Poverty Probability Index (PPI) lookup table for Peru
ppiPER2012
A data frame with 9 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
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 Peru PPI table ppiPER2012#> score nlFood nl100 nl150 nl200 extreme ppp125 ppp250 ppp375 #> 0 0 73.7 100.0 100.0 100.0 83.5 45.4 72.6 100.0 #> 1 1 73.7 100.0 100.0 100.0 83.5 45.4 72.6 100.0 #> 2 2 73.7 100.0 100.0 100.0 83.5 45.4 72.6 100.0 #> 3 3 73.7 100.0 100.0 100.0 83.5 45.4 72.6 100.0 #> 4 4 73.7 100.0 100.0 100.0 83.5 45.4 72.6 100.0 #> 5 5 70.6 98.5 99.5 100.0 78.8 12.3 66.4 93.7 #> 6 6 70.6 98.5 99.5 100.0 78.8 12.3 66.4 93.7 #> 7 7 70.6 98.5 99.5 100.0 78.8 12.3 66.4 93.7 #> 8 8 70.6 98.5 99.5 100.0 78.8 12.3 66.4 93.7 #> 9 9 70.6 98.5 99.5 100.0 78.8 12.3 66.4 93.7 #> 10 10 57.5 95.8 99.4 100.0 72.2 4.7 47.4 90.1 #> 11 11 57.5 95.8 99.4 100.0 72.2 4.7 47.4 90.1 #> 12 12 57.5 95.8 99.4 100.0 72.2 4.7 47.4 90.1 #> 13 13 57.5 95.8 99.4 100.0 72.2 4.7 47.4 90.1 #> 14 14 57.5 95.8 99.4 100.0 72.2 4.7 47.4 90.1 #> 15 15 43.3 91.7 99.4 100.0 58.2 2.2 40.3 80.5 #> 16 16 43.3 91.7 99.4 100.0 58.2 2.2 40.3 80.5 #> 17 17 43.3 91.7 99.4 100.0 58.2 2.2 40.3 80.5 #> 18 18 43.3 91.7 99.4 100.0 58.2 2.2 40.3 80.5 #> 19 19 43.3 91.7 99.4 100.0 58.2 2.2 40.3 80.5 #> 20 20 39.7 84.5 96.7 99.6 53.5 2.1 35.2 72.6 #> 21 21 39.7 84.5 96.7 99.6 53.5 2.1 35.2 72.6 #> 22 22 39.7 84.5 96.7 99.6 53.5 2.1 35.2 72.6 #> 23 23 39.7 84.5 96.7 99.6 53.5 2.1 35.2 72.6 #> 24 24 39.7 84.5 96.7 99.6 53.5 2.1 35.2 72.6 #> 25 25 27.5 77.0 94.8 99.3 46.1 1.9 25.1 61.5 #> 26 26 27.5 77.0 94.8 99.3 46.1 1.9 25.1 61.5 #> 27 27 27.5 77.0 94.8 99.3 46.1 1.9 25.1 61.5 #> 28 28 27.5 77.0 94.8 99.3 46.1 1.9 25.1 61.5 #> 29 29 27.5 77.0 94.8 99.3 46.1 1.9 25.1 61.5 #> 30 30 17.8 66.9 90.7 98.1 32.3 1.0 16.7 48.8 #> 31 31 17.8 66.9 90.7 98.1 32.3 1.0 16.7 48.8 #> 32 32 17.8 66.9 90.7 98.1 32.3 1.0 16.7 48.8 #> 33 33 17.8 66.9 90.7 98.1 32.3 1.0 16.7 48.8 #> 34 34 17.8 66.9 90.7 98.1 32.3 1.0 16.7 48.8 #> 35 35 9.5 52.0 85.3 95.4 22.4 0.4 8.9 34.4 #> 36 36 9.5 52.0 85.3 95.4 22.4 0.4 8.9 34.4 #> 37 37 9.5 52.0 85.3 95.4 22.4 0.4 8.9 34.4 #> 38 38 9.5 52.0 85.3 95.4 22.4 0.4 8.9 34.4 #> 39 39 9.5 52.0 85.3 95.4 22.4 0.4 8.9 34.4 #> 40 40 4.8 38.9 76.8 93.6 18.4 0.3 4.8 23.6 #> 41 41 4.8 38.9 76.8 93.6 18.4 0.3 4.8 23.6 #> 42 42 4.8 38.9 76.8 93.6 18.4 0.3 4.8 23.6 #> 43 43 4.8 38.9 76.8 93.6 18.4 0.3 4.8 23.6 #> 44 44 4.8 38.9 76.8 93.6 18.4 0.3 4.8 23.6 #> 45 45 1.4 26.5 63.9 83.9 8.0 0.1 1.9 11.8 #> 46 46 1.4 26.5 63.9 83.9 8.0 0.1 1.9 11.8 #> 47 47 1.4 26.5 63.9 83.9 8.0 0.1 1.9 11.8 #> 48 48 1.4 26.5 63.9 83.9 8.0 0.1 1.9 11.8 #> 49 49 1.4 26.5 63.9 83.9 8.0 0.1 1.9 11.8 #> 50 50 0.6 16.8 53.6 77.2 4.3 0.0 0.7 5.2 #> 51 51 0.6 16.8 53.6 77.2 4.3 0.0 0.7 5.2 #> 52 52 0.6 16.8 53.6 77.2 4.3 0.0 0.7 5.2 #> 53 53 0.6 16.8 53.6 77.2 4.3 0.0 0.7 5.2 #> 54 54 0.6 16.8 53.6 77.2 4.3 0.0 0.7 5.2 #> 55 55 0.0 8.1 38.5 67.9 2.3 0.0 0.0 2.3 #> 56 56 0.0 8.1 38.5 67.9 2.3 0.0 0.0 2.3 #> 57 57 0.0 8.1 38.5 67.9 2.3 0.0 0.0 2.3 #> 58 58 0.0 8.1 38.5 67.9 2.3 0.0 0.0 2.3 #> 59 59 0.0 8.1 38.5 67.9 2.3 0.0 0.0 2.3 #> 60 60 0.0 3.6 25.8 53.3 1.0 0.0 0.0 1.2 #> 61 61 0.0 3.6 25.8 53.3 1.0 0.0 0.0 1.2 #> 62 62 0.0 3.6 25.8 53.3 1.0 0.0 0.0 1.2 #> 63 63 0.0 3.6 25.8 53.3 1.0 0.0 0.0 1.2 #> 64 64 0.0 3.6 25.8 53.3 1.0 0.0 0.0 1.2 #> 65 65 0.0 1.5 14.5 38.3 0.3 0.0 0.0 0.3 #> 66 66 0.0 1.5 14.5 38.3 0.3 0.0 0.0 0.3 #> 67 67 0.0 1.5 14.5 38.3 0.3 0.0 0.0 0.3 #> 68 68 0.0 1.5 14.5 38.3 0.3 0.0 0.0 0.3 #> 69 69 0.0 1.5 14.5 38.3 0.3 0.0 0.0 0.3 #> 70 70 0.0 0.7 6.5 20.2 0.2 0.0 0.0 0.0 #> 71 71 0.0 0.7 6.5 20.2 0.2 0.0 0.0 0.0 #> 72 72 0.0 0.7 6.5 20.2 0.2 0.0 0.0 0.0 #> 73 73 0.0 0.7 6.5 20.2 0.2 0.0 0.0 0.0 #> 74 74 0.0 0.7 6.5 20.2 0.2 0.0 0.0 0.0 #> 75 75 0.0 0.0 2.1 8.3 0.0 0.0 0.0 0.0 #> 76 76 0.0 0.0 2.1 8.3 0.0 0.0 0.0 0.0 #> 77 77 0.0 0.0 2.1 8.3 0.0 0.0 0.0 0.0 #> 78 78 0.0 0.0 2.1 8.3 0.0 0.0 0.0 0.0 #> 79 79 0.0 0.0 2.1 8.3 0.0 0.0 0.0 0.0 #> 80 80 0.0 0.0 0.0 4.5 0.0 0.0 0.0 0.0 #> 81 81 0.0 0.0 0.0 4.5 0.0 0.0 0.0 0.0 #> 82 82 0.0 0.0 0.0 4.5 0.0 0.0 0.0 0.0 #> 83 83 0.0 0.0 0.0 4.5 0.0 0.0 0.0 0.0 #> 84 84 0.0 0.0 0.0 4.5 0.0 0.0 0.0 0.0 #> 85 85 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 86 86 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 87 87 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 88 88 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 89 89 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 90 90 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 91 91 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 92 92 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 93 93 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 94 94 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 95 95 0.0 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 0.0 #> 97 97 0.0 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 0.0 #> 99 99 0.0 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 0.0# Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiPER2012[ppiPER2012$score == ppiScore, ]#> score nlFood nl100 nl150 nl200 extreme ppp125 ppp250 ppp375 #> 50 50 0.6 16.8 53.6 77.2 4.3 0 0.7 5.2# Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiPER2012, score == ppiScore)#> score nlFood nl100 nl150 nl200 extreme ppp125 ppp250 ppp375 #> 50 50 0.6 16.8 53.6 77.2 4.3 0 0.7 5.2# 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 definition ppiScore <- 50 ppiPER2012[ppiPER2012$score == ppiScore, "nl100"]#> [1] 16.8