Poverty Probability Index (PPI) lookup table for Morocco
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)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $3.75 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
Examples
# Access Morocco PPI table
ppiMAR2013
#> score nl100 nl150 nl200 extreme ppp125 ppp250 ppp375 ppp500
#> 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 72.4 93.7 100.0 51.8 38.7 93.0 100.0 100.0
#> 6 6 72.4 93.7 100.0 51.8 38.7 93.0 100.0 100.0
#> 7 7 72.4 93.7 100.0 51.8 38.7 93.0 100.0 100.0
#> 8 8 72.4 93.7 100.0 51.8 38.7 93.0 100.0 100.0
#> 9 9 72.4 93.7 100.0 51.8 38.7 93.0 100.0 100.0
#> 10 10 43.8 87.3 95.9 28.0 17.9 77.7 96.5 99.5
#> 11 11 43.8 87.3 95.9 28.0 17.9 77.7 96.5 99.5
#> 12 12 43.8 87.3 95.9 28.0 17.9 77.7 96.5 99.5
#> 13 13 43.8 87.3 95.9 28.0 17.9 77.7 96.5 99.5
#> 14 14 43.8 87.3 95.9 28.0 17.9 77.7 96.5 99.5
#> 15 15 36.9 77.3 92.7 22.5 13.1 72.9 93.6 98.4
#> 16 16 36.9 77.3 92.7 22.5 13.1 72.9 93.6 98.4
#> 17 17 36.9 77.3 92.7 22.5 13.1 72.9 93.6 98.4
#> 18 18 36.9 77.3 92.7 22.5 13.1 72.9 93.6 98.4
#> 19 19 36.9 77.3 92.7 22.5 13.1 72.9 93.6 98.4
#> 20 20 26.6 62.9 83.8 14.5 7.8 58.2 87.9 96.3
#> 21 21 26.6 62.9 83.8 14.5 7.8 58.2 87.9 96.3
#> 22 22 26.6 62.9 83.8 14.5 7.8 58.2 87.9 96.3
#> 23 23 26.6 62.9 83.8 14.5 7.8 58.2 87.9 96.3
#> 24 24 26.6 62.9 83.8 14.5 7.8 58.2 87.9 96.3
#> 25 25 14.5 46.3 76.9 6.9 3.6 42.0 81.6 94.1
#> 26 26 14.5 46.3 76.9 6.9 3.6 42.0 81.6 94.1
#> 27 27 14.5 46.3 76.9 6.9 3.6 42.0 81.6 94.1
#> 28 28 14.5 46.3 76.9 6.9 3.6 42.0 81.6 94.1
#> 29 29 14.5 46.3 76.9 6.9 3.6 42.0 81.6 94.1
#> 30 30 8.6 38.3 63.9 2.5 1.5 32.8 69.3 87.6
#> 31 31 8.6 38.3 63.9 2.5 1.5 32.8 69.3 87.6
#> 32 32 8.6 38.3 63.9 2.5 1.5 32.8 69.3 87.6
#> 33 33 8.6 38.3 63.9 2.5 1.5 32.8 69.3 87.6
#> 34 34 8.6 38.3 63.9 2.5 1.5 32.8 69.3 87.6
#> 35 35 3.8 19.5 45.0 1.5 0.5 16.1 51.4 77.8
#> 36 36 3.8 19.5 45.0 1.5 0.5 16.1 51.4 77.8
#> 37 37 3.8 19.5 45.0 1.5 0.5 16.1 51.4 77.8
#> 38 38 3.8 19.5 45.0 1.5 0.5 16.1 51.4 77.8
#> 39 39 3.8 19.5 45.0 1.5 0.5 16.1 51.4 77.8
#> 40 40 1.9 13.7 32.7 0.6 0.1 11.1 37.3 65.7
#> 41 41 1.9 13.7 32.7 0.6 0.1 11.1 37.3 65.7
#> 42 42 1.9 13.7 32.7 0.6 0.1 11.1 37.3 65.7
#> 43 43 1.9 13.7 32.7 0.6 0.1 11.1 37.3 65.7
#> 44 44 1.9 13.7 32.7 0.6 0.1 11.1 37.3 65.7
#> 45 45 0.5 8.7 26.3 0.0 0.0 5.7 29.9 57.7
#> 46 46 0.5 8.7 26.3 0.0 0.0 5.7 29.9 57.7
#> 47 47 0.5 8.7 26.3 0.0 0.0 5.7 29.9 57.7
#> 48 48 0.5 8.7 26.3 0.0 0.0 5.7 29.9 57.7
#> 49 49 0.5 8.7 26.3 0.0 0.0 5.7 29.9 57.7
#> 50 50 0.0 3.4 15.5 0.0 0.0 1.9 20.3 42.6
#> 51 51 0.0 3.4 15.5 0.0 0.0 1.9 20.3 42.6
#> 52 52 0.0 3.4 15.5 0.0 0.0 1.9 20.3 42.6
#> 53 53 0.0 3.4 15.5 0.0 0.0 1.9 20.3 42.6
#> 54 54 0.0 3.4 15.5 0.0 0.0 1.9 20.3 42.6
#> 55 55 0.0 2.0 9.9 0.0 0.0 1.1 12.9 30.3
#> 56 56 0.0 2.0 9.9 0.0 0.0 1.1 12.9 30.3
#> 57 57 0.0 2.0 9.9 0.0 0.0 1.1 12.9 30.3
#> 58 58 0.0 2.0 9.9 0.0 0.0 1.1 12.9 30.3
#> 59 59 0.0 2.0 9.9 0.0 0.0 1.1 12.9 30.3
#> 60 60 0.0 1.2 5.8 0.0 0.0 0.6 8.4 23.8
#> 61 61 0.0 1.2 5.8 0.0 0.0 0.6 8.4 23.8
#> 62 62 0.0 1.2 5.8 0.0 0.0 0.6 8.4 23.8
#> 63 63 0.0 1.2 5.8 0.0 0.0 0.6 8.4 23.8
#> 64 64 0.0 1.2 5.8 0.0 0.0 0.6 8.4 23.8
#> 65 65 0.0 0.0 2.1 0.0 0.0 0.0 2.6 13.2
#> 66 66 0.0 0.0 2.1 0.0 0.0 0.0 2.6 13.2
#> 67 67 0.0 0.0 2.1 0.0 0.0 0.0 2.6 13.2
#> 68 68 0.0 0.0 2.1 0.0 0.0 0.0 2.6 13.2
#> 69 69 0.0 0.0 2.1 0.0 0.0 0.0 2.6 13.2
#> 70 70 0.0 0.0 0.9 0.0 0.0 0.0 0.9 6.8
#> 71 71 0.0 0.0 0.9 0.0 0.0 0.0 0.9 6.8
#> 72 72 0.0 0.0 0.9 0.0 0.0 0.0 0.9 6.8
#> 73 73 0.0 0.0 0.9 0.0 0.0 0.0 0.9 6.8
#> 74 74 0.0 0.0 0.9 0.0 0.0 0.0 0.9 6.8
#> 75 75 0.0 0.0 0.4 0.0 0.0 0.0 0.4 2.8
#> 76 76 0.0 0.0 0.4 0.0 0.0 0.0 0.4 2.8
#> 77 77 0.0 0.0 0.4 0.0 0.0 0.0 0.4 2.8
#> 78 78 0.0 0.0 0.4 0.0 0.0 0.0 0.4 2.8
#> 79 79 0.0 0.0 0.4 0.0 0.0 0.0 0.4 2.8
#> 80 80 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 81 81 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 82 82 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 83 83 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 84 84 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 85 85 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 86 86 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 87 87 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 88 88 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 89 89 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 90 90 0.0 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 0.0
#> 92 92 0.0 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 0.0
#> 94 94 0.0 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 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
ppiMAR2013[ppiMAR2013$score == ppiScore, ]
#> score nl100 nl150 nl200 extreme ppp125 ppp250 ppp375 ppp500
#> 50 50 0 3.4 15.5 0 0 1.9 20.3 42.6
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiMAR2013, score == ppiScore)
#> score nl100 nl150 nl200 extreme ppp125 ppp250 ppp375 ppp500
#> 50 50 0 3.4 15.5 0 0 1.9 20.3 42.6
# 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
ppiMAR2013[ppiMAR2013$score == ppiScore, "nl100"]
#> [1] 0