Poverty Probability Index (PPI) lookup table for Yemen
Format
A data frame with 8 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp300Below $3.00 per day purchasing power parity (2005)
ppp400Below $4.00 per day purchasing power parity (2005)
Examples
# Access Yemen PPI table
ppiYEM2009
#> score nl100 nlFood extreme ppp125 ppp250 ppp300 ppp400
#> 0 0 86.4 44.0 47.4 39.8 92.2 92.2 100.0
#> 1 1 86.4 44.0 47.4 39.8 92.2 92.2 100.0
#> 2 2 86.4 44.0 47.4 39.8 92.2 92.2 100.0
#> 3 3 86.4 44.0 47.4 39.8 92.2 92.2 100.0
#> 4 4 86.4 44.0 47.4 39.8 92.2 92.2 100.0
#> 5 5 60.8 29.4 35.1 25.3 81.1 90.5 95.8
#> 6 6 60.8 29.4 35.1 25.3 81.1 90.5 95.8
#> 7 7 60.8 29.4 35.1 25.3 81.1 90.5 95.8
#> 8 8 60.8 29.4 35.1 25.3 81.1 90.5 95.8
#> 9 9 60.8 29.4 35.1 25.3 81.1 90.5 95.8
#> 10 10 59.4 23.3 29.6 19.2 81.9 88.2 97.3
#> 11 11 59.4 23.3 29.6 19.2 81.9 88.2 97.3
#> 12 12 59.4 23.3 29.6 19.2 81.9 88.2 97.3
#> 13 13 59.4 23.3 29.6 19.2 81.9 88.2 97.3
#> 14 14 59.4 23.3 29.6 19.2 81.9 88.2 97.3
#> 15 15 47.6 21.6 29.2 16.4 70.6 84.0 94.5
#> 16 16 47.6 21.6 29.2 16.4 70.6 84.0 94.5
#> 17 17 47.6 21.6 29.2 16.4 70.6 84.0 94.5
#> 18 18 47.6 21.6 29.2 16.4 70.6 84.0 94.5
#> 19 19 47.6 21.6 29.2 16.4 70.6 84.0 94.5
#> 20 20 36.3 10.8 16.8 8.6 61.0 75.5 92.7
#> 21 21 36.3 10.8 16.8 8.6 61.0 75.5 92.7
#> 22 22 36.3 10.8 16.8 8.6 61.0 75.5 92.7
#> 23 23 36.3 10.8 16.8 8.6 61.0 75.5 92.7
#> 24 24 36.3 10.8 16.8 8.6 61.0 75.5 92.7
#> 25 25 32.8 8.0 15.1 7.0 59.5 74.4 87.2
#> 26 26 32.8 8.0 15.1 7.0 59.5 74.4 87.2
#> 27 27 32.8 8.0 15.1 7.0 59.5 74.4 87.2
#> 28 28 32.8 8.0 15.1 7.0 59.5 74.4 87.2
#> 29 29 32.8 8.0 15.1 7.0 59.5 74.4 87.2
#> 30 30 21.6 5.2 10.4 4.2 42.8 56.9 78.7
#> 31 31 21.6 5.2 10.4 4.2 42.8 56.9 78.7
#> 32 32 21.6 5.2 10.4 4.2 42.8 56.9 78.7
#> 33 33 21.6 5.2 10.4 4.2 42.8 56.9 78.7
#> 34 34 21.6 5.2 10.4 4.2 42.8 56.9 78.7
#> 35 35 19.5 5.3 9.1 5.1 37.3 52.5 73.7
#> 36 36 19.5 5.3 9.1 5.1 37.3 52.5 73.7
#> 37 37 19.5 5.3 9.1 5.1 37.3 52.5 73.7
#> 38 38 19.5 5.3 9.1 5.1 37.3 52.5 73.7
#> 39 39 19.5 5.3 9.1 5.1 37.3 52.5 73.7
#> 40 40 10.8 3.0 3.4 1.9 25.2 43.3 69.2
#> 41 41 10.8 3.0 3.4 1.9 25.2 43.3 69.2
#> 42 42 10.8 3.0 3.4 1.9 25.2 43.3 69.2
#> 43 43 10.8 3.0 3.4 1.9 25.2 43.3 69.2
#> 44 44 10.8 3.0 3.4 1.9 25.2 43.3 69.2
#> 45 45 6.8 1.0 1.5 1.0 20.1 33.1 52.6
#> 46 46 6.8 1.0 1.5 1.0 20.1 33.1 52.6
#> 47 47 6.8 1.0 1.5 1.0 20.1 33.1 52.6
#> 48 48 6.8 1.0 1.5 1.0 20.1 33.1 52.6
#> 49 49 6.8 1.0 1.5 1.0 20.1 33.1 52.6
#> 50 50 3.9 0.3 0.6 0.3 12.5 22.4 46.0
#> 51 51 3.9 0.3 0.6 0.3 12.5 22.4 46.0
#> 52 52 3.9 0.3 0.6 0.3 12.5 22.4 46.0
#> 53 53 3.9 0.3 0.6 0.3 12.5 22.4 46.0
#> 54 54 3.9 0.3 0.6 0.3 12.5 22.4 46.0
#> 55 55 4.4 1.0 1.6 1.0 17.9 26.8 45.8
#> 56 56 4.4 1.0 1.6 1.0 17.9 26.8 45.8
#> 57 57 4.4 1.0 1.6 1.0 17.9 26.8 45.8
#> 58 58 4.4 1.0 1.6 1.0 17.9 26.8 45.8
#> 59 59 4.4 1.0 1.6 1.0 17.9 26.8 45.8
#> 60 60 0.8 0.0 0.0 0.0 3.5 8.3 29.0
#> 61 61 0.8 0.0 0.0 0.0 3.5 8.3 29.0
#> 62 62 0.8 0.0 0.0 0.0 3.5 8.3 29.0
#> 63 63 0.8 0.0 0.0 0.0 3.5 8.3 29.0
#> 64 64 0.8 0.0 0.0 0.0 3.5 8.3 29.0
#> 65 65 0.1 0.0 0.1 0.0 2.3 5.7 20.1
#> 66 66 0.1 0.0 0.1 0.0 2.3 5.7 20.1
#> 67 67 0.1 0.0 0.1 0.0 2.3 5.7 20.1
#> 68 68 0.1 0.0 0.1 0.0 2.3 5.7 20.1
#> 69 69 0.1 0.0 0.1 0.0 2.3 5.7 20.1
#> 70 70 0.0 0.0 0.0 0.0 1.5 2.8 5.3
#> 71 71 0.0 0.0 0.0 0.0 1.5 2.8 5.3
#> 72 72 0.0 0.0 0.0 0.0 1.5 2.8 5.3
#> 73 73 0.0 0.0 0.0 0.0 1.5 2.8 5.3
#> 74 74 0.0 0.0 0.0 0.0 1.5 2.8 5.3
#> 75 75 0.0 0.0 0.0 0.0 0.0 0.0 2.8
#> 76 76 0.0 0.0 0.0 0.0 0.0 0.0 2.8
#> 77 77 0.0 0.0 0.0 0.0 0.0 0.0 2.8
#> 78 78 0.0 0.0 0.0 0.0 0.0 0.0 2.8
#> 79 79 0.0 0.0 0.0 0.0 0.0 0.0 2.8
#> 80 80 0.0 0.0 0.0 0.0 0.0 0.0 6.5
#> 81 81 0.0 0.0 0.0 0.0 0.0 0.0 6.5
#> 82 82 0.0 0.0 0.0 0.0 0.0 0.0 6.5
#> 83 83 0.0 0.0 0.0 0.0 0.0 0.0 6.5
#> 84 84 0.0 0.0 0.0 0.0 0.0 0.0 6.5
#> 85 85 0.0 0.0 0.0 0.0 0.0 4.0 11.5
#> 86 86 0.0 0.0 0.0 0.0 0.0 4.0 11.5
#> 87 87 0.0 0.0 0.0 0.0 0.0 4.0 11.5
#> 88 88 0.0 0.0 0.0 0.0 0.0 4.0 11.5
#> 89 89 0.0 0.0 0.0 0.0 0.0 4.0 11.5
#> 90 90 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
#> 92 92 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
#> 94 94 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
#> 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
ppiYEM2009[ppiYEM2009$score == ppiScore, ]
#> score nl100 nlFood extreme ppp125 ppp250 ppp300 ppp400
#> 50 50 3.9 0.3 0.6 0.3 12.5 22.4 46
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiYEM2009, score == ppiScore)
#> score nl100 nlFood extreme ppp125 ppp250 ppp300 ppp400
#> 50 50 3.9 0.3 0.6 0.3 12.5 22.4 46
# 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
ppiYEM2009[ppiYEM2009$score == ppiScore, "nl100"]
#> [1] 3.9