Poverty Probability Index (PPI) lookup table for Cameroon
Format
A data frame with 8 columns and 101 rows:
scorePPI score
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 Cameroon PPI table
ppiCMR2013
#> score nl100 nl150 nl200 extreme ppp125 ppp200 ppp250
#> 0 0 94.4 100.0 100.0 67.2 83.4 98.3 100.0
#> 1 1 94.4 100.0 100.0 67.2 83.4 98.3 100.0
#> 2 2 94.4 100.0 100.0 67.2 83.4 98.3 100.0
#> 3 3 94.4 100.0 100.0 67.2 83.4 98.3 100.0
#> 4 4 94.4 100.0 100.0 67.2 83.4 98.3 100.0
#> 5 5 83.3 97.0 99.2 51.2 74.0 94.9 98.6
#> 6 6 83.3 97.0 99.2 51.2 74.0 94.9 98.6
#> 7 7 83.3 97.0 99.2 51.2 74.0 94.9 98.6
#> 8 8 83.3 97.0 99.2 51.2 74.0 94.9 98.6
#> 9 9 83.3 97.0 99.2 51.2 74.0 94.9 98.6
#> 10 10 81.7 96.8 98.9 48.5 72.4 94.3 98.3
#> 11 11 81.7 96.8 98.9 48.5 72.4 94.3 98.3
#> 12 12 81.7 96.8 98.9 48.5 72.4 94.3 98.3
#> 13 13 81.7 96.8 98.9 48.5 72.4 94.3 98.3
#> 14 14 81.7 96.8 98.9 48.5 72.4 94.3 98.3
#> 15 15 72.1 95.5 98.1 33.4 50.4 90.5 95.6
#> 16 16 72.1 95.5 98.1 33.4 50.4 90.5 95.6
#> 17 17 72.1 95.5 98.1 33.4 50.4 90.5 95.6
#> 18 18 72.1 95.5 98.1 33.4 50.4 90.5 95.6
#> 19 19 72.1 95.5 98.1 33.4 50.4 90.5 95.6
#> 20 20 63.0 89.8 97.6 23.7 42.6 84.5 91.9
#> 21 21 63.0 89.8 97.6 23.7 42.6 84.5 91.9
#> 22 22 63.0 89.8 97.6 23.7 42.6 84.5 91.9
#> 23 23 63.0 89.8 97.6 23.7 42.6 84.5 91.9
#> 24 24 63.0 89.8 97.6 23.7 42.6 84.5 91.9
#> 25 25 47.7 82.8 95.2 21.0 30.7 73.1 87.9
#> 26 26 47.7 82.8 95.2 21.0 30.7 73.1 87.9
#> 27 27 47.7 82.8 95.2 21.0 30.7 73.1 87.9
#> 28 28 47.7 82.8 95.2 21.0 30.7 73.1 87.9
#> 29 29 47.7 82.8 95.2 21.0 30.7 73.1 87.9
#> 30 30 34.1 74.3 93.7 11.6 18.9 59.5 83.2
#> 31 31 34.1 74.3 93.7 11.6 18.9 59.5 83.2
#> 32 32 34.1 74.3 93.7 11.6 18.9 59.5 83.2
#> 33 33 34.1 74.3 93.7 11.6 18.9 59.5 83.2
#> 34 34 34.1 74.3 93.7 11.6 18.9 59.5 83.2
#> 35 35 30.0 63.8 84.2 7.9 13.6 47.4 67.6
#> 36 36 30.0 63.8 84.2 7.9 13.6 47.4 67.6
#> 37 37 30.0 63.8 84.2 7.9 13.6 47.4 67.6
#> 38 38 30.0 63.8 84.2 7.9 13.6 47.4 67.6
#> 39 39 30.0 63.8 84.2 7.9 13.6 47.4 67.6
#> 40 40 18.0 52.5 75.9 4.0 6.2 35.1 57.3
#> 41 41 18.0 52.5 75.9 4.0 6.2 35.1 57.3
#> 42 42 18.0 52.5 75.9 4.0 6.2 35.1 57.3
#> 43 43 18.0 52.5 75.9 4.0 6.2 35.1 57.3
#> 44 44 18.0 52.5 75.9 4.0 6.2 35.1 57.3
#> 45 45 10.6 42.8 67.5 2.3 3.4 23.0 41.8
#> 46 46 10.6 42.8 67.5 2.3 3.4 23.0 41.8
#> 47 47 10.6 42.8 67.5 2.3 3.4 23.0 41.8
#> 48 48 10.6 42.8 67.5 2.3 3.4 23.0 41.8
#> 49 49 10.6 42.8 67.5 2.3 3.4 23.0 41.8
#> 50 50 8.3 33.5 56.3 2.3 2.7 18.0 32.9
#> 51 51 8.3 33.5 56.3 2.3 2.7 18.0 32.9
#> 52 52 8.3 33.5 56.3 2.3 2.7 18.0 32.9
#> 53 53 8.3 33.5 56.3 2.3 2.7 18.0 32.9
#> 54 54 8.3 33.5 56.3 2.3 2.7 18.0 32.9
#> 55 55 4.3 25.7 47.7 0.9 0.9 10.4 23.9
#> 56 56 4.3 25.7 47.7 0.9 0.9 10.4 23.9
#> 57 57 4.3 25.7 47.7 0.9 0.9 10.4 23.9
#> 58 58 4.3 25.7 47.7 0.9 0.9 10.4 23.9
#> 59 59 4.3 25.7 47.7 0.9 0.9 10.4 23.9
#> 60 60 3.6 17.2 37.2 0.3 0.3 5.4 17.5
#> 61 61 3.6 17.2 37.2 0.3 0.3 5.4 17.5
#> 62 62 3.6 17.2 37.2 0.3 0.3 5.4 17.5
#> 63 63 3.6 17.2 37.2 0.3 0.3 5.4 17.5
#> 64 64 3.6 17.2 37.2 0.3 0.3 5.4 17.5
#> 65 65 1.7 8.3 25.1 0.3 0.3 4.2 9.0
#> 66 66 1.7 8.3 25.1 0.3 0.3 4.2 9.0
#> 67 67 1.7 8.3 25.1 0.3 0.3 4.2 9.0
#> 68 68 1.7 8.3 25.1 0.3 0.3 4.2 9.0
#> 69 69 1.7 8.3 25.1 0.3 0.3 4.2 9.0
#> 70 70 0.9 5.7 20.7 0.0 0.0 1.5 5.5
#> 71 71 0.9 5.7 20.7 0.0 0.0 1.5 5.5
#> 72 72 0.9 5.7 20.7 0.0 0.0 1.5 5.5
#> 73 73 0.9 5.7 20.7 0.0 0.0 1.5 5.5
#> 74 74 0.9 5.7 20.7 0.0 0.0 1.5 5.5
#> 75 75 0.9 3.5 13.3 0.0 0.0 1.3 3.4
#> 76 76 0.9 3.5 13.3 0.0 0.0 1.3 3.4
#> 77 77 0.9 3.5 13.3 0.0 0.0 1.3 3.4
#> 78 78 0.9 3.5 13.3 0.0 0.0 1.3 3.4
#> 79 79 0.9 3.5 13.3 0.0 0.0 1.3 3.4
#> 80 80 0.5 2.9 9.3 0.0 0.0 0.6 2.3
#> 81 81 0.5 2.9 9.3 0.0 0.0 0.6 2.3
#> 82 82 0.5 2.9 9.3 0.0 0.0 0.6 2.3
#> 83 83 0.5 2.9 9.3 0.0 0.0 0.6 2.3
#> 84 84 0.5 2.9 9.3 0.0 0.0 0.6 2.3
#> 85 85 0.0 1.2 7.0 0.0 0.0 0.4 0.8
#> 86 86 0.0 1.2 7.0 0.0 0.0 0.4 0.8
#> 87 87 0.0 1.2 7.0 0.0 0.0 0.4 0.8
#> 88 88 0.0 1.2 7.0 0.0 0.0 0.4 0.8
#> 89 89 0.0 1.2 7.0 0.0 0.0 0.4 0.8
#> 90 90 0.0 1.1 3.3 0.0 0.0 0.4 0.8
#> 91 91 0.0 1.1 3.3 0.0 0.0 0.4 0.8
#> 92 92 0.0 1.1 3.3 0.0 0.0 0.4 0.8
#> 93 93 0.0 1.1 3.3 0.0 0.0 0.4 0.8
#> 94 94 0.0 1.1 3.3 0.0 0.0 0.4 0.8
#> 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
ppiCMR2013[ppiCMR2013$score == ppiScore, ]
#> score nl100 nl150 nl200 extreme ppp125 ppp200 ppp250
#> 50 50 8.3 33.5 56.3 2.3 2.7 18 32.9
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiCMR2013, score == ppiScore)
#> score nl100 nl150 nl200 extreme ppp125 ppp200 ppp250
#> 50 50 8.3 33.5 56.3 2.3 2.7 18 32.9
# Given a specific PPI score (from 0 - 100), get a poverty probability
# based on a specific poverty definition. In this example, the USAID
# extreme poverty definition
ppiScore <- 50
ppiCMR2013[ppiCMR2013$score == ppiScore, "extreme"]
#> [1] 2.3