Poverty Probability Index (PPI) lookup table for Indonesia using new poverty definitions
ppiIDN2012_a
A data frame with 9 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
extremeUSAID extreme poverty
ppp125Below $1.25 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
# Access Indonesia PPI table ppiIDN2012_a#> score nl100 nl150 nl200 extreme ppp125 ppp250 ppp190 ppp310 #> 0 0 66.3 96.1 99.0 49.8 74.2 99.6 52.5 94.9 #> 1 1 66.3 96.1 99.0 49.8 74.2 99.6 52.5 94.9 #> 2 2 66.3 96.1 99.0 49.8 74.2 99.6 52.5 94.9 #> 3 3 66.3 96.1 99.0 49.8 74.2 99.6 52.5 94.9 #> 4 4 66.3 96.1 99.0 49.8 74.2 99.6 52.5 94.9 #> 5 5 60.0 93.3 98.3 38.4 68.9 99.0 43.0 92.1 #> 6 6 60.0 93.3 98.3 38.4 68.9 99.0 43.0 92.1 #> 7 7 60.0 93.3 98.3 38.4 68.9 99.0 43.0 92.1 #> 8 8 60.0 93.3 98.3 38.4 68.9 99.0 43.0 92.1 #> 9 9 60.0 93.3 98.3 38.4 68.9 99.0 43.0 92.1 #> 10 10 48.4 87.9 97.0 28.3 57.7 98.3 31.9 85.9 #> 11 11 48.4 87.9 97.0 28.3 57.7 98.3 31.9 85.9 #> 12 12 48.4 87.9 97.0 28.3 57.7 98.3 31.9 85.9 #> 13 13 48.4 87.9 97.0 28.3 57.7 98.3 31.9 85.9 #> 14 14 48.4 87.9 97.0 28.3 57.7 98.3 31.9 85.9 #> 15 15 34.1 81.8 95.1 18.0 45.5 96.5 20.1 78.7 #> 16 16 34.1 81.8 95.1 18.0 45.5 96.5 20.1 78.7 #> 17 17 34.1 81.8 95.1 18.0 45.5 96.5 20.1 78.7 #> 18 18 34.1 81.8 95.1 18.0 45.5 96.5 20.1 78.7 #> 19 19 34.1 81.8 95.1 18.0 45.5 96.5 20.1 78.7 #> 20 20 25.2 76.2 93.4 12.6 35.3 95.2 14.2 72.1 #> 21 21 25.2 76.2 93.4 12.6 35.3 95.2 14.2 72.1 #> 22 22 25.2 76.2 93.4 12.6 35.3 95.2 14.2 72.1 #> 23 23 25.2 76.2 93.4 12.6 35.3 95.2 14.2 72.1 #> 24 24 25.2 76.2 93.4 12.6 35.3 95.2 14.2 72.1 #> 25 25 17.3 65.5 88.1 7.3 24.7 91.5 8.6 60.6 #> 26 26 17.3 65.5 88.1 7.3 24.7 91.5 8.6 60.6 #> 27 27 17.3 65.5 88.1 7.3 24.7 91.5 8.6 60.6 #> 28 28 17.3 65.5 88.1 7.3 24.7 91.5 8.6 60.6 #> 29 29 17.3 65.5 88.1 7.3 24.7 91.5 8.6 60.6 #> 30 30 10.3 54.0 82.6 4.0 16.2 87.7 4.7 48.9 #> 31 31 10.3 54.0 82.6 4.0 16.2 87.7 4.7 48.9 #> 32 32 10.3 54.0 82.6 4.0 16.2 87.7 4.7 48.9 #> 33 33 10.3 54.0 82.6 4.0 16.2 87.7 4.7 48.9 #> 34 34 10.3 54.0 82.6 4.0 16.2 87.7 4.7 48.9 #> 35 35 5.8 40.7 72.9 1.9 9.4 79.7 2.3 35.5 #> 36 36 5.8 40.7 72.9 1.9 9.4 79.7 2.3 35.5 #> 37 37 5.8 40.7 72.9 1.9 9.4 79.7 2.3 35.5 #> 38 38 5.8 40.7 72.9 1.9 9.4 79.7 2.3 35.5 #> 39 39 5.8 40.7 72.9 1.9 9.4 79.7 2.3 35.5 #> 40 40 3.2 27.9 60.6 1.1 5.3 68.4 1.2 23.7 #> 41 41 3.2 27.9 60.6 1.1 5.3 68.4 1.2 23.7 #> 42 42 3.2 27.9 60.6 1.1 5.3 68.4 1.2 23.7 #> 43 43 3.2 27.9 60.6 1.1 5.3 68.4 1.2 23.7 #> 44 44 3.2 27.9 60.6 1.1 5.3 68.4 1.2 23.7 #> 45 45 1.4 17.4 46.1 0.5 2.6 54.7 0.6 14.3 #> 46 46 1.4 17.4 46.1 0.5 2.6 54.7 0.6 14.3 #> 47 47 1.4 17.4 46.1 0.5 2.6 54.7 0.6 14.3 #> 48 48 1.4 17.4 46.1 0.5 2.6 54.7 0.6 14.3 #> 49 49 1.4 17.4 46.1 0.5 2.6 54.7 0.6 14.3 #> 50 50 0.6 9.9 32.4 0.1 1.3 40.1 0.2 7.8 #> 51 51 0.6 9.9 32.4 0.1 1.3 40.1 0.2 7.8 #> 52 52 0.6 9.9 32.4 0.1 1.3 40.1 0.2 7.8 #> 53 53 0.6 9.9 32.4 0.1 1.3 40.1 0.2 7.8 #> 54 54 0.6 9.9 32.4 0.1 1.3 40.1 0.2 7.8 #> 55 55 0.2 5.2 20.7 0.0 0.5 26.9 0.1 4.1 #> 56 56 0.2 5.2 20.7 0.0 0.5 26.9 0.1 4.1 #> 57 57 0.2 5.2 20.7 0.0 0.5 26.9 0.1 4.1 #> 58 58 0.2 5.2 20.7 0.0 0.5 26.9 0.1 4.1 #> 59 59 0.2 5.2 20.7 0.0 0.5 26.9 0.1 4.1 #> 60 60 0.1 2.9 12.8 0.0 0.1 17.6 0.0 2.4 #> 61 61 0.1 2.9 12.8 0.0 0.1 17.6 0.0 2.4 #> 62 62 0.1 2.9 12.8 0.0 0.1 17.6 0.0 2.4 #> 63 63 0.1 2.9 12.8 0.0 0.1 17.6 0.0 2.4 #> 64 64 0.1 2.9 12.8 0.0 0.1 17.6 0.0 2.4 #> 65 65 0.0 1.3 6.4 0.0 0.1 9.1 0.0 1.1 #> 66 66 0.0 1.3 6.4 0.0 0.1 9.1 0.0 1.1 #> 67 67 0.0 1.3 6.4 0.0 0.1 9.1 0.0 1.1 #> 68 68 0.0 1.3 6.4 0.0 0.1 9.1 0.0 1.1 #> 69 69 0.0 1.3 6.4 0.0 0.1 9.1 0.0 1.1 #> 70 70 0.0 0.9 4.8 0.0 0.0 6.9 0.0 0.6 #> 71 71 0.0 0.9 4.8 0.0 0.0 6.9 0.0 0.6 #> 72 72 0.0 0.9 4.8 0.0 0.0 6.9 0.0 0.6 #> 73 73 0.0 0.9 4.8 0.0 0.0 6.9 0.0 0.6 #> 74 74 0.0 0.9 4.8 0.0 0.0 6.9 0.0 0.6 #> 75 75 0.0 0.4 2.5 0.0 0.0 3.7 0.0 0.4 #> 76 76 0.0 0.4 2.5 0.0 0.0 3.7 0.0 0.4 #> 77 77 0.0 0.4 2.5 0.0 0.0 3.7 0.0 0.4 #> 78 78 0.0 0.4 2.5 0.0 0.0 3.7 0.0 0.4 #> 79 79 0.0 0.4 2.5 0.0 0.0 3.7 0.0 0.4 #> 80 80 0.0 0.2 0.2 0.0 0.0 0.2 0.0 0.1 #> 81 81 0.0 0.2 0.2 0.0 0.0 0.2 0.0 0.1 #> 82 82 0.0 0.2 0.2 0.0 0.0 0.2 0.0 0.1 #> 83 83 0.0 0.2 0.2 0.0 0.0 0.2 0.0 0.1 #> 84 84 0.0 0.2 0.2 0.0 0.0 0.2 0.0 0.1 #> 85 85 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 86 86 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 87 87 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 88 88 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 89 89 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 #> 90 90 0.0 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 0.0 #> 92 92 0.0 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 0.0 #> 94 94 0.0 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 0.0 #> 96 96 0.0 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 0.0 #> 98 98 0.0 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 0.0 #> 100 100 0.0 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 ppiIDN2012_a[ppiIDN2012_a$score == ppiScore, ]#> score nl100 nl150 nl200 extreme ppp125 ppp250 ppp190 ppp310 #> 50 50 0.6 9.9 32.4 0.1 1.3 40.1 0.2 7.8# Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiIDN2012_a, score == ppiScore)#> score nl100 nl150 nl200 extreme ppp125 ppp250 ppp190 ppp310 #> 50 50 0.6 9.9 32.4 0.1 1.3 40.1 0.2 7.8# 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 ppiIDN2012_a[ppiIDN2012_a$score == ppiScore, "extreme"]#> [1] 0.1