Poverty Probability Index (PPI) lookup table for Mexico using legacy definitions
ppiMEX2017
A data frame with 8 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nlCapabilityCapabilities
nl100National poverty line (100%)
nl125National poverty line (125%)
nl150National poverty line (150%)
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
# Access Mexico PPI table ppiMEX2017#> score nlFood nlCapability nl100 nl125 nl150 ppp125 ppp250 #> 0 0 84.5 92.7 98.6 100.0 100.0 25.2 69.5 #> 1 1 84.5 92.7 98.6 100.0 100.0 25.2 69.5 #> 2 2 84.5 92.7 98.6 100.0 100.0 25.2 69.5 #> 3 3 84.5 92.7 98.6 100.0 100.0 25.2 69.5 #> 4 4 84.5 92.7 98.6 100.0 100.0 25.2 69.5 #> 5 5 77.0 86.2 97.4 100.0 100.0 14.8 55.3 #> 6 6 77.0 86.2 97.4 100.0 100.0 14.8 55.3 #> 7 7 77.0 86.2 97.4 100.0 100.0 14.8 55.3 #> 8 8 77.0 86.2 97.4 100.0 100.0 14.8 55.3 #> 9 9 77.0 86.2 97.4 100.0 100.0 14.8 55.3 #> 10 10 66.6 75.1 96.5 99.5 99.8 7.4 45.8 #> 11 11 66.6 75.1 96.5 99.5 99.8 7.4 45.8 #> 12 12 66.6 75.1 96.5 99.5 99.8 7.4 45.8 #> 13 13 66.6 75.1 96.5 99.5 99.8 7.4 45.8 #> 14 14 66.6 75.1 96.5 99.5 99.8 7.4 45.8 #> 15 15 58.1 70.5 92.0 98.0 99.5 4.9 36.3 #> 16 16 58.1 70.5 92.0 98.0 99.5 4.9 36.3 #> 17 17 58.1 70.5 92.0 98.0 99.5 4.9 36.3 #> 18 18 58.1 70.5 92.0 98.0 99.5 4.9 36.3 #> 19 19 58.1 70.5 92.0 98.0 99.5 4.9 36.3 #> 20 20 45.9 58.3 89.7 96.0 98.0 2.6 24.6 #> 21 21 45.9 58.3 89.7 96.0 98.0 2.6 24.6 #> 22 22 45.9 58.3 89.7 96.0 98.0 2.6 24.6 #> 23 23 45.9 58.3 89.7 96.0 98.0 2.6 24.6 #> 24 24 45.9 58.3 89.7 96.0 98.0 2.6 24.6 #> 25 25 35.7 49.9 84.7 93.1 95.4 2.2 15.9 #> 26 26 35.7 49.9 84.7 93.1 95.4 2.2 15.9 #> 27 27 35.7 49.9 84.7 93.1 95.4 2.2 15.9 #> 28 28 35.7 49.9 84.7 93.1 95.4 2.2 15.9 #> 29 29 35.7 49.9 84.7 93.1 95.4 2.2 15.9 #> 30 30 28.6 41.7 76.2 89.0 94.4 2.2 12.8 #> 31 31 28.6 41.7 76.2 89.0 94.4 2.2 12.8 #> 32 32 28.6 41.7 76.2 89.0 94.4 2.2 12.8 #> 33 33 28.6 41.7 76.2 89.0 94.4 2.2 12.8 #> 34 34 28.6 41.7 76.2 89.0 94.4 2.2 12.8 #> 35 35 21.6 34.1 71.3 83.4 91.3 0.9 9.1 #> 36 36 21.6 34.1 71.3 83.4 91.3 0.9 9.1 #> 37 37 21.6 34.1 71.3 83.4 91.3 0.9 9.1 #> 38 38 21.6 34.1 71.3 83.4 91.3 0.9 9.1 #> 39 39 21.6 34.1 71.3 83.4 91.3 0.9 9.1 #> 40 40 13.1 27.6 59.8 75.9 85.1 0.8 5.7 #> 41 41 13.1 27.6 59.8 75.9 85.1 0.8 5.7 #> 42 42 13.1 27.6 59.8 75.9 85.1 0.8 5.7 #> 43 43 13.1 27.6 59.8 75.9 85.1 0.8 5.7 #> 44 44 13.1 27.6 59.8 75.9 85.1 0.8 5.7 #> 45 45 10.2 18.7 49.6 68.7 79.0 0.6 3.7 #> 46 46 10.2 18.7 49.6 68.7 79.0 0.6 3.7 #> 47 47 10.2 18.7 49.6 68.7 79.0 0.6 3.7 #> 48 48 10.2 18.7 49.6 68.7 79.0 0.6 3.7 #> 49 49 10.2 18.7 49.6 68.7 79.0 0.6 3.7 #> 50 50 8.5 14.5 42.2 61.3 72.9 0.6 3.2 #> 51 51 8.5 14.5 42.2 61.3 72.9 0.6 3.2 #> 52 52 8.5 14.5 42.2 61.3 72.9 0.6 3.2 #> 53 53 8.5 14.5 42.2 61.3 72.9 0.6 3.2 #> 54 54 8.5 14.5 42.2 61.3 72.9 0.6 3.2 #> 55 55 5.8 10.0 30.4 47.2 63.8 0.4 2.5 #> 56 56 5.8 10.0 30.4 47.2 63.8 0.4 2.5 #> 57 57 5.8 10.0 30.4 47.2 63.8 0.4 2.5 #> 58 58 5.8 10.0 30.4 47.2 63.8 0.4 2.5 #> 59 59 5.8 10.0 30.4 47.2 63.8 0.4 2.5 #> 60 60 3.1 6.4 25.1 37.7 51.2 0.1 1.2 #> 61 61 3.1 6.4 25.1 37.7 51.2 0.1 1.2 #> 62 62 3.1 6.4 25.1 37.7 51.2 0.1 1.2 #> 63 63 3.1 6.4 25.1 37.7 51.2 0.1 1.2 #> 64 64 3.1 6.4 25.1 37.7 51.2 0.1 1.2 #> 65 65 2.3 4.3 20.6 31.0 42.6 0.1 0.5 #> 66 66 2.3 4.3 20.6 31.0 42.6 0.1 0.5 #> 67 67 2.3 4.3 20.6 31.0 42.6 0.1 0.5 #> 68 68 2.3 4.3 20.6 31.0 42.6 0.1 0.5 #> 69 69 2.3 4.3 20.6 31.0 42.6 0.1 0.5 #> 70 70 1.0 2.4 10.5 18.9 31.1 0.1 0.4 #> 71 71 1.0 2.4 10.5 18.9 31.1 0.1 0.4 #> 72 72 1.0 2.4 10.5 18.9 31.1 0.1 0.4 #> 73 73 1.0 2.4 10.5 18.9 31.1 0.1 0.4 #> 74 74 1.0 2.4 10.5 18.9 31.1 0.1 0.4 #> 75 75 0.9 1.6 7.0 14.0 23.4 0.1 0.4 #> 76 76 0.9 1.6 7.0 14.0 23.4 0.1 0.4 #> 77 77 0.9 1.6 7.0 14.0 23.4 0.1 0.4 #> 78 78 0.9 1.6 7.0 14.0 23.4 0.1 0.4 #> 79 79 0.9 1.6 7.0 14.0 23.4 0.1 0.4 #> 80 80 0.4 1.0 5.5 11.3 17.9 0.0 0.3 #> 81 81 0.4 1.0 5.5 11.3 17.9 0.0 0.3 #> 82 82 0.4 1.0 5.5 11.3 17.9 0.0 0.3 #> 83 83 0.4 1.0 5.5 11.3 17.9 0.0 0.3 #> 84 84 0.4 1.0 5.5 11.3 17.9 0.0 0.3 #> 85 85 0.4 0.9 4.9 8.3 12.3 0.0 0.3 #> 86 86 0.4 0.9 4.9 8.3 12.3 0.0 0.3 #> 87 87 0.4 0.9 4.9 8.3 12.3 0.0 0.3 #> 88 88 0.4 0.9 4.9 8.3 12.3 0.0 0.3 #> 89 89 0.4 0.9 4.9 8.3 12.3 0.0 0.3 #> 90 90 0.3 0.7 2.9 5.3 8.9 0.0 0.2 #> 91 91 0.3 0.7 2.9 5.3 8.9 0.0 0.2 #> 92 92 0.3 0.7 2.9 5.3 8.9 0.0 0.2 #> 93 93 0.3 0.7 2.9 5.3 8.9 0.0 0.2 #> 94 94 0.3 0.7 2.9 5.3 8.9 0.0 0.2 #> 95 95 0.0 0.0 1.4 1.7 4.1 0.0 0.0 #> 96 96 0.0 0.0 1.4 1.7 4.1 0.0 0.0 #> 97 97 0.0 0.0 1.4 1.7 4.1 0.0 0.0 #> 98 98 0.0 0.0 1.4 1.7 4.1 0.0 0.0 #> 99 99 0.0 0.0 1.4 1.7 4.1 0.0 0.0 #> 100 100 0.0 0.0 1.4 1.7 4.1 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 ppiMEX2017[ppiMEX2017$score == ppiScore, ]#> score nlFood nlCapability nl100 nl125 nl150 ppp125 ppp250 #> 50 50 8.5 14.5 42.2 61.3 72.9 0.6 3.2# Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMEX2017, score == ppiScore)#> score nlFood nlCapability nl100 nl125 nl150 ppp125 ppp250 #> 50 50 8.5 14.5 42.2 61.3 72.9 0.6 3.2# 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 ppiMEX2017[ppiMEX2017$score == ppiScore, "nl100"]#> [1] 42.2