Poverty Probability Index (PPI) lookup table for Egypt
ppiEGY2010
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)
# 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