Poverty Probability Index (PPI) lookup table for Vietnam
Format
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
Examples
# 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