Poverty Probability Index (PPI) lookup table for Egypt
Format
A data frame with 8 columns and 101 rows:
scorePPI score
nu100National upper poverty line (100%)
nl100National lower poverty line (100%)
nlFoodFood poverty line
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
Examples
# Access Egypt PPI table
ppiEGY2010
#> score nu100 nl100 nlFood extreme ppp125 ppp250 ppp375
#> 0 0 100.0 100.0 34.3 100.0 0.0 100.0 100.0
#> 1 1 100.0 100.0 34.3 100.0 0.0 100.0 100.0
#> 2 2 100.0 100.0 34.3 100.0 0.0 100.0 100.0
#> 3 3 100.0 100.0 34.3 100.0 0.0 100.0 100.0
#> 4 4 100.0 100.0 34.3 100.0 0.0 100.0 100.0
#> 5 5 100.0 100.0 66.6 91.9 66.3 100.0 100.0
#> 6 6 100.0 100.0 66.6 91.9 66.3 100.0 100.0
#> 7 7 100.0 100.0 66.6 91.9 66.3 100.0 100.0
#> 8 8 100.0 100.0 66.6 91.9 66.3 100.0 100.0
#> 9 9 100.0 100.0 66.6 91.9 66.3 100.0 100.0
#> 10 10 100.0 82.7 34.4 85.7 24.1 100.0 100.0
#> 11 11 100.0 82.7 34.4 85.7 24.1 100.0 100.0
#> 12 12 100.0 82.7 34.4 85.7 24.1 100.0 100.0
#> 13 13 100.0 82.7 34.4 85.7 24.1 100.0 100.0
#> 14 14 100.0 82.7 34.4 85.7 24.1 100.0 100.0
#> 15 15 91.9 60.5 22.6 61.7 13.0 86.6 98.2
#> 16 16 91.9 60.5 22.6 61.7 13.0 86.6 98.2
#> 17 17 91.9 60.5 22.6 61.7 13.0 86.6 98.2
#> 18 18 91.9 60.5 22.6 61.7 13.0 86.6 98.2
#> 19 19 91.9 60.5 22.6 61.7 13.0 86.6 98.2
#> 20 20 86.5 58.6 16.1 56.4 6.5 86.5 99.3
#> 21 21 86.5 58.6 16.1 56.4 6.5 86.5 99.3
#> 22 22 86.5 58.6 16.1 56.4 6.5 86.5 99.3
#> 23 23 86.5 58.6 16.1 56.4 6.5 86.5 99.3
#> 24 24 86.5 58.6 16.1 56.4 6.5 86.5 99.3
#> 25 25 76.8 45.8 7.5 45.6 5.0 74.1 97.1
#> 26 26 76.8 45.8 7.5 45.6 5.0 74.1 97.1
#> 27 27 76.8 45.8 7.5 45.6 5.0 74.1 97.1
#> 28 28 76.8 45.8 7.5 45.6 5.0 74.1 97.1
#> 29 29 76.8 45.8 7.5 45.6 5.0 74.1 97.1
#> 30 30 65.2 32.2 4.5 30.3 2.1 62.8 94.4
#> 31 31 65.2 32.2 4.5 30.3 2.1 62.8 94.4
#> 32 32 65.2 32.2 4.5 30.3 2.1 62.8 94.4
#> 33 33 65.2 32.2 4.5 30.3 2.1 62.8 94.4
#> 34 34 65.2 32.2 4.5 30.3 2.1 62.8 94.4
#> 35 35 50.9 19.4 2.2 20.9 1.4 48.1 89.9
#> 36 36 50.9 19.4 2.2 20.9 1.4 48.1 89.9
#> 37 37 50.9 19.4 2.2 20.9 1.4 48.1 89.9
#> 38 38 50.9 19.4 2.2 20.9 1.4 48.1 89.9
#> 39 39 50.9 19.4 2.2 20.9 1.4 48.1 89.9
#> 40 40 44.6 14.3 1.4 16.1 0.3 43.2 87.3
#> 41 41 44.6 14.3 1.4 16.1 0.3 43.2 87.3
#> 42 42 44.6 14.3 1.4 16.1 0.3 43.2 87.3
#> 43 43 44.6 14.3 1.4 16.1 0.3 43.2 87.3
#> 44 44 44.6 14.3 1.4 16.1 0.3 43.2 87.3
#> 45 45 37.1 11.8 2.0 12.1 1.7 35.3 83.4
#> 46 46 37.1 11.8 2.0 12.1 1.7 35.3 83.4
#> 47 47 37.1 11.8 2.0 12.1 1.7 35.3 83.4
#> 48 48 37.1 11.8 2.0 12.1 1.7 35.3 83.4
#> 49 49 37.1 11.8 2.0 12.1 1.7 35.3 83.4
#> 50 50 26.9 9.5 1.0 11.2 0.0 25.3 75.1
#> 51 51 26.9 9.5 1.0 11.2 0.0 25.3 75.1
#> 52 52 26.9 9.5 1.0 11.2 0.0 25.3 75.1
#> 53 53 26.9 9.5 1.0 11.2 0.0 25.3 75.1
#> 54 54 26.9 9.5 1.0 11.2 0.0 25.3 75.1
#> 55 55 17.6 3.6 0.0 6.3 0.0 15.4 58.7
#> 56 56 17.6 3.6 0.0 6.3 0.0 15.4 58.7
#> 57 57 17.6 3.6 0.0 6.3 0.0 15.4 58.7
#> 58 58 17.6 3.6 0.0 6.3 0.0 15.4 58.7
#> 59 59 17.6 3.6 0.0 6.3 0.0 15.4 58.7
#> 60 60 9.9 1.8 0.5 2.8 0.3 8.9 50.3
#> 61 61 9.9 1.8 0.5 2.8 0.3 8.9 50.3
#> 62 62 9.9 1.8 0.5 2.8 0.3 8.9 50.3
#> 63 63 9.9 1.8 0.5 2.8 0.3 8.9 50.3
#> 64 64 9.9 1.8 0.5 2.8 0.3 8.9 50.3
#> 65 65 8.3 2.4 0.4 1.2 0.0 7.6 36.0
#> 66 66 8.3 2.4 0.4 1.2 0.0 7.6 36.0
#> 67 67 8.3 2.4 0.4 1.2 0.0 7.6 36.0
#> 68 68 8.3 2.4 0.4 1.2 0.0 7.6 36.0
#> 69 69 8.3 2.4 0.4 1.2 0.0 7.6 36.0
#> 70 70 3.6 0.0 0.0 1.0 0.0 2.5 21.4
#> 71 71 3.6 0.0 0.0 1.0 0.0 2.5 21.4
#> 72 72 3.6 0.0 0.0 1.0 0.0 2.5 21.4
#> 73 73 3.6 0.0 0.0 1.0 0.0 2.5 21.4
#> 74 74 3.6 0.0 0.0 1.0 0.0 2.5 21.4
#> 75 75 1.6 0.0 0.0 0.0 0.0 1.6 8.2
#> 76 76 1.6 0.0 0.0 0.0 0.0 1.6 8.2
#> 77 77 1.6 0.0 0.0 0.0 0.0 1.6 8.2
#> 78 78 1.6 0.0 0.0 0.0 0.0 1.6 8.2
#> 79 79 1.6 0.0 0.0 0.0 0.0 1.6 8.2
#> 80 80 0.7 0.7 0.0 0.7 0.0 0.7 10.6
#> 81 81 0.7 0.7 0.0 0.7 0.0 0.7 10.6
#> 82 82 0.7 0.7 0.0 0.7 0.0 0.7 10.6
#> 83 83 0.7 0.7 0.0 0.7 0.0 0.7 10.6
#> 84 84 0.7 0.7 0.0 0.7 0.0 0.7 10.6
#> 85 85 0.0 0.0 0.0 0.0 0.0 0.0 5.0
#> 86 86 0.0 0.0 0.0 0.0 0.0 0.0 5.0
#> 87 87 0.0 0.0 0.0 0.0 0.0 0.0 5.0
#> 88 88 0.0 0.0 0.0 0.0 0.0 0.0 5.0
#> 89 89 0.0 0.0 0.0 0.0 0.0 0.0 5.0
#> 90 90 0.0 0.0 0.0 0.0 0.0 0.0 2.2
#> 91 91 0.0 0.0 0.0 0.0 0.0 0.0 2.2
#> 92 92 0.0 0.0 0.0 0.0 0.0 0.0 2.2
#> 93 93 0.0 0.0 0.0 0.0 0.0 0.0 2.2
#> 94 94 0.0 0.0 0.0 0.0 0.0 0.0 2.2
#> 95 95 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 96 96 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 97 97 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 98 98 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 99 99 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 100 100 0.0 0.0 0.0 0.0 0.0 0.0 0.0
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiEGY2010[ppiEGY2010$score == ppiScore, ]
#> score nu100 nl100 nlFood extreme ppp125 ppp250 ppp375
#> 50 50 26.9 9.5 1 11.2 0 25.3 75.1
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiEGY2010, score == ppiScore)
#> score nu100 nl100 nlFood extreme ppp125 ppp250 ppp375
#> 50 50 26.9 9.5 1 11.2 0 25.3 75.1
# 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
ppiEGY2010[ppiEGY2010$score == ppiScore, "extreme"]
#> [1] 11.2