Poverty Probability Index (PPI) lookup table for Jordan
Format
A data frame with 10 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
nl250National poverty line (250%)
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 Jordan PPI table
ppiJOR2010
#> score nl100 nl150 nl200 nl250 extreme ppp125 ppp250 ppp375 ppp500
#> 1 0 86.7 100.0 100.0 100.0 85.7 21.8 85.7 100.0 100.0
#> 2 1 86.7 100.0 100.0 100.0 85.7 21.8 85.7 100.0 100.0
#> 3 2 86.7 100.0 100.0 100.0 85.7 21.8 85.7 100.0 100.0
#> 4 3 86.7 100.0 100.0 100.0 85.7 21.8 85.7 100.0 100.0
#> 5 4 86.7 100.0 100.0 100.0 85.7 21.8 85.7 100.0 100.0
#> 6 5 65.7 94.4 99.2 100.0 44.7 2.7 51.6 90.4 96.6
#> 7 6 65.7 94.4 99.2 100.0 44.7 2.7 51.6 90.4 96.6
#> 8 7 65.7 94.4 99.2 100.0 44.7 2.7 51.6 90.4 96.6
#> 9 8 65.7 94.4 99.2 100.0 44.7 2.7 51.6 90.4 96.6
#> 10 9 65.7 94.4 99.2 100.0 44.7 2.7 51.6 90.4 96.6
#> 11 10 63.7 86.9 97.8 99.2 42.7 1.2 46.6 78.7 93.4
#> 12 11 63.7 86.9 97.8 99.2 42.7 1.2 46.6 78.7 93.4
#> 13 12 63.7 86.9 97.8 99.2 42.7 1.2 46.6 78.7 93.4
#> 14 13 63.7 86.9 97.8 99.2 42.7 1.2 46.6 78.7 93.4
#> 15 14 63.7 86.9 97.8 99.2 42.7 1.2 46.6 78.7 93.4
#> 16 15 39.5 78.5 96.2 98.5 22.2 2.1 26.6 68.2 90.7
#> 17 16 39.5 78.5 96.2 98.5 22.2 2.1 26.6 68.2 90.7
#> 18 17 39.5 78.5 96.2 98.5 22.2 2.1 26.6 68.2 90.7
#> 19 18 39.5 78.5 96.2 98.5 22.2 2.1 26.6 68.2 90.7
#> 20 19 39.5 78.5 96.2 98.5 22.2 2.1 26.6 68.2 90.7
#> 21 20 22.6 66.2 86.7 94.1 9.5 0.0 13.9 53.7 77.6
#> 22 21 22.6 66.2 86.7 94.1 9.5 0.0 13.9 53.7 77.6
#> 23 22 22.6 66.2 86.7 94.1 9.5 0.0 13.9 53.7 77.6
#> 24 23 22.6 66.2 86.7 94.1 9.5 0.0 13.9 53.7 77.6
#> 25 24 22.6 66.2 86.7 94.1 9.5 0.0 13.9 53.7 77.6
#> 26 25 16.0 52.0 74.4 89.5 6.6 0.0 8.8 37.1 63.2
#> 27 26 16.0 52.0 74.4 89.5 6.6 0.0 8.8 37.1 63.2
#> 28 27 16.0 52.0 74.4 89.5 6.6 0.0 8.8 37.1 63.2
#> 29 28 16.0 52.0 74.4 89.5 6.6 0.0 8.8 37.1 63.2
#> 30 29 16.0 52.0 74.4 89.5 6.6 0.0 8.8 37.1 63.2
#> 31 30 7.7 43.0 73.6 87.9 2.1 0.0 3.7 27.3 60.0
#> 32 31 7.7 43.0 73.6 87.9 2.1 0.0 3.7 27.3 60.0
#> 33 32 7.7 43.0 73.6 87.9 2.1 0.0 3.7 27.3 60.0
#> 34 33 7.7 43.0 73.6 87.9 2.1 0.0 3.7 27.3 60.0
#> 35 34 7.7 43.0 73.6 87.9 2.1 0.0 3.7 27.3 60.0
#> 36 35 3.3 27.3 57.2 76.2 0.7 0.0 2.0 14.0 42.8
#> 37 36 3.3 27.3 57.2 76.2 0.7 0.0 2.0 14.0 42.8
#> 38 37 3.3 27.3 57.2 76.2 0.7 0.0 2.0 14.0 42.8
#> 39 38 3.3 27.3 57.2 76.2 0.7 0.0 2.0 14.0 42.8
#> 40 39 3.3 27.3 57.2 76.2 0.7 0.0 2.0 14.0 42.8
#> 41 40 1.5 16.8 46.4 68.5 0.5 0.0 0.4 8.6 30.3
#> 42 41 1.5 16.8 46.4 68.5 0.5 0.0 0.4 8.6 30.3
#> 43 42 1.5 16.8 46.4 68.5 0.5 0.0 0.4 8.6 30.3
#> 44 43 1.5 16.8 46.4 68.5 0.5 0.0 0.4 8.6 30.3
#> 45 44 1.5 16.8 46.4 68.5 0.5 0.0 0.4 8.6 30.3
#> 46 45 0.2 6.9 29.3 50.7 0.0 0.0 0.2 3.3 15.9
#> 47 46 0.2 6.9 29.3 50.7 0.0 0.0 0.2 3.3 15.9
#> 48 47 0.2 6.9 29.3 50.7 0.0 0.0 0.2 3.3 15.9
#> 49 48 0.2 6.9 29.3 50.7 0.0 0.0 0.2 3.3 15.9
#> 50 49 0.2 6.9 29.3 50.7 0.0 0.0 0.2 3.3 15.9
#> 51 50 0.9 3.6 20.0 39.8 0.0 0.0 0.2 1.4 9.9
#> 52 51 0.9 3.6 20.0 39.8 0.0 0.0 0.2 1.4 9.9
#> 53 52 0.9 3.6 20.0 39.8 0.0 0.0 0.2 1.4 9.9
#> 54 53 0.9 3.6 20.0 39.8 0.0 0.0 0.2 1.4 9.9
#> 55 54 0.9 3.6 20.0 39.8 0.0 0.0 0.2 1.4 9.9
#> 56 55 0.0 2.1 9.5 24.6 0.0 0.0 0.0 0.1 5.8
#> 57 56 0.0 2.1 9.5 24.6 0.0 0.0 0.0 0.1 5.8
#> 58 57 0.0 2.1 9.5 24.6 0.0 0.0 0.0 0.1 5.8
#> 59 58 0.0 2.1 9.5 24.6 0.0 0.0 0.0 0.1 5.8
#> 60 59 0.0 2.1 9.5 24.6 0.0 0.0 0.0 0.1 5.8
#> 61 60 0.0 0.7 4.2 15.3 0.0 0.0 0.0 0.1 1.3
#> 62 61 0.0 0.7 4.2 15.3 0.0 0.0 0.0 0.1 1.3
#> 63 62 0.0 0.7 4.2 15.3 0.0 0.0 0.0 0.1 1.3
#> 64 63 0.0 0.7 4.2 15.3 0.0 0.0 0.0 0.1 1.3
#> 65 64 0.0 0.7 4.2 15.3 0.0 0.0 0.0 0.1 1.3
#> 66 65 0.0 0.0 1.1 5.8 0.0 0.0 0.0 0.0 0.4
#> 67 66 0.0 0.0 1.1 5.8 0.0 0.0 0.0 0.0 0.4
#> 68 67 0.0 0.0 1.1 5.8 0.0 0.0 0.0 0.0 0.4
#> 69 68 0.0 0.0 1.1 5.8 0.0 0.0 0.0 0.0 0.4
#> 70 69 0.0 0.0 1.1 5.8 0.0 0.0 0.0 0.0 0.4
#> 71 70 0.0 0.0 2.0 4.5 0.0 0.0 0.0 0.0 0.4
#> 72 71 0.0 0.0 2.0 4.5 0.0 0.0 0.0 0.0 0.4
#> 73 72 0.0 0.0 2.0 4.5 0.0 0.0 0.0 0.0 0.4
#> 74 73 0.0 0.0 2.0 4.5 0.0 0.0 0.0 0.0 0.4
#> 75 74 0.0 0.0 2.0 4.5 0.0 0.0 0.0 0.0 0.4
#> 76 75 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 77 76 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 78 77 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 79 78 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 80 79 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 81 80 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 82 81 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 83 82 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 84 83 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 85 84 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 86 85 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 87 86 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 88 87 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 89 88 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 90 89 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 91 90 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 92 91 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 93 92 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 94 93 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 95 94 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 96 95 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 97 96 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 98 97 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 99 98 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 100 99 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 1001 100 0.0 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
ppiJOR2010[ppiJOR2010$score == ppiScore, ]
#> score nl100 nl150 nl200 nl250 extreme ppp125 ppp250 ppp375 ppp500
#> 51 50 0.9 3.6 20 39.8 0 0 0.2 1.4 9.9
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiJOR2010, score == ppiScore)
#> score nl100 nl150 nl200 nl250 extreme ppp125 ppp250 ppp375 ppp500
#> 51 50 0.9 3.6 20 39.8 0 0 0.2 1.4 9.9
# 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
ppiJOR2010[ppiJOR2010$score == ppiScore, "extreme"]
#> [1] 0