Poverty Probability Index (PPI) lookup table for Niger
Format
A data frame with 9 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)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
Examples
# Access Niger PPI table
ppiNER2013
#> score nlFood nl100 nl150 nl200 extreme ppp125 ppp200 ppp250
#> 0 0 40.2 90.4 99.1 100.0 72.2 92.0 100.0 100.0
#> 1 1 40.2 90.4 99.1 100.0 72.2 92.0 100.0 100.0
#> 2 2 40.2 90.4 99.1 100.0 72.2 92.0 100.0 100.0
#> 3 3 40.2 90.4 99.1 100.0 72.2 92.0 100.0 100.0
#> 4 4 40.2 90.4 99.1 100.0 72.2 92.0 100.0 100.0
#> 5 5 36.0 89.7 98.6 99.6 54.1 90.9 99.4 99.8
#> 6 6 36.0 89.7 98.6 99.6 54.1 90.9 99.4 99.8
#> 7 7 36.0 89.7 98.6 99.6 54.1 90.9 99.4 99.8
#> 8 8 36.0 89.7 98.6 99.6 54.1 90.9 99.4 99.8
#> 9 9 36.0 89.7 98.6 99.6 54.1 90.9 99.4 99.8
#> 10 10 25.1 78.7 96.6 99.1 41.7 85.6 98.4 99.2
#> 11 11 25.1 78.7 96.6 99.1 41.7 85.6 98.4 99.2
#> 12 12 25.1 78.7 96.6 99.1 41.7 85.6 98.4 99.2
#> 13 13 25.1 78.7 96.6 99.1 41.7 85.6 98.4 99.2
#> 14 14 25.1 78.7 96.6 99.1 41.7 85.6 98.4 99.2
#> 15 15 20.1 76.0 96.6 99.1 35.6 83.8 98.4 99.2
#> 16 16 20.1 76.0 96.6 99.1 35.6 83.8 98.4 99.2
#> 17 17 20.1 76.0 96.6 99.1 35.6 83.8 98.4 99.2
#> 18 18 20.1 76.0 96.6 99.1 35.6 83.8 98.4 99.2
#> 19 19 20.1 76.0 96.6 99.1 35.6 83.8 98.4 99.2
#> 20 20 15.0 67.9 96.6 99.1 33.2 74.6 98.4 99.2
#> 21 21 15.0 67.9 96.6 99.1 33.2 74.6 98.4 99.2
#> 22 22 15.0 67.9 96.6 99.1 33.2 74.6 98.4 99.2
#> 23 23 15.0 67.9 96.6 99.1 33.2 74.6 98.4 99.2
#> 24 24 15.0 67.9 96.6 99.1 33.2 74.6 98.4 99.2
#> 25 25 10.7 53.9 84.3 97.5 19.4 63.4 95.4 98.0
#> 26 26 10.7 53.9 84.3 97.5 19.4 63.4 95.4 98.0
#> 27 27 10.7 53.9 84.3 97.5 19.4 63.4 95.4 98.0
#> 28 28 10.7 53.9 84.3 97.5 19.4 63.4 95.4 98.0
#> 29 29 10.7 53.9 84.3 97.5 19.4 63.4 95.4 98.0
#> 30 30 4.9 40.0 73.0 92.6 12.5 50.2 88.2 94.4
#> 31 31 4.9 40.0 73.0 92.6 12.5 50.2 88.2 94.4
#> 32 32 4.9 40.0 73.0 92.6 12.5 50.2 88.2 94.4
#> 33 33 4.9 40.0 73.0 92.6 12.5 50.2 88.2 94.4
#> 34 34 4.9 40.0 73.0 92.6 12.5 50.2 88.2 94.4
#> 35 35 3.5 32.3 64.6 84.3 10.1 38.8 74.2 89.5
#> 36 36 3.5 32.3 64.6 84.3 10.1 38.8 74.2 89.5
#> 37 37 3.5 32.3 64.6 84.3 10.1 38.8 74.2 89.5
#> 38 38 3.5 32.3 64.6 84.3 10.1 38.8 74.2 89.5
#> 39 39 3.5 32.3 64.6 84.3 10.1 38.8 74.2 89.5
#> 40 40 2.9 32.3 60.7 79.8 10.1 36.4 70.6 83.0
#> 41 41 2.9 32.3 60.7 79.8 10.1 36.4 70.6 83.0
#> 42 42 2.9 32.3 60.7 79.8 10.1 36.4 70.6 83.0
#> 43 43 2.9 32.3 60.7 79.8 10.1 36.4 70.6 83.0
#> 44 44 2.9 32.3 60.7 79.8 10.1 36.4 70.6 83.0
#> 45 45 1.9 25.3 59.9 75.0 6.3 30.0 70.3 77.8
#> 46 46 1.9 25.3 59.9 75.0 6.3 30.0 70.3 77.8
#> 47 47 1.9 25.3 59.9 75.0 6.3 30.0 70.3 77.8
#> 48 48 1.9 25.3 59.9 75.0 6.3 30.0 70.3 77.8
#> 49 49 1.9 25.3 59.9 75.0 6.3 30.0 70.3 77.8
#> 50 50 0.6 11.4 54.4 73.4 1.4 16.8 67.4 76.9
#> 51 51 0.6 11.4 54.4 73.4 1.4 16.8 67.4 76.9
#> 52 52 0.6 11.4 54.4 73.4 1.4 16.8 67.4 76.9
#> 53 53 0.6 11.4 54.4 73.4 1.4 16.8 67.4 76.9
#> 54 54 0.6 11.4 54.4 73.4 1.4 16.8 67.4 76.9
#> 55 55 0.2 5.3 24.2 44.4 0.3 9.0 36.3 51.2
#> 56 56 0.2 5.3 24.2 44.4 0.3 9.0 36.3 51.2
#> 57 57 0.2 5.3 24.2 44.4 0.3 9.0 36.3 51.2
#> 58 58 0.2 5.3 24.2 44.4 0.3 9.0 36.3 51.2
#> 59 59 0.2 5.3 24.2 44.4 0.3 9.0 36.3 51.2
#> 60 60 0.0 1.7 17.2 39.6 0.2 5.4 33.1 47.5
#> 61 61 0.0 1.7 17.2 39.6 0.2 5.4 33.1 47.5
#> 62 62 0.0 1.7 17.2 39.6 0.2 5.4 33.1 47.5
#> 63 63 0.0 1.7 17.2 39.6 0.2 5.4 33.1 47.5
#> 64 64 0.0 1.7 17.2 39.6 0.2 5.4 33.1 47.5
#> 65 65 0.0 1.7 9.9 32.3 0.0 2.9 21.6 37.2
#> 66 66 0.0 1.7 9.9 32.3 0.0 2.9 21.6 37.2
#> 67 67 0.0 1.7 9.9 32.3 0.0 2.9 21.6 37.2
#> 68 68 0.0 1.7 9.9 32.3 0.0 2.9 21.6 37.2
#> 69 69 0.0 1.7 9.9 32.3 0.0 2.9 21.6 37.2
#> 70 70 0.0 0.0 5.7 14.0 0.0 0.7 7.8 19.7
#> 71 71 0.0 0.0 5.7 14.0 0.0 0.7 7.8 19.7
#> 72 72 0.0 0.0 5.7 14.0 0.0 0.7 7.8 19.7
#> 73 73 0.0 0.0 5.7 14.0 0.0 0.7 7.8 19.7
#> 74 74 0.0 0.0 5.7 14.0 0.0 0.7 7.8 19.7
#> 75 75 0.0 0.0 4.4 11.0 0.0 0.7 6.7 18.1
#> 76 76 0.0 0.0 4.4 11.0 0.0 0.7 6.7 18.1
#> 77 77 0.0 0.0 4.4 11.0 0.0 0.7 6.7 18.1
#> 78 78 0.0 0.0 4.4 11.0 0.0 0.7 6.7 18.1
#> 79 79 0.0 0.0 4.4 11.0 0.0 0.7 6.7 18.1
#> 80 80 0.0 0.0 4.4 11.0 0.0 0.7 6.7 16.6
#> 81 81 0.0 0.0 4.4 11.0 0.0 0.7 6.7 16.6
#> 82 82 0.0 0.0 4.4 11.0 0.0 0.7 6.7 16.6
#> 83 83 0.0 0.0 4.4 11.0 0.0 0.7 6.7 16.6
#> 84 84 0.0 0.0 4.4 11.0 0.0 0.7 6.7 16.6
#> 85 85 0.0 0.0 4.4 11.0 0.0 0.0 6.7 15.7
#> 86 86 0.0 0.0 4.4 11.0 0.0 0.0 6.7 15.7
#> 87 87 0.0 0.0 4.4 11.0 0.0 0.0 6.7 15.7
#> 88 88 0.0 0.0 4.4 11.0 0.0 0.0 6.7 15.7
#> 89 89 0.0 0.0 4.4 11.0 0.0 0.0 6.7 15.7
#> 90 90 0.0 0.0 0.0 3.5 0.0 0.0 0.0 8.4
#> 91 91 0.0 0.0 0.0 3.5 0.0 0.0 0.0 8.4
#> 92 92 0.0 0.0 0.0 3.5 0.0 0.0 0.0 8.4
#> 93 93 0.0 0.0 0.0 3.5 0.0 0.0 0.0 8.4
#> 94 94 0.0 0.0 0.0 3.5 0.0 0.0 0.0 8.4
#> 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
ppiNER2013[ppiNER2013$score == ppiScore, ]
#> score nlFood nl100 nl150 nl200 extreme ppp125 ppp200 ppp250
#> 50 50 0.6 11.4 54.4 73.4 1.4 16.8 67.4 76.9
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiNER2013, score == ppiScore)
#> score nlFood nl100 nl150 nl200 extreme ppp125 ppp200 ppp250
#> 50 50 0.6 11.4 54.4 73.4 1.4 16.8 67.4 76.9
# 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
ppiNER2013[ppiNER2013$score == ppiScore, "nl100"]
#> [1] 11.4