Poverty Probability Index (PPI) lookup table for Vietnam
ppiVNM2009
A data frame with 8 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nlFoodFood poverty line
extremeUSAID extreme poverty line
ppp125Below $1.25 per day purchasing power parity (2005)
ppp175Below $1.75 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
molisaMOLISA poverty line
# Access Vietnam PPI table ppiVNM2009#> score nl100 nlFood extreme ppp125 ppp175 ppp250 molisa #> 0 0 93.0 78.9 78.9 93.0 100.0 100.0 83.1 #> 1 1 93.0 78.9 78.9 93.0 100.0 100.0 83.1 #> 2 2 93.0 78.9 78.9 93.0 100.0 100.0 83.1 #> 3 3 93.0 78.9 78.9 93.0 100.0 100.0 83.1 #> 4 4 93.0 78.9 78.9 93.0 100.0 100.0 83.1 #> 5 5 90.0 78.5 68.1 90.0 96.5 100.0 90.0 #> 6 6 90.0 78.5 68.1 90.0 96.5 100.0 90.0 #> 7 7 90.0 78.5 68.1 90.0 96.5 100.0 90.0 #> 8 8 90.0 78.5 68.1 90.0 96.5 100.0 90.0 #> 9 9 90.0 78.5 68.1 90.0 96.5 100.0 90.0 #> 10 10 74.5 60.9 52.4 84.7 97.7 100.0 67.7 #> 11 11 74.5 60.9 52.4 84.7 97.7 100.0 67.7 #> 12 12 74.5 60.9 52.4 84.7 97.7 100.0 67.7 #> 13 13 74.5 60.9 52.4 84.7 97.7 100.0 67.7 #> 14 14 74.5 60.9 52.4 84.7 97.7 100.0 67.7 #> 15 15 70.9 52.4 37.9 79.2 96.1 100.0 67.8 #> 16 16 70.9 52.4 37.9 79.2 96.1 100.0 67.8 #> 17 17 70.9 52.4 37.9 79.2 96.1 100.0 67.8 #> 18 18 70.9 52.4 37.9 79.2 96.1 100.0 67.8 #> 19 19 70.9 52.4 37.9 79.2 96.1 100.0 67.8 #> 20 20 55.4 30.7 26.8 65.5 89.4 96.7 47.5 #> 21 21 55.4 30.7 26.8 65.5 89.4 96.7 47.5 #> 22 22 55.4 30.7 26.8 65.5 89.4 96.7 47.5 #> 23 23 55.4 30.7 26.8 65.5 89.4 96.7 47.5 #> 24 24 55.4 30.7 26.8 65.5 89.4 96.7 47.5 #> 25 25 35.2 15.4 12.2 44.0 79.5 95.6 26.6 #> 26 26 35.2 15.4 12.2 44.0 79.5 95.6 26.6 #> 27 27 35.2 15.4 12.2 44.0 79.5 95.6 26.6 #> 28 28 35.2 15.4 12.2 44.0 79.5 95.6 26.6 #> 29 29 35.2 15.4 12.2 44.0 79.5 95.6 26.6 #> 30 30 33.0 17.0 13.2 43.4 82.0 95.0 27.1 #> 31 31 33.0 17.0 13.2 43.4 82.0 95.0 27.1 #> 32 32 33.0 17.0 13.2 43.4 82.0 95.0 27.1 #> 33 33 33.0 17.0 13.2 43.4 82.0 95.0 27.1 #> 34 34 33.0 17.0 13.2 43.4 82.0 95.0 27.1 #> 35 35 20.8 10.2 8.3 31.1 70.3 91.2 15.7 #> 36 36 20.8 10.2 8.3 31.1 70.3 91.2 15.7 #> 37 37 20.8 10.2 8.3 31.1 70.3 91.2 15.7 #> 38 38 20.8 10.2 8.3 31.1 70.3 91.2 15.7 #> 39 39 20.8 10.2 8.3 31.1 70.3 91.2 15.7 #> 40 40 10.8 4.7 4.3 17.8 52.0 86.6 8.9 #> 41 41 10.8 4.7 4.3 17.8 52.0 86.6 8.9 #> 42 42 10.8 4.7 4.3 17.8 52.0 86.6 8.9 #> 43 43 10.8 4.7 4.3 17.8 52.0 86.6 8.9 #> 44 44 10.8 4.7 4.3 17.8 52.0 86.6 8.9 #> 45 45 4.9 0.9 0.7 11.7 42.8 75.8 4.5 #> 46 46 4.9 0.9 0.7 11.7 42.8 75.8 4.5 #> 47 47 4.9 0.9 0.7 11.7 42.8 75.8 4.5 #> 48 48 4.9 0.9 0.7 11.7 42.8 75.8 4.5 #> 49 49 4.9 0.9 0.7 11.7 42.8 75.8 4.5 #> 50 50 3.3 0.4 0.8 4.1 25.2 64.9 3.7 #> 51 51 3.3 0.4 0.8 4.1 25.2 64.9 3.7 #> 52 52 3.3 0.4 0.8 4.1 25.2 64.9 3.7 #> 53 53 3.3 0.4 0.8 4.1 25.2 64.9 3.7 #> 54 54 3.3 0.4 0.8 4.1 25.2 64.9 3.7 #> 55 55 1.2 0.9 0.9 1.9 16.4 57.1 0.9 #> 56 56 1.2 0.9 0.9 1.9 16.4 57.1 0.9 #> 57 57 1.2 0.9 0.9 1.9 16.4 57.1 0.9 #> 58 58 1.2 0.9 0.9 1.9 16.4 57.1 0.9 #> 59 59 1.2 0.9 0.9 1.9 16.4 57.1 0.9 #> 60 60 1.2 0.0 0.0 2.2 14.1 49.4 2.3 #> 61 61 1.2 0.0 0.0 2.2 14.1 49.4 2.3 #> 62 62 1.2 0.0 0.0 2.2 14.1 49.4 2.3 #> 63 63 1.2 0.0 0.0 2.2 14.1 49.4 2.3 #> 64 64 1.2 0.0 0.0 2.2 14.1 49.4 2.3 #> 65 65 0.5 0.5 0.0 0.5 10.8 48.5 1.0 #> 66 66 0.5 0.5 0.0 0.5 10.8 48.5 1.0 #> 67 67 0.5 0.5 0.0 0.5 10.8 48.5 1.0 #> 68 68 0.5 0.5 0.0 0.5 10.8 48.5 1.0 #> 69 69 0.5 0.5 0.0 0.5 10.8 48.5 1.0 #> 70 70 0.5 0.5 0.5 0.5 5.2 32.7 0.5 #> 71 71 0.5 0.5 0.5 0.5 5.2 32.7 0.5 #> 72 72 0.5 0.5 0.5 0.5 5.2 32.7 0.5 #> 73 73 0.5 0.5 0.5 0.5 5.2 32.7 0.5 #> 74 74 0.5 0.5 0.5 0.5 5.2 32.7 0.5 #> 75 75 0.0 0.0 0.0 0.0 3.6 19.0 1.2 #> 76 76 0.0 0.0 0.0 0.0 3.6 19.0 1.2 #> 77 77 0.0 0.0 0.0 0.0 3.6 19.0 1.2 #> 78 78 0.0 0.0 0.0 0.0 3.6 19.0 1.2 #> 79 79 0.0 0.0 0.0 0.0 3.6 19.0 1.2 #> 80 80 0.0 0.0 0.0 0.0 0.5 8.1 0.0 #> 81 81 0.0 0.0 0.0 0.0 0.5 8.1 0.0 #> 82 82 0.0 0.0 0.0 0.0 0.5 8.1 0.0 #> 83 83 0.0 0.0 0.0 0.0 0.5 8.1 0.0 #> 84 84 0.0 0.0 0.0 0.0 0.5 8.1 0.0 #> 85 85 0.0 0.0 0.0 0.0 0.0 7.2 0.0 #> 86 86 0.0 0.0 0.0 0.0 0.0 7.2 0.0 #> 87 87 0.0 0.0 0.0 0.0 0.0 7.2 0.0 #> 88 88 0.0 0.0 0.0 0.0 0.0 7.2 0.0 #> 89 89 0.0 0.0 0.0 0.0 0.0 7.2 0.0 #> 90 90 0.0 0.0 0.0 0.0 0.0 0.8 0.0 #> 91 91 0.0 0.0 0.0 0.0 0.0 0.8 0.0 #> 92 92 0.0 0.0 0.0 0.0 0.0 0.8 0.0 #> 93 93 0.0 0.0 0.0 0.0 0.0 0.8 0.0 #> 94 94 0.0 0.0 0.0 0.0 0.0 0.8 0.0 #> 95 95 0.0 0.0 0.0 0.0 0.0 1.4 0.0 #> 96 96 0.0 0.0 0.0 0.0 0.0 1.4 0.0 #> 97 97 0.0 0.0 0.0 0.0 0.0 1.4 0.0 #> 98 98 0.0 0.0 0.0 0.0 0.0 1.4 0.0 #> 99 99 0.0 0.0 0.0 0.0 0.0 1.4 0.0 #> 100 100 0.0 0.0 0.0 0.0 0.0 1.4 0.0# Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiVNM2009[ppiVNM2009$score == ppiScore, ]#> score nl100 nlFood extreme ppp125 ppp175 ppp250 molisa #> 50 50 3.3 0.4 0.8 4.1 25.2 64.9 3.7# Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiVNM2009, score == ppiScore)#> score nl100 nlFood extreme ppp125 ppp175 ppp250 molisa #> 50 50 3.3 0.4 0.8 4.1 25.2 64.9 3.7# 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 ppiVNM2009[ppiVNM2009$score == ppiScore, "nl100"]#> [1] 3.3