Poverty Probability Index (PPI) lookup table for Myanmar
Format
A data frame with 8 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)
Examples
# Access Myanmar PPI table
ppiMMR2012
#> score nlFood nl100 nl150 nl200 extreme ppp125 ppp250
#> 0 0 30.0 83.4 100.0 100.0 71.1 95.2 100.0
#> 1 1 30.0 83.4 100.0 100.0 71.1 95.2 100.0
#> 2 2 30.0 83.4 100.0 100.0 71.1 95.2 100.0
#> 3 3 30.0 83.4 100.0 100.0 71.1 95.2 100.0
#> 4 4 30.0 83.4 100.0 100.0 71.1 95.2 100.0
#> 5 5 30.0 76.1 100.0 100.0 51.7 87.9 100.0
#> 6 6 30.0 76.1 100.0 100.0 51.7 87.9 100.0
#> 7 7 30.0 76.1 100.0 100.0 51.7 87.9 100.0
#> 8 8 30.0 76.1 100.0 100.0 51.7 87.9 100.0
#> 9 9 30.0 76.1 100.0 100.0 51.7 87.9 100.0
#> 10 10 25.4 68.6 96.8 99.6 44.1 84.1 99.8
#> 11 11 25.4 68.6 96.8 99.6 44.1 84.1 99.8
#> 12 12 25.4 68.6 96.8 99.6 44.1 84.1 99.8
#> 13 13 25.4 68.6 96.8 99.6 44.1 84.1 99.8
#> 14 14 25.4 68.6 96.8 99.6 44.1 84.1 99.8
#> 15 15 12.2 60.4 95.7 99.4 33.4 74.6 99.8
#> 16 16 12.2 60.4 95.7 99.4 33.4 74.6 99.8
#> 17 17 12.2 60.4 95.7 99.4 33.4 74.6 99.8
#> 18 18 12.2 60.4 95.7 99.4 33.4 74.6 99.8
#> 19 19 12.2 60.4 95.7 99.4 33.4 74.6 99.8
#> 20 20 9.1 48.8 93.5 99.4 24.5 61.1 99.8
#> 21 21 9.1 48.8 93.5 99.4 24.5 61.1 99.8
#> 22 22 9.1 48.8 93.5 99.4 24.5 61.1 99.8
#> 23 23 9.1 48.8 93.5 99.4 24.5 61.1 99.8
#> 24 24 9.1 48.8 93.5 99.4 24.5 61.1 99.8
#> 25 25 6.8 41.6 92.4 99.3 18.2 49.7 99.7
#> 26 26 6.8 41.6 92.4 99.3 18.2 49.7 99.7
#> 27 27 6.8 41.6 92.4 99.3 18.2 49.7 99.7
#> 28 28 6.8 41.6 92.4 99.3 18.2 49.7 99.7
#> 29 29 6.8 41.6 92.4 99.3 18.2 49.7 99.7
#> 30 30 4.4 29.5 88.4 99.2 13.0 35.1 99.1
#> 31 31 4.4 29.5 88.4 99.2 13.0 35.1 99.1
#> 32 32 4.4 29.5 88.4 99.2 13.0 35.1 99.1
#> 33 33 4.4 29.5 88.4 99.2 13.0 35.1 99.1
#> 34 34 4.4 29.5 88.4 99.2 13.0 35.1 99.1
#> 35 35 3.2 23.3 84.7 98.2 10.7 27.2 97.5
#> 36 36 3.2 23.3 84.7 98.2 10.7 27.2 97.5
#> 37 37 3.2 23.3 84.7 98.2 10.7 27.2 97.5
#> 38 38 3.2 23.3 84.7 98.2 10.7 27.2 97.5
#> 39 39 3.2 23.3 84.7 98.2 10.7 27.2 97.5
#> 40 40 1.0 15.0 70.5 95.4 5.5 16.3 93.8
#> 41 41 1.0 15.0 70.5 95.4 5.5 16.3 93.8
#> 42 42 1.0 15.0 70.5 95.4 5.5 16.3 93.8
#> 43 43 1.0 15.0 70.5 95.4 5.5 16.3 93.8
#> 44 44 1.0 15.0 70.5 95.4 5.5 16.3 93.8
#> 45 45 0.7 10.6 62.9 92.4 3.6 9.7 89.2
#> 46 46 0.7 10.6 62.9 92.4 3.6 9.7 89.2
#> 47 47 0.7 10.6 62.9 92.4 3.6 9.7 89.2
#> 48 48 0.7 10.6 62.9 92.4 3.6 9.7 89.2
#> 49 49 0.7 10.6 62.9 92.4 3.6 9.7 89.2
#> 50 50 0.2 7.4 55.9 88.4 2.0 5.2 85.6
#> 51 51 0.2 7.4 55.9 88.4 2.0 5.2 85.6
#> 52 52 0.2 7.4 55.9 88.4 2.0 5.2 85.6
#> 53 53 0.2 7.4 55.9 88.4 2.0 5.2 85.6
#> 54 54 0.2 7.4 55.9 88.4 2.0 5.2 85.6
#> 55 55 0.0 3.5 41.0 80.4 1.2 4.0 73.3
#> 56 56 0.0 3.5 41.0 80.4 1.2 4.0 73.3
#> 57 57 0.0 3.5 41.0 80.4 1.2 4.0 73.3
#> 58 58 0.0 3.5 41.0 80.4 1.2 4.0 73.3
#> 59 59 0.0 3.5 41.0 80.4 1.2 4.0 73.3
#> 60 60 0.0 1.2 28.8 69.5 0.4 0.8 61.4
#> 61 61 0.0 1.2 28.8 69.5 0.4 0.8 61.4
#> 62 62 0.0 1.2 28.8 69.5 0.4 0.8 61.4
#> 63 63 0.0 1.2 28.8 69.5 0.4 0.8 61.4
#> 64 64 0.0 1.2 28.8 69.5 0.4 0.8 61.4
#> 65 65 0.0 1.0 22.7 57.6 0.0 0.6 49.5
#> 66 66 0.0 1.0 22.7 57.6 0.0 0.6 49.5
#> 67 67 0.0 1.0 22.7 57.6 0.0 0.6 49.5
#> 68 68 0.0 1.0 22.7 57.6 0.0 0.6 49.5
#> 69 69 0.0 1.0 22.7 57.6 0.0 0.6 49.5
#> 70 70 0.0 0.3 14.9 49.1 0.0 0.2 37.5
#> 71 71 0.0 0.3 14.9 49.1 0.0 0.2 37.5
#> 72 72 0.0 0.3 14.9 49.1 0.0 0.2 37.5
#> 73 73 0.0 0.3 14.9 49.1 0.0 0.2 37.5
#> 74 74 0.0 0.3 14.9 49.1 0.0 0.2 37.5
#> 75 75 0.0 0.0 9.3 47.8 0.0 0.0 27.3
#> 76 76 0.0 0.0 9.3 47.8 0.0 0.0 27.3
#> 77 77 0.0 0.0 9.3 47.8 0.0 0.0 27.3
#> 78 78 0.0 0.0 9.3 47.8 0.0 0.0 27.3
#> 79 79 0.0 0.0 9.3 47.8 0.0 0.0 27.3
#> 80 80 0.0 0.0 4.3 44.6 0.0 0.0 18.6
#> 81 81 0.0 0.0 4.3 44.6 0.0 0.0 18.6
#> 82 82 0.0 0.0 4.3 44.6 0.0 0.0 18.6
#> 83 83 0.0 0.0 4.3 44.6 0.0 0.0 18.6
#> 84 84 0.0 0.0 4.3 44.6 0.0 0.0 18.6
#> 85 85 0.0 0.0 3.9 31.9 0.0 0.0 12.1
#> 86 86 0.0 0.0 3.9 31.9 0.0 0.0 12.1
#> 87 87 0.0 0.0 3.9 31.9 0.0 0.0 12.1
#> 88 88 0.0 0.0 3.9 31.9 0.0 0.0 12.1
#> 89 89 0.0 0.0 3.9 31.9 0.0 0.0 12.1
#> 90 90 0.0 0.0 0.0 31.9 0.0 0.0 0.0
#> 91 91 0.0 0.0 0.0 31.9 0.0 0.0 0.0
#> 92 92 0.0 0.0 0.0 31.9 0.0 0.0 0.0
#> 93 93 0.0 0.0 0.0 31.9 0.0 0.0 0.0
#> 94 94 0.0 0.0 0.0 31.9 0.0 0.0 0.0
#> 95 95 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
#> 97 97 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
#> 99 99 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
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiMMR2012[ppiMMR2012$score == ppiScore, ]
#> score nlFood nl100 nl150 nl200 extreme ppp125 ppp250
#> 50 50 0.2 7.4 55.9 88.4 2 5.2 85.6
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiMMR2012, score == ppiScore)
#> score nlFood nl100 nl150 nl200 extreme ppp125 ppp250
#> 50 50 0.2 7.4 55.9 88.4 2 5.2 85.6
# 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
ppiMMR2012[ppiMMR2012$score == ppiScore, "nl100"]
#> [1] 7.4