Poverty Probability Index (PPI) lookup table for Ivory Coast
Format
A data frame with 9 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 (2011)
ppp800Below $8.00 per day purchasing power parity (2011)
Examples
# Access Ivory Coast PPI table
ppiCIV2013
#> score nl100 nl150 nl200 extreme ppp125 ppp200 ppp250 ppp800
#> 0 0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 1 1 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 2 2 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 3 3 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 4 4 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 5 5 92.7 98.0 100.0 68.4 81.7 96.7 98.0 100.0
#> 6 6 92.7 98.0 100.0 68.4 81.7 96.7 98.0 100.0
#> 7 7 92.7 98.0 100.0 68.4 81.7 96.7 98.0 100.0
#> 8 8 92.7 98.0 100.0 68.4 81.7 96.7 98.0 100.0
#> 9 9 92.7 98.0 100.0 68.4 81.7 96.7 98.0 100.0
#> 10 10 87.6 97.0 99.5 53.1 71.5 93.9 97.2 100.0
#> 11 11 87.6 97.0 99.5 53.1 71.5 93.9 97.2 100.0
#> 12 12 87.6 97.0 99.5 53.1 71.5 93.9 97.2 100.0
#> 13 13 87.6 97.0 99.5 53.1 71.5 93.9 97.2 100.0
#> 14 14 87.6 97.0 99.5 53.1 71.5 93.9 97.2 100.0
#> 15 15 79.6 93.6 98.2 49.7 66.1 89.0 94.9 100.0
#> 16 16 79.6 93.6 98.2 49.7 66.1 89.0 94.9 100.0
#> 17 17 79.6 93.6 98.2 49.7 66.1 89.0 94.9 100.0
#> 18 18 79.6 93.6 98.2 49.7 66.1 89.0 94.9 100.0
#> 19 19 79.6 93.6 98.2 49.7 66.1 89.0 94.9 100.0
#> 20 20 77.7 92.1 97.2 42.0 58.3 87.1 93.6 99.9
#> 21 21 77.7 92.1 97.2 42.0 58.3 87.1 93.6 99.9
#> 22 22 77.7 92.1 97.2 42.0 58.3 87.1 93.6 99.9
#> 23 23 77.7 92.1 97.2 42.0 58.3 87.1 93.6 99.9
#> 24 24 77.7 92.1 97.2 42.0 58.3 87.1 93.6 99.9
#> 25 25 75.8 90.7 96.3 37.5 56.5 85.6 92.0 99.9
#> 26 26 75.8 90.7 96.3 37.5 56.5 85.6 92.0 99.9
#> 27 27 75.8 90.7 96.3 37.5 56.5 85.6 92.0 99.9
#> 28 28 75.8 90.7 96.3 37.5 56.5 85.6 92.0 99.9
#> 29 29 75.8 90.7 96.3 37.5 56.5 85.6 92.0 99.9
#> 30 30 58.0 84.1 94.0 26.3 40.1 72.9 86.6 99.9
#> 31 31 58.0 84.1 94.0 26.3 40.1 72.9 86.6 99.9
#> 32 32 58.0 84.1 94.0 26.3 40.1 72.9 86.6 99.9
#> 33 33 58.0 84.1 94.0 26.3 40.1 72.9 86.6 99.9
#> 34 34 58.0 84.1 94.0 26.3 40.1 72.9 86.6 99.9
#> 35 35 50.7 80.0 92.1 20.9 33.2 68.4 81.6 99.9
#> 36 36 50.7 80.0 92.1 20.9 33.2 68.4 81.6 99.9
#> 37 37 50.7 80.0 92.1 20.9 33.2 68.4 81.6 99.9
#> 38 38 50.7 80.0 92.1 20.9 33.2 68.4 81.6 99.9
#> 39 39 50.7 80.0 92.1 20.9 33.2 68.4 81.6 99.9
#> 40 40 42.3 70.8 85.5 16.7 27.1 59.4 74.1 99.6
#> 41 41 42.3 70.8 85.5 16.7 27.1 59.4 74.1 99.6
#> 42 42 42.3 70.8 85.5 16.7 27.1 59.4 74.1 99.6
#> 43 43 42.3 70.8 85.5 16.7 27.1 59.4 74.1 99.6
#> 44 44 42.3 70.8 85.5 16.7 27.1 59.4 74.1 99.6
#> 45 45 28.9 58.9 76.1 10.1 18.1 44.8 61.8 98.7
#> 46 46 28.9 58.9 76.1 10.1 18.1 44.8 61.8 98.7
#> 47 47 28.9 58.9 76.1 10.1 18.1 44.8 61.8 98.7
#> 48 48 28.9 58.9 76.1 10.1 18.1 44.8 61.8 98.7
#> 49 49 28.9 58.9 76.1 10.1 18.1 44.8 61.8 98.7
#> 50 50 18.3 49.0 69.1 3.7 8.2 33.7 53.7 96.9
#> 51 51 18.3 49.0 69.1 3.7 8.2 33.7 53.7 96.9
#> 52 52 18.3 49.0 69.1 3.7 8.2 33.7 53.7 96.9
#> 53 53 18.3 49.0 69.1 3.7 8.2 33.7 53.7 96.9
#> 54 54 18.3 49.0 69.1 3.7 8.2 33.7 53.7 96.9
#> 55 55 12.0 34.7 52.9 2.0 5.0 22.3 37.2 95.3
#> 56 56 12.0 34.7 52.9 2.0 5.0 22.3 37.2 95.3
#> 57 57 12.0 34.7 52.9 2.0 5.0 22.3 37.2 95.3
#> 58 58 12.0 34.7 52.9 2.0 5.0 22.3 37.2 95.3
#> 59 59 12.0 34.7 52.9 2.0 5.0 22.3 37.2 95.3
#> 60 60 4.4 22.4 43.6 1.0 2.2 11.8 25.1 91.9
#> 61 61 4.4 22.4 43.6 1.0 2.2 11.8 25.1 91.9
#> 62 62 4.4 22.4 43.6 1.0 2.2 11.8 25.1 91.9
#> 63 63 4.4 22.4 43.6 1.0 2.2 11.8 25.1 91.9
#> 64 64 4.4 22.4 43.6 1.0 2.2 11.8 25.1 91.9
#> 65 65 2.9 13.9 32.6 0.5 1.2 8.1 16.7 87.2
#> 66 66 2.9 13.9 32.6 0.5 1.2 8.1 16.7 87.2
#> 67 67 2.9 13.9 32.6 0.5 1.2 8.1 16.7 87.2
#> 68 68 2.9 13.9 32.6 0.5 1.2 8.1 16.7 87.2
#> 69 69 2.9 13.9 32.6 0.5 1.2 8.1 16.7 87.2
#> 70 70 1.0 10.6 22.2 0.1 0.1 4.3 12.2 83.3
#> 71 71 1.0 10.6 22.2 0.1 0.1 4.3 12.2 83.3
#> 72 72 1.0 10.6 22.2 0.1 0.1 4.3 12.2 83.3
#> 73 73 1.0 10.6 22.2 0.1 0.1 4.3 12.2 83.3
#> 74 74 1.0 10.6 22.2 0.1 0.1 4.3 12.2 83.3
#> 75 75 0.3 6.5 17.3 0.0 0.0 2.5 6.5 73.7
#> 76 76 0.3 6.5 17.3 0.0 0.0 2.5 6.5 73.7
#> 77 77 0.3 6.5 17.3 0.0 0.0 2.5 6.5 73.7
#> 78 78 0.3 6.5 17.3 0.0 0.0 2.5 6.5 73.7
#> 79 79 0.3 6.5 17.3 0.0 0.0 2.5 6.5 73.7
#> 80 80 0.0 0.5 5.7 0.0 0.0 0.0 2.1 56.2
#> 81 81 0.0 0.5 5.7 0.0 0.0 0.0 2.1 56.2
#> 82 82 0.0 0.5 5.7 0.0 0.0 0.0 2.1 56.2
#> 83 83 0.0 0.5 5.7 0.0 0.0 0.0 2.1 56.2
#> 84 84 0.0 0.5 5.7 0.0 0.0 0.0 2.1 56.2
#> 85 85 0.0 0.0 3.5 0.0 0.0 0.0 0.9 37.7
#> 86 86 0.0 0.0 3.5 0.0 0.0 0.0 0.9 37.7
#> 87 87 0.0 0.0 3.5 0.0 0.0 0.0 0.9 37.7
#> 88 88 0.0 0.0 3.5 0.0 0.0 0.0 0.9 37.7
#> 89 89 0.0 0.0 3.5 0.0 0.0 0.0 0.9 37.7
#> 90 90 0.0 0.0 0.6 0.0 0.0 0.0 0.0 17.1
#> 91 91 0.0 0.0 0.6 0.0 0.0 0.0 0.0 17.1
#> 92 92 0.0 0.0 0.6 0.0 0.0 0.0 0.0 17.1
#> 93 93 0.0 0.0 0.6 0.0 0.0 0.0 0.0 17.1
#> 94 94 0.0 0.0 0.6 0.0 0.0 0.0 0.0 17.1
#> 95 95 0.0 0.0 0.0 0.0 0.0 0.0 0.0 11.8
#> 96 96 0.0 0.0 0.0 0.0 0.0 0.0 0.0 11.8
#> 97 97 0.0 0.0 0.0 0.0 0.0 0.0 0.0 11.8
#> 98 98 0.0 0.0 0.0 0.0 0.0 0.0 0.0 11.8
#> 99 99 0.0 0.0 0.0 0.0 0.0 0.0 0.0 11.8
#> 100 100 0.0 0.0 0.0 0.0 0.0 0.0 0.0 11.8
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiCIV2013[ppiCIV2013$score == ppiScore, ]
#> score nl100 nl150 nl200 extreme ppp125 ppp200 ppp250 ppp800
#> 50 50 18.3 49 69.1 3.7 8.2 33.7 53.7 96.9
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiCIV2013, score == ppiScore)
#> score nl100 nl150 nl200 extreme ppp125 ppp200 ppp250 ppp800
#> 50 50 18.3 49 69.1 3.7 8.2 33.7 53.7 96.9
# 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
ppiCIV2013[ppiCIV2013$score == ppiScore, "extreme"]
#> [1] 3.7