Poverty Probability Index (PPI) lookup table for Morocco
ppiMAR2013
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)
# 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