Poverty Probability Index (PPI) lookup table for Brazil
ppiBRA2010
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)
# 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 #> 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 #> [ reached getOption("max.print") -- omitted 1 row ]# 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