Poverty Probability Index (PPI) lookup table for Peru
Format
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)
Examples
# 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