 extreme nl150 nl200 ppp100 ppp190 ppp320 ppp550 ppp800 ppp1100
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 95.3 83.9 98.8 99.7 86.2 98.1 99.8 100. 100. 100.
#> 2 2 94.8 82.4 98.6 99.7 84.9 97.9 99.8 100. 100. 100.
#> 3 3 94.3 80.9 98.5 99.6 83.6 97.7 99.7 100. 100. 100.
#> 4 4 93.8 79.3 98.3 99.6 82.1 97.4 99.7 100. 100. 100.
#> 5 5 93.2 77.5 98.2 99.6 80.6 97.2 99.7 100. 100. 100.
#> 6 6 92.5 75.7 98.0 99.5 79.0 96.9 99.6 100. 100. 100.
#> 7 7 91.8 73.7 97.8 99.5 77.2 96.6 99.6 100. 100. 100.
#> 8 8 91.0 71.7 97.5 99.4 75.4 96.2 99.6 100. 100. 100.
#> 9 9 90.1 69.6 97.3 99.3 73.5 95.8 99.5 99.9 100. 100.
#> 10 10 89.2 67.3 97.0 99.2 71.4 95.4 99.4 99.9 100. 100.
#> # ℹ 91 more rows
#> # ℹ 9 more variables: ppp1500 <dbl>, ppp2170 <dbl>, ppp125 <dbl>, ppp250 <dbl>,
#> # ppp500 <dbl>, percentile20 <dbl>, percentile40 <dbl>, percentile60 <dbl>,
#> # percentile80 <dbl>
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiRWA2019[ppiRWA2019$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