Poverty Probability Index (PPI) lookup table for Uganda 2022
Format
A data frame with 21 columns and 100 rows:
score
PPI score
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 $21.70 per day purchasing power parity (2011)
percentile20
Below 20th percentile poverty line
percentile40
Below 40th percentile poverty line
percentile60
Below 50th percentile poverty line
percentile80
Below 60th percentile poverty line
Examples
# Access Uganda PPI table
ppiUGA2022
#> # A tibble: 100 × 13
#> score ppp100 ppp190 ppp320 ppp550 ppp800 ppp1100 ppp1500 ppp2170 percentile20
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 66.0 89.8 96.1 99.1 99.6 99.8 99.9 99.9 79.7
#> 2 2 63.9 89.1 95.9 99.1 99.6 99.7 99.8 99.9 78.5
#> 3 3 61.7 88.5 95.6 99.0 99.6 99.7 99.8 99.9 77.2
#> 4 4 59.5 87.8 95.4 99.0 99.6 99.7 99.8 99.9 75.9
#> 5 5 57.3 87.0 95.2 98.9 99.5 99.7 99.8 99.9 74.6
#> 6 6 55.0 86.2 94.9 98.8 99.5 99.7 99.8 99.9 73.2
#> 7 7 52.7 85.4 94.6 98.8 99.5 99.7 99.8 99.9 71.8
#> 8 8 50.4 84.6 94.3 98.7 99.5 99.7 99.8 99.9 70.3
#> 9 9 48.0 83.7 94.0 98.6 99.4 99.6 99.8 99.9 68.8
#> 10 10 45.7 82.7 93.7 98.5 99.4 99.6 99.8 99.9 67.2
#> # ℹ 90 more rows
#> # ℹ 3 more variables: percentile40 <dbl>, percentile60 <dbl>,
#> # percentile80 <dbl>
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiUGA2022[ppiUGA2022$score == ppiScore, ]
#> # A tibble: 1 × 13
#> score ppp100 ppp190 ppp320 ppp550 ppp800 ppp1100 ppp1500 ppp2170 percentile20
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 50 2.02 24.6 61.4 86.8 94.3 96.9 98.3 99.4 10.2
#> # ℹ 3 more variables: percentile40 <dbl>, percentile60 <dbl>,
#> # percentile80 <dbl>
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiUGA2022, score == ppiScore)
#> # A tibble: 1 × 13
#> score ppp100 ppp190 ppp320 ppp550 ppp800 ppp1100 ppp1500 ppp2170 percentile20
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 50 2.02 24.6 61.4 86.8 94.3 96.9 98.3 99.4 10.2
#> # ℹ 3 more variables: 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 purchasing
# power parity at $1.00
ppiScore <- 50
ppiUGA2022[ppiUGA2022$score == ppiScore, "ppp100"]
#> # A tibble: 1 × 1
#> ppp100
#> <dbl>
#> 1 2.02