Poverty Probability Index (PPI) lookup table for Mexico using legacy definitions
Source:R/04_data.R
ppiMEX2017.RdPoverty Probability Index (PPI) lookup table for Mexico using legacy definitions
Format
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)
Examples
# 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