Poverty Probability Index (PPI) lookup table for Yemen

ppiYEM2009

Format

A data frame with 8 columns and 101 rows:

score

PPI score

nl100

National poverty line (100%)

nlFood

Food poverty line

extreme

USAID extreme poverty

ppp125

Below $1.25 per day purchasing power parity (2005)

ppp250

Below $2.50 per day purchasing power parity (2005)

ppp300

Below $3.00 per day purchasing power parity (2005)

ppp400

Below $4.00 per day purchasing power parity (2005)

Source

www.povertyindex.org

Examples

# Access Yemen PPI table ppiYEM2009
#> score nl100 nlFood extreme ppp125 ppp250 ppp300 ppp400 #> 0 0 86.4 44.0 47.4 39.8 92.2 92.2 100.0 #> 1 1 86.4 44.0 47.4 39.8 92.2 92.2 100.0 #> 2 2 86.4 44.0 47.4 39.8 92.2 92.2 100.0 #> 3 3 86.4 44.0 47.4 39.8 92.2 92.2 100.0 #> 4 4 86.4 44.0 47.4 39.8 92.2 92.2 100.0 #> 5 5 60.8 29.4 35.1 25.3 81.1 90.5 95.8 #> 6 6 60.8 29.4 35.1 25.3 81.1 90.5 95.8 #> 7 7 60.8 29.4 35.1 25.3 81.1 90.5 95.8 #> 8 8 60.8 29.4 35.1 25.3 81.1 90.5 95.8 #> 9 9 60.8 29.4 35.1 25.3 81.1 90.5 95.8 #> 10 10 59.4 23.3 29.6 19.2 81.9 88.2 97.3 #> 11 11 59.4 23.3 29.6 19.2 81.9 88.2 97.3 #> 12 12 59.4 23.3 29.6 19.2 81.9 88.2 97.3 #> 13 13 59.4 23.3 29.6 19.2 81.9 88.2 97.3 #> 14 14 59.4 23.3 29.6 19.2 81.9 88.2 97.3 #> 15 15 47.6 21.6 29.2 16.4 70.6 84.0 94.5 #> 16 16 47.6 21.6 29.2 16.4 70.6 84.0 94.5 #> 17 17 47.6 21.6 29.2 16.4 70.6 84.0 94.5 #> 18 18 47.6 21.6 29.2 16.4 70.6 84.0 94.5 #> 19 19 47.6 21.6 29.2 16.4 70.6 84.0 94.5 #> 20 20 36.3 10.8 16.8 8.6 61.0 75.5 92.7 #> 21 21 36.3 10.8 16.8 8.6 61.0 75.5 92.7 #> 22 22 36.3 10.8 16.8 8.6 61.0 75.5 92.7 #> 23 23 36.3 10.8 16.8 8.6 61.0 75.5 92.7 #> 24 24 36.3 10.8 16.8 8.6 61.0 75.5 92.7 #> 25 25 32.8 8.0 15.1 7.0 59.5 74.4 87.2 #> 26 26 32.8 8.0 15.1 7.0 59.5 74.4 87.2 #> 27 27 32.8 8.0 15.1 7.0 59.5 74.4 87.2 #> 28 28 32.8 8.0 15.1 7.0 59.5 74.4 87.2 #> 29 29 32.8 8.0 15.1 7.0 59.5 74.4 87.2 #> 30 30 21.6 5.2 10.4 4.2 42.8 56.9 78.7 #> 31 31 21.6 5.2 10.4 4.2 42.8 56.9 78.7 #> 32 32 21.6 5.2 10.4 4.2 42.8 56.9 78.7 #> 33 33 21.6 5.2 10.4 4.2 42.8 56.9 78.7 #> 34 34 21.6 5.2 10.4 4.2 42.8 56.9 78.7 #> 35 35 19.5 5.3 9.1 5.1 37.3 52.5 73.7 #> 36 36 19.5 5.3 9.1 5.1 37.3 52.5 73.7 #> 37 37 19.5 5.3 9.1 5.1 37.3 52.5 73.7 #> 38 38 19.5 5.3 9.1 5.1 37.3 52.5 73.7 #> 39 39 19.5 5.3 9.1 5.1 37.3 52.5 73.7 #> 40 40 10.8 3.0 3.4 1.9 25.2 43.3 69.2 #> 41 41 10.8 3.0 3.4 1.9 25.2 43.3 69.2 #> 42 42 10.8 3.0 3.4 1.9 25.2 43.3 69.2 #> 43 43 10.8 3.0 3.4 1.9 25.2 43.3 69.2 #> 44 44 10.8 3.0 3.4 1.9 25.2 43.3 69.2 #> 45 45 6.8 1.0 1.5 1.0 20.1 33.1 52.6 #> 46 46 6.8 1.0 1.5 1.0 20.1 33.1 52.6 #> 47 47 6.8 1.0 1.5 1.0 20.1 33.1 52.6 #> 48 48 6.8 1.0 1.5 1.0 20.1 33.1 52.6 #> 49 49 6.8 1.0 1.5 1.0 20.1 33.1 52.6 #> 50 50 3.9 0.3 0.6 0.3 12.5 22.4 46.0 #> 51 51 3.9 0.3 0.6 0.3 12.5 22.4 46.0 #> 52 52 3.9 0.3 0.6 0.3 12.5 22.4 46.0 #> 53 53 3.9 0.3 0.6 0.3 12.5 22.4 46.0 #> 54 54 3.9 0.3 0.6 0.3 12.5 22.4 46.0 #> 55 55 4.4 1.0 1.6 1.0 17.9 26.8 45.8 #> 56 56 4.4 1.0 1.6 1.0 17.9 26.8 45.8 #> 57 57 4.4 1.0 1.6 1.0 17.9 26.8 45.8 #> 58 58 4.4 1.0 1.6 1.0 17.9 26.8 45.8 #> 59 59 4.4 1.0 1.6 1.0 17.9 26.8 45.8 #> 60 60 0.8 0.0 0.0 0.0 3.5 8.3 29.0 #> 61 61 0.8 0.0 0.0 0.0 3.5 8.3 29.0 #> 62 62 0.8 0.0 0.0 0.0 3.5 8.3 29.0 #> 63 63 0.8 0.0 0.0 0.0 3.5 8.3 29.0 #> 64 64 0.8 0.0 0.0 0.0 3.5 8.3 29.0 #> 65 65 0.1 0.0 0.1 0.0 2.3 5.7 20.1 #> 66 66 0.1 0.0 0.1 0.0 2.3 5.7 20.1 #> 67 67 0.1 0.0 0.1 0.0 2.3 5.7 20.1 #> 68 68 0.1 0.0 0.1 0.0 2.3 5.7 20.1 #> 69 69 0.1 0.0 0.1 0.0 2.3 5.7 20.1 #> 70 70 0.0 0.0 0.0 0.0 1.5 2.8 5.3 #> 71 71 0.0 0.0 0.0 0.0 1.5 2.8 5.3 #> 72 72 0.0 0.0 0.0 0.0 1.5 2.8 5.3 #> 73 73 0.0 0.0 0.0 0.0 1.5 2.8 5.3 #> 74 74 0.0 0.0 0.0 0.0 1.5 2.8 5.3 #> 75 75 0.0 0.0 0.0 0.0 0.0 0.0 2.8 #> 76 76 0.0 0.0 0.0 0.0 0.0 0.0 2.8 #> 77 77 0.0 0.0 0.0 0.0 0.0 0.0 2.8 #> 78 78 0.0 0.0 0.0 0.0 0.0 0.0 2.8 #> 79 79 0.0 0.0 0.0 0.0 0.0 0.0 2.8 #> 80 80 0.0 0.0 0.0 0.0 0.0 0.0 6.5 #> 81 81 0.0 0.0 0.0 0.0 0.0 0.0 6.5 #> 82 82 0.0 0.0 0.0 0.0 0.0 0.0 6.5 #> 83 83 0.0 0.0 0.0 0.0 0.0 0.0 6.5 #> 84 84 0.0 0.0 0.0 0.0 0.0 0.0 6.5 #> 85 85 0.0 0.0 0.0 0.0 0.0 4.0 11.5 #> 86 86 0.0 0.0 0.0 0.0 0.0 4.0 11.5 #> 87 87 0.0 0.0 0.0 0.0 0.0 4.0 11.5 #> 88 88 0.0 0.0 0.0 0.0 0.0 4.0 11.5 #> 89 89 0.0 0.0 0.0 0.0 0.0 4.0 11.5 #> 90 90 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 #> 92 92 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 #> 94 94 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 #> 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 ppiYEM2009[ppiYEM2009$score == ppiScore, ]
#> score nl100 nlFood extreme ppp125 ppp250 ppp300 ppp400 #> 50 50 3.9 0.3 0.6 0.3 12.5 22.4 46
# Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiYEM2009, score == ppiScore)
#> score nl100 nlFood extreme ppp125 ppp250 ppp300 ppp400 #> 50 50 3.9 0.3 0.6 0.3 12.5 22.4 46
# Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiYEM2009[ppiYEM2009$score == ppiScore, "nl100"]
#> [1] 3.9