Poverty Probability Index (PPI) lookup table for Myanmar
ppiMMR2012
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)
# 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