Poverty Probability Index (PPI) lookup table for Cambodia
Format
A data frame with 9 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
medianMedian poverty line
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
Examples
# Access Cambodia PPI table
ppiKHM2015_wb
#> score nl100 nl150 nl200 median ppp125 ppp200 ppp250 ppp500
#> 0 0 100.0 100.0 100.0 96.0 42.0 100.0 100.0 100.0
#> 1 1 100.0 100.0 100.0 96.0 42.0 100.0 100.0 100.0
#> 2 2 100.0 100.0 100.0 96.0 42.0 100.0 100.0 100.0
#> 3 3 100.0 100.0 100.0 96.0 42.0 100.0 100.0 100.0
#> 4 4 100.0 100.0 100.0 96.0 42.0 100.0 100.0 100.0
#> 5 5 94.9 100.0 100.0 84.9 42.0 95.6 95.9 100.0
#> 6 6 94.9 100.0 100.0 84.9 42.0 95.6 95.9 100.0
#> 7 7 94.9 100.0 100.0 84.9 42.0 95.6 95.9 100.0
#> 8 8 94.9 100.0 100.0 84.9 42.0 95.6 95.9 100.0
#> 9 9 94.9 100.0 100.0 84.9 42.0 95.6 95.9 100.0
#> 10 10 88.6 100.0 100.0 71.8 17.4 91.5 92.1 100.0
#> 11 11 88.6 100.0 100.0 71.8 17.4 91.5 92.1 100.0
#> 12 12 88.6 100.0 100.0 71.8 17.4 91.5 92.1 100.0
#> 13 13 88.6 100.0 100.0 71.8 17.4 91.5 92.1 100.0
#> 14 14 88.6 100.0 100.0 71.8 17.4 91.5 92.1 100.0
#> 15 15 73.8 97.1 100.0 41.4 10.1 77.5 92.1 100.0
#> 16 16 73.8 97.1 100.0 41.4 10.1 77.5 92.1 100.0
#> 17 17 73.8 97.1 100.0 41.4 10.1 77.5 92.1 100.0
#> 18 18 73.8 97.1 100.0 41.4 10.1 77.5 92.1 100.0
#> 19 19 73.8 97.1 100.0 41.4 10.1 77.5 92.1 100.0
#> 20 20 60.7 96.4 100.0 31.7 9.3 62.0 91.9 100.0
#> 21 21 60.7 96.4 100.0 31.7 9.3 62.0 91.9 100.0
#> 22 22 60.7 96.4 100.0 31.7 9.3 62.0 91.9 100.0
#> 23 23 60.7 96.4 100.0 31.7 9.3 62.0 91.9 100.0
#> 24 24 60.7 96.4 100.0 31.7 9.3 62.0 91.9 100.0
#> 25 25 46.6 93.3 97.5 23.3 7.5 52.5 79.4 99.5
#> 26 26 46.6 93.3 97.5 23.3 7.5 52.5 79.4 99.5
#> 27 27 46.6 93.3 97.5 23.3 7.5 52.5 79.4 99.5
#> 28 28 46.6 93.3 97.5 23.3 7.5 52.5 79.4 99.5
#> 29 29 46.6 93.3 97.5 23.3 7.5 52.5 79.4 99.5
#> 30 30 34.3 86.6 97.5 15.3 4.1 39.4 73.7 99.5
#> 31 31 34.3 86.6 97.5 15.3 4.1 39.4 73.7 99.5
#> 32 32 34.3 86.6 97.5 15.3 4.1 39.4 73.7 99.5
#> 33 33 34.3 86.6 97.5 15.3 4.1 39.4 73.7 99.5
#> 34 34 34.3 86.6 97.5 15.3 4.1 39.4 73.7 99.5
#> 35 35 20.2 74.6 96.5 6.0 0.4 24.6 55.0 99.5
#> 36 36 20.2 74.6 96.5 6.0 0.4 24.6 55.0 99.5
#> 37 37 20.2 74.6 96.5 6.0 0.4 24.6 55.0 99.5
#> 38 38 20.2 74.6 96.5 6.0 0.4 24.6 55.0 99.5
#> 39 39 20.2 74.6 96.5 6.0 0.4 24.6 55.0 99.5
#> 40 40 10.5 62.4 90.0 2.9 0.2 14.8 43.1 98.6
#> 41 41 10.5 62.4 90.0 2.9 0.2 14.8 43.1 98.6
#> 42 42 10.5 62.4 90.0 2.9 0.2 14.8 43.1 98.6
#> 43 43 10.5 62.4 90.0 2.9 0.2 14.8 43.1 98.6
#> 44 44 10.5 62.4 90.0 2.9 0.2 14.8 43.1 98.6
#> 45 45 5.5 42.5 76.8 0.8 0.1 8.4 25.2 93.1
#> 46 46 5.5 42.5 76.8 0.8 0.1 8.4 25.2 93.1
#> 47 47 5.5 42.5 76.8 0.8 0.1 8.4 25.2 93.1
#> 48 48 5.5 42.5 76.8 0.8 0.1 8.4 25.2 93.1
#> 49 49 5.5 42.5 76.8 0.8 0.1 8.4 25.2 93.1
#> 50 50 0.7 31.4 70.2 0.0 0.0 1.9 15.9 89.2
#> 51 51 0.7 31.4 70.2 0.0 0.0 1.9 15.9 89.2
#> 52 52 0.7 31.4 70.2 0.0 0.0 1.9 15.9 89.2
#> 53 53 0.7 31.4 70.2 0.0 0.0 1.9 15.9 89.2
#> 54 54 0.7 31.4 70.2 0.0 0.0 1.9 15.9 89.2
#> 55 55 0.2 15.1 45.4 0.0 0.0 1.0 5.3 72.2
#> 56 56 0.2 15.1 45.4 0.0 0.0 1.0 5.3 72.2
#> 57 57 0.2 15.1 45.4 0.0 0.0 1.0 5.3 72.2
#> 58 58 0.2 15.1 45.4 0.0 0.0 1.0 5.3 72.2
#> 59 59 0.2 15.1 45.4 0.0 0.0 1.0 5.3 72.2
#> 60 60 0.2 9.0 38.7 0.0 0.0 0.5 1.0 67.3
#> 61 61 0.2 9.0 38.7 0.0 0.0 0.5 1.0 67.3
#> 62 62 0.2 9.0 38.7 0.0 0.0 0.5 1.0 67.3
#> 63 63 0.2 9.0 38.7 0.0 0.0 0.5 1.0 67.3
#> 64 64 0.2 9.0 38.7 0.0 0.0 0.5 1.0 67.3
#> 65 65 0.0 2.1 14.7 0.0 0.0 0.0 0.6 49.8
#> 66 66 0.0 2.1 14.7 0.0 0.0 0.0 0.6 49.8
#> 67 67 0.0 2.1 14.7 0.0 0.0 0.0 0.6 49.8
#> 68 68 0.0 2.1 14.7 0.0 0.0 0.0 0.6 49.8
#> 69 69 0.0 2.1 14.7 0.0 0.0 0.0 0.6 49.8
#> 70 70 0.0 0.0 6.8 0.0 0.0 0.0 0.0 25.7
#> 71 71 0.0 0.0 6.8 0.0 0.0 0.0 0.0 25.7
#> 72 72 0.0 0.0 6.8 0.0 0.0 0.0 0.0 25.7
#> 73 73 0.0 0.0 6.8 0.0 0.0 0.0 0.0 25.7
#> 74 74 0.0 0.0 6.8 0.0 0.0 0.0 0.0 25.7
#> 75 75 0.0 0.0 5.6 0.0 0.0 0.0 0.0 19.6
#> 76 76 0.0 0.0 5.6 0.0 0.0 0.0 0.0 19.6
#> 77 77 0.0 0.0 5.6 0.0 0.0 0.0 0.0 19.6
#> 78 78 0.0 0.0 5.6 0.0 0.0 0.0 0.0 19.6
#> 79 79 0.0 0.0 5.6 0.0 0.0 0.0 0.0 19.6
#> 80 80 0.0 0.0 1.6 0.0 0.0 0.0 0.0 15.3
#> 81 81 0.0 0.0 1.6 0.0 0.0 0.0 0.0 15.3
#> 82 82 0.0 0.0 1.6 0.0 0.0 0.0 0.0 15.3
#> 83 83 0.0 0.0 1.6 0.0 0.0 0.0 0.0 15.3
#> 84 84 0.0 0.0 1.6 0.0 0.0 0.0 0.0 15.3
#> 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
ppiKHM2015_wb[ppiKHM2015_wb$score == ppiScore, ]
#> score nl100 nl150 nl200 median ppp125 ppp200 ppp250 ppp500
#> 50 50 0.7 31.4 70.2 0 0 1.9 15.9 89.2
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiKHM2015_wb, score == ppiScore)
#> score nl100 nl150 nl200 median ppp125 ppp200 ppp250 ppp500
#> 50 50 0.7 31.4 70.2 0 0 1.9 15.9 89.2
# 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
ppiKHM2015_wb[ppiKHM2015_wb$score == ppiScore, "nl100"]
#> [1] 0.7