Poverty Probability Index (PPI) lookup table for Cambodia
ppiKHM2015_wb
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)
# 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