Poverty Probability Index (PPI) lookup table for Sri Lanka
Format
A data frame with 16 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
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)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile50Below 50th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Examples
# Access Sri Lanka PPI table
ppiLKA2016
#> score nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp190 ppp310
#> 0 0 78.0 95.3 100.0 61.3 61.7 94.8 100.0 100.0 43.6 85.3
#> 1 1 78.0 95.3 100.0 61.3 61.7 94.8 100.0 100.0 43.6 85.3
#> 2 2 78.0 95.3 100.0 61.3 61.7 94.8 100.0 100.0 43.6 85.3
#> 3 3 78.0 95.3 100.0 61.3 61.7 94.8 100.0 100.0 43.6 85.3
#> 4 4 78.0 95.3 100.0 61.3 61.7 94.8 100.0 100.0 43.6 85.3
#> 5 5 57.8 91.3 99.6 35.3 43.2 91.1 97.9 100.0 25.9 76.6
#> 6 6 57.8 91.3 99.6 35.3 43.2 91.1 97.9 100.0 25.9 76.6
#> 7 7 57.8 91.3 99.6 35.3 43.2 91.1 97.9 100.0 25.9 76.6
#> 8 8 57.8 91.3 99.6 35.3 43.2 91.1 97.9 100.0 25.9 76.6
#> 9 9 57.8 91.3 99.6 35.3 43.2 91.1 97.9 100.0 25.9 76.6
#> 10 10 46.4 84.4 97.7 25.3 35.3 83.0 93.8 100.0 15.2 66.7
#> 11 11 46.4 84.4 97.7 25.3 35.3 83.0 93.8 100.0 15.2 66.7
#> 12 12 46.4 84.4 97.7 25.3 35.3 83.0 93.8 100.0 15.2 66.7
#> 13 13 46.4 84.4 97.7 25.3 35.3 83.0 93.8 100.0 15.2 66.7
#> 14 14 46.4 84.4 97.7 25.3 35.3 83.0 93.8 100.0 15.2 66.7
#> 15 15 30.4 71.9 92.7 17.6 22.5 69.9 89.1 99.0 12.0 56.1
#> 16 16 30.4 71.9 92.7 17.6 22.5 69.9 89.1 99.0 12.0 56.1
#> 17 17 30.4 71.9 92.7 17.6 22.5 69.9 89.1 99.0 12.0 56.1
#> 18 18 30.4 71.9 92.7 17.6 22.5 69.9 89.1 99.0 12.0 56.1
#> 19 19 30.4 71.9 92.7 17.6 22.5 69.9 89.1 99.0 12.0 56.1
#> 20 20 19.3 64.3 87.9 10.2 14.1 61.1 81.6 98.8 6.0 44.9
#> 21 21 19.3 64.3 87.9 10.2 14.1 61.1 81.6 98.8 6.0 44.9
#> 22 22 19.3 64.3 87.9 10.2 14.1 61.1 81.6 98.8 6.0 44.9
#> 23 23 19.3 64.3 87.9 10.2 14.1 61.1 81.6 98.8 6.0 44.9
#> 24 24 19.3 64.3 87.9 10.2 14.1 61.1 81.6 98.8 6.0 44.9
#> 25 25 11.5 48.7 79.1 5.3 7.3 46.9 71.5 98.1 1.5 29.0
#> 26 26 11.5 48.7 79.1 5.3 7.3 46.9 71.5 98.1 1.5 29.0
#> 27 27 11.5 48.7 79.1 5.3 7.3 46.9 71.5 98.1 1.5 29.0
#> 28 28 11.5 48.7 79.1 5.3 7.3 46.9 71.5 98.1 1.5 29.0
#> 29 29 11.5 48.7 79.1 5.3 7.3 46.9 71.5 98.1 1.5 29.0
#> 30 30 7.3 36.4 68.5 3.4 4.5 33.9 58.9 97.0 1.4 18.9
#> 31 31 7.3 36.4 68.5 3.4 4.5 33.9 58.9 97.0 1.4 18.9
#> 32 32 7.3 36.4 68.5 3.4 4.5 33.9 58.9 97.0 1.4 18.9
#> 33 33 7.3 36.4 68.5 3.4 4.5 33.9 58.9 97.0 1.4 18.9
#> 34 34 7.3 36.4 68.5 3.4 4.5 33.9 58.9 97.0 1.4 18.9
#> 35 35 4.9 27.9 56.5 2.4 3.2 26.4 48.0 95.6 1.0 14.0
#> 36 36 4.9 27.9 56.5 2.4 3.2 26.4 48.0 95.6 1.0 14.0
#> 37 37 4.9 27.9 56.5 2.4 3.2 26.4 48.0 95.6 1.0 14.0
#> 38 38 4.9 27.9 56.5 2.4 3.2 26.4 48.0 95.6 1.0 14.0
#> 39 39 4.9 27.9 56.5 2.4 3.2 26.4 48.0 95.6 1.0 14.0
#> 40 40 2.4 18.0 45.6 1.0 1.2 16.1 37.9 90.8 0.3 7.7
#> 41 41 2.4 18.0 45.6 1.0 1.2 16.1 37.9 90.8 0.3 7.7
#> 42 42 2.4 18.0 45.6 1.0 1.2 16.1 37.9 90.8 0.3 7.7
#> 43 43 2.4 18.0 45.6 1.0 1.2 16.1 37.9 90.8 0.3 7.7
#> 44 44 2.4 18.0 45.6 1.0 1.2 16.1 37.9 90.8 0.3 7.7
#> 45 45 0.6 9.0 34.2 0.3 0.5 8.1 24.5 85.2 0.1 3.3
#> 46 46 0.6 9.0 34.2 0.3 0.5 8.1 24.5 85.2 0.1 3.3
#> 47 47 0.6 9.0 34.2 0.3 0.5 8.1 24.5 85.2 0.1 3.3
#> 48 48 0.6 9.0 34.2 0.3 0.5 8.1 24.5 85.2 0.1 3.3
#> 49 49 0.6 9.0 34.2 0.3 0.5 8.1 24.5 85.2 0.1 3.3
#> 50 50 0.2 5.5 21.5 0.0 0.1 4.3 14.5 76.8 0.0 1.6
#> 51 51 0.2 5.5 21.5 0.0 0.1 4.3 14.5 76.8 0.0 1.6
#> 52 52 0.2 5.5 21.5 0.0 0.1 4.3 14.5 76.8 0.0 1.6
#> 53 53 0.2 5.5 21.5 0.0 0.1 4.3 14.5 76.8 0.0 1.6
#> 54 54 0.2 5.5 21.5 0.0 0.1 4.3 14.5 76.8 0.0 1.6
#> 55 55 0.0 2.8 11.9 0.0 0.0 2.4 8.0 63.8 0.0 0.3
#> 56 56 0.0 2.8 11.9 0.0 0.0 2.4 8.0 63.8 0.0 0.3
#> 57 57 0.0 2.8 11.9 0.0 0.0 2.4 8.0 63.8 0.0 0.3
#> 58 58 0.0 2.8 11.9 0.0 0.0 2.4 8.0 63.8 0.0 0.3
#> 59 59 0.0 2.8 11.9 0.0 0.0 2.4 8.0 63.8 0.0 0.3
#> 60 60 0.0 1.1 6.8 0.0 0.0 0.9 4.2 50.5 0.0 0.0
#> 61 61 0.0 1.1 6.8 0.0 0.0 0.9 4.2 50.5 0.0 0.0
#> 62 62 0.0 1.1 6.8 0.0 0.0 0.9 4.2 50.5 0.0 0.0
#> 63 63 0.0 1.1 6.8 0.0 0.0 0.9 4.2 50.5 0.0 0.0
#> 64 64 0.0 1.1 6.8 0.0 0.0 0.9 4.2 50.5 0.0 0.0
#> 65 65 0.0 0.3 3.8 0.0 0.0 0.3 2.8 40.4 0.0 0.0
#> 66 66 0.0 0.3 3.8 0.0 0.0 0.3 2.8 40.4 0.0 0.0
#> 67 67 0.0 0.3 3.8 0.0 0.0 0.3 2.8 40.4 0.0 0.0
#> 68 68 0.0 0.3 3.8 0.0 0.0 0.3 2.8 40.4 0.0 0.0
#> 69 69 0.0 0.3 3.8 0.0 0.0 0.3 2.8 40.4 0.0 0.0
#> 70 70 0.0 0.2 1.9 0.0 0.0 0.2 0.8 31.7 0.0 0.0
#> 71 71 0.0 0.2 1.9 0.0 0.0 0.2 0.8 31.7 0.0 0.0
#> 72 72 0.0 0.2 1.9 0.0 0.0 0.2 0.8 31.7 0.0 0.0
#> 73 73 0.0 0.2 1.9 0.0 0.0 0.2 0.8 31.7 0.0 0.0
#> 74 74 0.0 0.2 1.9 0.0 0.0 0.2 0.8 31.7 0.0 0.0
#> 75 75 0.0 0.0 0.4 0.0 0.0 0.0 0.2 17.8 0.0 0.0
#> 76 76 0.0 0.0 0.4 0.0 0.0 0.0 0.2 17.8 0.0 0.0
#> 77 77 0.0 0.0 0.4 0.0 0.0 0.0 0.2 17.8 0.0 0.0
#> 78 78 0.0 0.0 0.4 0.0 0.0 0.0 0.2 17.8 0.0 0.0
#> 79 79 0.0 0.0 0.4 0.0 0.0 0.0 0.2 17.8 0.0 0.0
#> 80 80 0.0 0.0 0.3 0.0 0.0 0.0 0.2 6.0 0.0 0.0
#> 81 81 0.0 0.0 0.3 0.0 0.0 0.0 0.2 6.0 0.0 0.0
#> 82 82 0.0 0.0 0.3 0.0 0.0 0.0 0.2 6.0 0.0 0.0
#> 83 83 0.0 0.0 0.3 0.0 0.0 0.0 0.2 6.0 0.0 0.0
#> 84 84 0.0 0.0 0.3 0.0 0.0 0.0 0.2 6.0 0.0 0.0
#> 85 85 0.0 0.0 0.1 0.0 0.0 0.0 0.0 3.7 0.0 0.0
#> 86 86 0.0 0.0 0.1 0.0 0.0 0.0 0.0 3.7 0.0 0.0
#> 87 87 0.0 0.0 0.1 0.0 0.0 0.0 0.0 3.7 0.0 0.0
#> 88 88 0.0 0.0 0.1 0.0 0.0 0.0 0.0 3.7 0.0 0.0
#> 89 89 0.0 0.0 0.1 0.0 0.0 0.0 0.0 3.7 0.0 0.0
#> 90 90 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.7 0.0 0.0
#> 91 91 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.7 0.0 0.0
#> 92 92 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.7 0.0 0.0
#> 93 93 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.7 0.0 0.0
#> 94 94 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.7 0.0 0.0
#> 95 95 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.2 0.0 0.0
#> 96 96 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.2 0.0 0.0
#> 97 97 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.2 0.0 0.0
#> 98 98 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.2 0.0 0.0
#> 99 99 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.2 0.0 0.0
#> 100 100 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.2 0.0 0.0
#> percentile20 percentile40 percentile50 percentile60 percentile80
#> 0 91.5 100.0 100.0 100.0 100.0
#> 1 91.5 100.0 100.0 100.0 100.0
#> 2 91.5 100.0 100.0 100.0 100.0
#> 3 91.5 100.0 100.0 100.0 100.0
#> 4 91.5 100.0 100.0 100.0 100.0
#> 5 85.5 99.4 99.7 100.0 100.0
#> 6 85.5 99.4 99.7 100.0 100.0
#> 7 85.5 99.4 99.7 100.0 100.0
#> 8 85.5 99.4 99.7 100.0 100.0
#> 9 85.5 99.4 99.7 100.0 100.0
#> 10 75.6 95.3 98.3 99.8 100.0
#> 11 75.6 95.3 98.3 99.8 100.0
#> 12 75.6 95.3 98.3 99.8 100.0
#> 13 75.6 95.3 98.3 99.8 100.0
#> 14 75.6 95.3 98.3 99.8 100.0
#> 15 63.8 90.6 94.5 96.5 99.1
#> 16 63.8 90.6 94.5 96.5 99.1
#> 17 63.8 90.6 94.5 96.5 99.1
#> 18 63.8 90.6 94.5 96.5 99.1
#> 19 63.8 90.6 94.5 96.5 99.1
#> 20 57.1 83.6 90.9 95.9 98.9
#> 21 57.1 83.6 90.9 95.9 98.9
#> 22 57.1 83.6 90.9 95.9 98.9
#> 23 57.1 83.6 90.9 95.9 98.9
#> 24 57.1 83.6 90.9 95.9 98.9
#> 25 41.8 74.3 84.2 91.0 98.4
#> 26 41.8 74.3 84.2 91.0 98.4
#> 27 41.8 74.3 84.2 91.0 98.4
#> 28 41.8 74.3 84.2 91.0 98.4
#> 29 41.8 74.3 84.2 91.0 98.4
#> 30 27.4 62.0 77.1 87.2 97.5
#> 31 27.4 62.0 77.1 87.2 97.5
#> 32 27.4 62.0 77.1 87.2 97.5
#> 33 27.4 62.0 77.1 87.2 97.5
#> 34 27.4 62.0 77.1 87.2 97.5
#> 35 21.2 50.8 64.9 79.8 96.0
#> 36 21.2 50.8 64.9 79.8 96.0
#> 37 21.2 50.8 64.9 79.8 96.0
#> 38 21.2 50.8 64.9 79.8 96.0
#> 39 21.2 50.8 64.9 79.8 96.0
#> 40 12.7 39.5 53.9 67.8 91.5
#> 41 12.7 39.5 53.9 67.8 91.5
#> 42 12.7 39.5 53.9 67.8 91.5
#> 43 12.7 39.5 53.9 67.8 91.5
#> 44 12.7 39.5 53.9 67.8 91.5
#> 45 6.6 27.6 42.5 57.2 86.1
#> 46 6.6 27.6 42.5 57.2 86.1
#> 47 6.6 27.6 42.5 57.2 86.1
#> 48 6.6 27.6 42.5 57.2 86.1
#> 49 6.6 27.6 42.5 57.2 86.1
#> 50 3.7 16.6 28.6 42.6 77.9
#> 51 3.7 16.6 28.6 42.6 77.9
#> 52 3.7 16.6 28.6 42.6 77.9
#> 53 3.7 16.6 28.6 42.6 77.9
#> 54 3.7 16.6 28.6 42.6 77.9
#> 55 1.6 8.5 17.2 29.0 65.4
#> 56 1.6 8.5 17.2 29.0 65.4
#> 57 1.6 8.5 17.2 29.0 65.4
#> 58 1.6 8.5 17.2 29.0 65.4
#> 59 1.6 8.5 17.2 29.0 65.4
#> 60 0.2 4.3 10.5 20.3 53.7
#> 61 0.2 4.3 10.5 20.3 53.7
#> 62 0.2 4.3 10.5 20.3 53.7
#> 63 0.2 4.3 10.5 20.3 53.7
#> 64 0.2 4.3 10.5 20.3 53.7
#> 65 0.0 2.5 5.2 11.2 42.3
#> 66 0.0 2.5 5.2 11.2 42.3
#> 67 0.0 2.5 5.2 11.2 42.3
#> 68 0.0 2.5 5.2 11.2 42.3
#> 69 0.0 2.5 5.2 11.2 42.3
#> 70 0.0 1.2 3.1 8.5 34.0
#> 71 0.0 1.2 3.1 8.5 34.0
#> 72 0.0 1.2 3.1 8.5 34.0
#> 73 0.0 1.2 3.1 8.5 34.0
#> 74 0.0 1.2 3.1 8.5 34.0
#> 75 0.0 0.4 0.4 3.6 18.7
#> 76 0.0 0.4 0.4 3.6 18.7
#> 77 0.0 0.4 0.4 3.6 18.7
#> 78 0.0 0.4 0.4 3.6 18.7
#> 79 0.0 0.4 0.4 3.6 18.7
#> 80 0.0 0.0 0.3 1.1 6.2
#> 81 0.0 0.0 0.3 1.1 6.2
#> 82 0.0 0.0 0.3 1.1 6.2
#> 83 0.0 0.0 0.3 1.1 6.2
#> 84 0.0 0.0 0.3 1.1 6.2
#> 85 0.0 0.0 0.1 0.1 3.3
#> 86 0.0 0.0 0.1 0.1 3.3
#> 87 0.0 0.0 0.1 0.1 3.3
#> 88 0.0 0.0 0.1 0.1 3.3
#> 89 0.0 0.0 0.1 0.1 3.3
#> 90 0.0 0.0 0.0 0.0 0.9
#> 91 0.0 0.0 0.0 0.0 0.9
#> 92 0.0 0.0 0.0 0.0 0.9
#> 93 0.0 0.0 0.0 0.0 0.9
#> 94 0.0 0.0 0.0 0.0 0.9
#> 95 0.0 0.0 0.0 0.0 0.4
#> 96 0.0 0.0 0.0 0.0 0.4
#> 97 0.0 0.0 0.0 0.0 0.4
#> 98 0.0 0.0 0.0 0.0 0.4
#> 99 0.0 0.0 0.0 0.0 0.4
#> 100 0.0 0.0 0.0 0.0 0.4
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiLKA2016[ppiLKA2016$score == ppiScore, ]
#> score nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp190 ppp310
#> 50 50 0.2 5.5 21.5 0 0.1 4.3 14.5 76.8 0 1.6
#> percentile20 percentile40 percentile50 percentile60 percentile80
#> 50 3.7 16.6 28.6 42.6 77.9
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiLKA2016, score == ppiScore)
#> score nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp190 ppp310
#> 50 50 0.2 5.5 21.5 0 0.1 4.3 14.5 76.8 0 1.6
#> percentile20 percentile40 percentile50 percentile60 percentile80
#> 50 3.7 16.6 28.6 42.6 77.9
# 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
ppiLKA2016[ppiLKA2016$score == ppiScore, "nl100"]
#> [1] 0.2