Poverty Probability Index (PPI) lookup table for Brazil
Format
A data frame with 10 columns and 101 rows:
scorePPI score
belowHalfWageBelow the half minimum wage line
belowQtrWageBelow the quarter minimum wage line
belowOneWageBelow the one minimum wage line
belowTwoWageBelow the two minimum wage line
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 Brazil PPI table
ppiBRA2010
#> score belowHalfWage belowQtrWage belowOneWage belowTwoWage extreme ppp125
#> 0 0 95.0 71.7 99.5 100.0 80.2 46.4
#> 1 1 95.0 71.7 99.5 100.0 80.2 46.4
#> 2 2 95.0 71.7 99.5 100.0 80.2 46.4
#> 3 3 95.0 71.7 99.5 100.0 80.2 46.4
#> 4 4 95.0 71.7 99.5 100.0 80.2 46.4
#> 5 5 93.4 65.4 99.6 100.0 77.2 34.2
#> 6 6 93.4 65.4 99.6 100.0 77.2 34.2
#> 7 7 93.4 65.4 99.6 100.0 77.2 34.2
#> 8 8 93.4 65.4 99.6 100.0 77.2 34.2
#> 9 9 93.4 65.4 99.6 100.0 77.2 34.2
#> 10 10 89.4 51.6 99.5 100.0 65.0 24.0
#> 11 11 89.4 51.6 99.5 100.0 65.0 24.0
#> 12 12 89.4 51.6 99.5 100.0 65.0 24.0
#> 13 13 89.4 51.6 99.5 100.0 65.0 24.0
#> 14 14 89.4 51.6 99.5 100.0 65.0 24.0
#> 15 15 81.1 35.0 98.5 99.9 47.0 14.0
#> 16 16 81.1 35.0 98.5 99.9 47.0 14.0
#> 17 17 81.1 35.0 98.5 99.9 47.0 14.0
#> 18 18 81.1 35.0 98.5 99.9 47.0 14.0
#> 19 19 81.1 35.0 98.5 99.9 47.0 14.0
#> 20 20 68.7 24.6 96.2 99.7 36.1 10.2
#> 21 21 68.7 24.6 96.2 99.7 36.1 10.2
#> 22 22 68.7 24.6 96.2 99.7 36.1 10.2
#> 23 23 68.7 24.6 96.2 99.7 36.1 10.2
#> 24 24 68.7 24.6 96.2 99.7 36.1 10.2
#> 25 25 54.2 16.1 92.2 99.4 23.2 7.1
#> 26 26 54.2 16.1 92.2 99.4 23.2 7.1
#> 27 27 54.2 16.1 92.2 99.4 23.2 7.1
#> 28 28 54.2 16.1 92.2 99.4 23.2 7.1
#> 29 29 54.2 16.1 92.2 99.4 23.2 7.1
#> 30 30 41.1 10.5 85.0 98.7 15.2 4.6
#> 31 31 41.1 10.5 85.0 98.7 15.2 4.6
#> 32 32 41.1 10.5 85.0 98.7 15.2 4.6
#> 33 33 41.1 10.5 85.0 98.7 15.2 4.6
#> 34 34 41.1 10.5 85.0 98.7 15.2 4.6
#> 35 35 26.1 6.2 75.3 96.5 8.3 3.3
#> 36 36 26.1 6.2 75.3 96.5 8.3 3.3
#> 37 37 26.1 6.2 75.3 96.5 8.3 3.3
#> 38 38 26.1 6.2 75.3 96.5 8.3 3.3
#> 39 39 26.1 6.2 75.3 96.5 8.3 3.3
#> 40 40 17.4 3.9 61.8 93.7 5.1 2.0
#> 41 41 17.4 3.9 61.8 93.7 5.1 2.0
#> 42 42 17.4 3.9 61.8 93.7 5.1 2.0
#> 43 43 17.4 3.9 61.8 93.7 5.1 2.0
#> 44 44 17.4 3.9 61.8 93.7 5.1 2.0
#> 45 45 12.4 2.6 52.0 89.6 3.1 1.9
#> 46 46 12.4 2.6 52.0 89.6 3.1 1.9
#> 47 47 12.4 2.6 52.0 89.6 3.1 1.9
#> 48 48 12.4 2.6 52.0 89.6 3.1 1.9
#> 49 49 12.4 2.6 52.0 89.6 3.1 1.9
#> 50 50 6.9 1.7 35.6 82.1 2.1 1.5
#> 51 51 6.9 1.7 35.6 82.1 2.1 1.5
#> 52 52 6.9 1.7 35.6 82.1 2.1 1.5
#> 53 53 6.9 1.7 35.6 82.1 2.1 1.5
#> 54 54 6.9 1.7 35.6 82.1 2.1 1.5
#> 55 55 3.4 1.2 24.4 69.4 1.2 1.0
#> 56 56 3.4 1.2 24.4 69.4 1.2 1.0
#> 57 57 3.4 1.2 24.4 69.4 1.2 1.0
#> 58 58 3.4 1.2 24.4 69.4 1.2 1.0
#> 59 59 3.4 1.2 24.4 69.4 1.2 1.0
#> 60 60 2.1 1.1 15.4 58.8 1.2 1.1
#> 61 61 2.1 1.1 15.4 58.8 1.2 1.1
#> 62 62 2.1 1.1 15.4 58.8 1.2 1.1
#> 63 63 2.1 1.1 15.4 58.8 1.2 1.1
#> 64 64 2.1 1.1 15.4 58.8 1.2 1.1
#> 65 65 1.0 0.4 8.9 42.9 0.4 0.4
#> 66 66 1.0 0.4 8.9 42.9 0.4 0.4
#> 67 67 1.0 0.4 8.9 42.9 0.4 0.4
#> 68 68 1.0 0.4 8.9 42.9 0.4 0.4
#> 69 69 1.0 0.4 8.9 42.9 0.4 0.4
#> 70 70 1.1 0.6 3.9 29.8 0.6 0.6
#> 71 71 1.1 0.6 3.9 29.8 0.6 0.6
#> 72 72 1.1 0.6 3.9 29.8 0.6 0.6
#> 73 73 1.1 0.6 3.9 29.8 0.6 0.6
#> 74 74 1.1 0.6 3.9 29.8 0.6 0.6
#> 75 75 0.1 0.0 1.4 19.4 0.0 0.0
#> 76 76 0.1 0.0 1.4 19.4 0.0 0.0
#> 77 77 0.1 0.0 1.4 19.4 0.0 0.0
#> 78 78 0.1 0.0 1.4 19.4 0.0 0.0
#> 79 79 0.1 0.0 1.4 19.4 0.0 0.0
#> 80 80 0.1 0.0 0.8 10.3 0.0 0.0
#> 81 81 0.1 0.0 0.8 10.3 0.0 0.0
#> 82 82 0.1 0.0 0.8 10.3 0.0 0.0
#> 83 83 0.1 0.0 0.8 10.3 0.0 0.0
#> 84 84 0.1 0.0 0.8 10.3 0.0 0.0
#> 85 85 0.0 0.0 1.4 7.5 0.0 0.0
#> 86 86 0.0 0.0 1.4 7.5 0.0 0.0
#> 87 87 0.0 0.0 1.4 7.5 0.0 0.0
#> 88 88 0.0 0.0 1.4 7.5 0.0 0.0
#> 89 89 0.0 0.0 1.4 7.5 0.0 0.0
#> 90 90 0.0 0.0 0.0 5.7 0.0 0.0
#> 91 91 0.0 0.0 0.0 5.7 0.0 0.0
#> 92 92 0.0 0.0 0.0 5.7 0.0 0.0
#> 93 93 0.0 0.0 0.0 5.7 0.0 0.0
#> 94 94 0.0 0.0 0.0 5.7 0.0 0.0
#> 95 95 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
#> 97 97 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
#> 99 99 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
#> ppp250 ppp375 ppp500
#> 0 81.8 93.7 99.0
#> 1 81.8 93.7 99.0
#> 2 81.8 93.7 99.0
#> 3 81.8 93.7 99.0
#> 4 81.8 93.7 99.0
#> 5 77.8 92.0 97.4
#> 6 77.8 92.0 97.4
#> 7 77.8 92.0 97.4
#> 8 77.8 92.0 97.4
#> 9 77.8 92.0 97.4
#> 10 66.1 87.3 94.3
#> 11 66.1 87.3 94.3
#> 12 66.1 87.3 94.3
#> 13 66.1 87.3 94.3
#> 14 66.1 87.3 94.3
#> 15 49.0 76.0 90.3
#> 16 49.0 76.0 90.3
#> 17 49.0 76.0 90.3
#> 18 49.0 76.0 90.3
#> 19 49.0 76.0 90.3
#> 20 37.2 64.0 80.3
#> 21 37.2 64.0 80.3
#> 22 37.2 64.0 80.3
#> 23 37.2 64.0 80.3
#> 24 37.2 64.0 80.3
#> 25 23.9 47.6 67.5
#> 26 23.9 47.6 67.5
#> 27 23.9 47.6 67.5
#> 28 23.9 47.6 67.5
#> 29 23.9 47.6 67.5
#> 30 15.4 33.4 53.3
#> 31 15.4 33.4 53.3
#> 32 15.4 33.4 53.3
#> 33 15.4 33.4 53.3
#> 34 15.4 33.4 53.3
#> 35 8.6 19.7 37.2
#> 36 8.6 19.7 37.2
#> 37 8.6 19.7 37.2
#> 38 8.6 19.7 37.2
#> 39 8.6 19.7 37.2
#> 40 5.2 12.0 26.0
#> 41 5.2 12.0 26.0
#> 42 5.2 12.0 26.0
#> 43 5.2 12.0 26.0
#> 44 5.2 12.0 26.0
#> 45 3.2 7.8 20.1
#> 46 3.2 7.8 20.1
#> 47 3.2 7.8 20.1
#> 48 3.2 7.8 20.1
#> 49 3.2 7.8 20.1
#> 50 2.1 4.0 10.6
#> 51 2.1 4.0 10.6
#> 52 2.1 4.0 10.6
#> 53 2.1 4.0 10.6
#> 54 2.1 4.0 10.6
#> 55 1.2 2.0 5.6
#> 56 1.2 2.0 5.6
#> 57 1.2 2.0 5.6
#> 58 1.2 2.0 5.6
#> 59 1.2 2.0 5.6
#> 60 1.2 1.5 3.8
#> 61 1.2 1.5 3.8
#> 62 1.2 1.5 3.8
#> 63 1.2 1.5 3.8
#> 64 1.2 1.5 3.8
#> 65 0.4 0.7 1.8
#> 66 0.4 0.7 1.8
#> 67 0.4 0.7 1.8
#> 68 0.4 0.7 1.8
#> 69 0.4 0.7 1.8
#> 70 0.6 0.8 1.3
#> 71 0.6 0.8 1.3
#> 72 0.6 0.8 1.3
#> 73 0.6 0.8 1.3
#> 74 0.6 0.8 1.3
#> 75 0.0 0.1 0.1
#> 76 0.0 0.1 0.1
#> 77 0.0 0.1 0.1
#> 78 0.0 0.1 0.1
#> 79 0.0 0.1 0.1
#> 80 0.0 0.0 0.3
#> 81 0.0 0.0 0.3
#> 82 0.0 0.0 0.3
#> 83 0.0 0.0 0.3
#> 84 0.0 0.0 0.3
#> 85 0.0 0.0 0.0
#> 86 0.0 0.0 0.0
#> 87 0.0 0.0 0.0
#> 88 0.0 0.0 0.0
#> 89 0.0 0.0 0.0
#> 90 0.0 0.0 0.0
#> 91 0.0 0.0 0.0
#> 92 0.0 0.0 0.0
#> 93 0.0 0.0 0.0
#> 94 0.0 0.0 0.0
#> 95 0.0 0.0 0.0
#> 96 0.0 0.0 0.0
#> 97 0.0 0.0 0.0
#> 98 0.0 0.0 0.0
#> 99 0.0 0.0 0.0
#> 100 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
ppiBRA2010[ppiBRA2010$score == ppiScore, ]
#> score belowHalfWage belowQtrWage belowOneWage belowTwoWage extreme ppp125
#> 50 50 6.9 1.7 35.6 82.1 2.1 1.5
#> ppp250 ppp375 ppp500
#> 50 2.1 4 10.6
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiBRA2010, score == ppiScore)
#> score belowHalfWage belowQtrWage belowOneWage belowTwoWage extreme ppp125
#> 50 50 6.9 1.7 35.6 82.1 2.1 1.5
#> ppp250 ppp375 ppp500
#> 50 2.1 4 10.6
# 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
ppiBRA2010[ppiBRA2010$score == ppiScore, "extreme"]
#> [1] 2.1