Poverty Probability Index (PPI) lookup table for Rwanda

ppiRWA2016

Format

A data frame with 11 columns and 101 rows:

score

PPI score

nlFood

Food poverty line

nl100

National poverty line (100%)

nl150

National poverty line (150%)

nl200

National poverty line (200%)

half100

Poorest half below 100% national

ppp125

Below $1.25 per day purchasing power parity (2005)

ppp200

Below $2.00 per day purchasing power parity (2005)

ppp250

Below $2.50 per day purchasing power parity (2005)

ppp500

Below $5.00 per day purchasing power parity (2005)

ppp844

Below $8.44 per day purchasing power parity (2005)

Source

www.povertyindex.org

Examples

# Access Rwanda PPI table ppiRWA2016
#> score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp844 #> 0 0 98.3 99.5 100.0 100.0 98.2 100.0 100.0 100.0 100.0 100.0 #> 1 1 98.3 99.5 100.0 100.0 98.2 100.0 100.0 100.0 100.0 100.0 #> 2 2 98.3 99.5 100.0 100.0 98.2 100.0 100.0 100.0 100.0 100.0 #> 3 3 98.3 99.5 100.0 100.0 98.2 100.0 100.0 100.0 100.0 100.0 #> 4 4 98.3 99.5 100.0 100.0 98.2 100.0 100.0 100.0 100.0 100.0 #> 5 5 77.2 93.4 98.1 99.2 75.6 97.5 99.2 99.8 100.0 100.0 #> 6 6 77.2 93.4 98.1 99.2 75.6 97.5 99.2 99.8 100.0 100.0 #> 7 7 77.2 93.4 98.1 99.2 75.6 97.5 99.2 99.8 100.0 100.0 #> 8 8 77.2 93.4 98.1 99.2 75.6 97.5 99.2 99.8 100.0 100.0 #> 9 9 77.2 93.4 98.1 99.2 75.6 97.5 99.2 99.8 100.0 100.0 #> 10 10 72.0 90.3 97.7 99.1 69.7 96.7 99.1 99.7 100.0 100.0 #> 11 11 72.0 90.3 97.7 99.1 69.7 96.7 99.1 99.7 100.0 100.0 #> 12 12 72.0 90.3 97.7 99.1 69.7 96.7 99.1 99.7 100.0 100.0 #> 13 13 72.0 90.3 97.7 99.1 69.7 96.7 99.1 99.7 100.0 100.0 #> 14 14 72.0 90.3 97.7 99.1 69.7 96.7 99.1 99.7 100.0 100.0 #> 15 15 57.3 83.2 95.6 98.3 56.3 94.3 98.6 99.6 100.0 100.0 #> 16 16 57.3 83.2 95.6 98.3 56.3 94.3 98.6 99.6 100.0 100.0 #> 17 17 57.3 83.2 95.6 98.3 56.3 94.3 98.6 99.6 100.0 100.0 #> 18 18 57.3 83.2 95.6 98.3 56.3 94.3 98.6 99.6 100.0 100.0 #> 19 19 57.3 83.2 95.6 98.3 56.3 94.3 98.6 99.6 100.0 100.0 #> 20 20 38.7 71.2 91.0 96.9 38.6 88.2 97.4 99.1 100.0 100.0 #> 21 21 38.7 71.2 91.0 96.9 38.6 88.2 97.4 99.1 100.0 100.0 #> 22 22 38.7 71.2 91.0 96.9 38.6 88.2 97.4 99.1 100.0 100.0 #> 23 23 38.7 71.2 91.0 96.9 38.6 88.2 97.4 99.1 100.0 100.0 #> 24 24 38.7 71.2 91.0 96.9 38.6 88.2 97.4 99.1 100.0 100.0 #> 25 25 28.8 63.0 90.6 96.1 28.3 85.1 96.9 98.7 99.9 100.0 #> 26 26 28.8 63.0 90.6 96.1 28.3 85.1 96.9 98.7 99.9 100.0 #> 27 27 28.8 63.0 90.6 96.1 28.3 85.1 96.9 98.7 99.9 100.0 #> 28 28 28.8 63.0 90.6 96.1 28.3 85.1 96.9 98.7 99.9 100.0 #> 29 29 28.8 63.0 90.6 96.1 28.3 85.1 96.9 98.7 99.9 100.0 #> 30 30 19.3 50.2 83.0 94.4 18.2 76.6 95.9 98.3 99.9 100.0 #> 31 31 19.3 50.2 83.0 94.4 18.2 76.6 95.9 98.3 99.9 100.0 #> 32 32 19.3 50.2 83.0 94.4 18.2 76.6 95.9 98.3 99.9 100.0 #> 33 33 19.3 50.2 83.0 94.4 18.2 76.6 95.9 98.3 99.9 100.0 #> 34 34 19.3 50.2 83.0 94.4 18.2 76.6 95.9 98.3 99.9 100.0 #> 35 35 14.0 34.7 70.5 87.1 12.6 60.4 90.6 95.7 99.9 100.0 #> 36 36 14.0 34.7 70.5 87.1 12.6 60.4 90.6 95.7 99.9 100.0 #> 37 37 14.0 34.7 70.5 87.1 12.6 60.4 90.6 95.7 99.9 100.0 #> 38 38 14.0 34.7 70.5 87.1 12.6 60.4 90.6 95.7 99.9 100.0 #> 39 39 14.0 34.7 70.5 87.1 12.6 60.4 90.6 95.7 99.9 100.0 #> 40 40 9.2 27.7 58.4 78.9 6.5 50.8 83.3 91.2 99.5 99.9 #> 41 41 9.2 27.7 58.4 78.9 6.5 50.8 83.3 91.2 99.5 99.9 #> 42 42 9.2 27.7 58.4 78.9 6.5 50.8 83.3 91.2 99.5 99.9 #> 43 43 9.2 27.7 58.4 78.9 6.5 50.8 83.3 91.2 99.5 99.9 #> 44 44 9.2 27.7 58.4 78.9 6.5 50.8 83.3 91.2 99.5 99.9 #> 45 45 5.0 17.0 45.1 67.8 3.4 36.4 73.2 85.2 98.5 99.9 #> 46 46 5.0 17.0 45.1 67.8 3.4 36.4 73.2 85.2 98.5 99.9 #> 47 47 5.0 17.0 45.1 67.8 3.4 36.4 73.2 85.2 98.5 99.9 #> 48 48 5.0 17.0 45.1 67.8 3.4 36.4 73.2 85.2 98.5 99.9 #> 49 49 5.0 17.0 45.1 67.8 3.4 36.4 73.2 85.2 98.5 99.9 #> 50 50 2.7 11.0 30.5 56.3 2.0 21.2 61.5 77.2 95.7 99.9 #> 51 51 2.7 11.0 30.5 56.3 2.0 21.2 61.5 77.2 95.7 99.9 #> 52 52 2.7 11.0 30.5 56.3 2.0 21.2 61.5 77.2 95.7 99.9 #> 53 53 2.7 11.0 30.5 56.3 2.0 21.2 61.5 77.2 95.7 99.9 #> 54 54 2.7 11.0 30.5 56.3 2.0 21.2 61.5 77.2 95.7 99.9 #> 55 55 0.6 6.0 25.4 42.8 0.5 17.4 46.6 61.0 90.4 98.6 #> 56 56 0.6 6.0 25.4 42.8 0.5 17.4 46.6 61.0 90.4 98.6 #> 57 57 0.6 6.0 25.4 42.8 0.5 17.4 46.6 61.0 90.4 98.6 #> 58 58 0.6 6.0 25.4 42.8 0.5 17.4 46.6 61.0 90.4 98.6 #> 59 59 0.6 6.0 25.4 42.8 0.5 17.4 46.6 61.0 90.4 98.6 #> 60 60 0.4 2.0 14.0 27.8 0.0 7.7 31.1 44.4 80.2 94.8 #> 61 61 0.4 2.0 14.0 27.8 0.0 7.7 31.1 44.4 80.2 94.8 #> 62 62 0.4 2.0 14.0 27.8 0.0 7.7 31.1 44.4 80.2 94.8 #> 63 63 0.4 2.0 14.0 27.8 0.0 7.7 31.1 44.4 80.2 94.8 #> 64 64 0.4 2.0 14.0 27.8 0.0 7.7 31.1 44.4 80.2 94.8 #> 65 65 0.2 0.9 7.3 18.6 0.0 3.4 17.7 28.0 69.4 86.2 #> 66 66 0.2 0.9 7.3 18.6 0.0 3.4 17.7 28.0 69.4 86.2 #> 67 67 0.2 0.9 7.3 18.6 0.0 3.4 17.7 28.0 69.4 86.2 #> 68 68 0.2 0.9 7.3 18.6 0.0 3.4 17.7 28.0 69.4 86.2 #> 69 69 0.2 0.9 7.3 18.6 0.0 3.4 17.7 28.0 69.4 86.2 #> 70 70 0.0 0.0 3.6 9.9 0.0 1.8 10.1 18.2 55.6 74.3 #> 71 71 0.0 0.0 3.6 9.9 0.0 1.8 10.1 18.2 55.6 74.3 #> 72 72 0.0 0.0 3.6 9.9 0.0 1.8 10.1 18.2 55.6 74.3 #> 73 73 0.0 0.0 3.6 9.9 0.0 1.8 10.1 18.2 55.6 74.3 #> 74 74 0.0 0.0 3.6 9.9 0.0 1.8 10.1 18.2 55.6 74.3 #> 75 75 0.0 0.0 1.3 7.2 0.0 0.2 8.2 14.8 50.8 65.7 #> 76 76 0.0 0.0 1.3 7.2 0.0 0.2 8.2 14.8 50.8 65.7 #> 77 77 0.0 0.0 1.3 7.2 0.0 0.2 8.2 14.8 50.8 65.7 #> 78 78 0.0 0.0 1.3 7.2 0.0 0.2 8.2 14.8 50.8 65.7 #> 79 79 0.0 0.0 1.3 7.2 0.0 0.2 8.2 14.8 50.8 65.7 #> 80 80 0.0 0.0 0.5 4.9 0.0 0.2 2.1 8.7 28.2 58.1 #> 81 81 0.0 0.0 0.5 4.9 0.0 0.2 2.1 8.7 28.2 58.1 #> 82 82 0.0 0.0 0.5 4.9 0.0 0.2 2.1 8.7 28.2 58.1 #> 83 83 0.0 0.0 0.5 4.9 0.0 0.2 2.1 8.7 28.2 58.1 #> 84 84 0.0 0.0 0.5 4.9 0.0 0.2 2.1 8.7 28.2 58.1 #> 85 85 0.0 0.0 0.4 1.0 0.0 0.2 0.6 2.4 16.8 45.6 #> 86 86 0.0 0.0 0.4 1.0 0.0 0.2 0.6 2.4 16.8 45.6 #> 87 87 0.0 0.0 0.4 1.0 0.0 0.2 0.6 2.4 16.8 45.6 #> 88 88 0.0 0.0 0.4 1.0 0.0 0.2 0.6 2.4 16.8 45.6 #> 89 89 0.0 0.0 0.4 1.0 0.0 0.2 0.6 2.4 16.8 45.6 #> [ reached getOption("max.print") -- omitted 11 rows ]
# Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiRWA2016[ppiRWA2016$score == ppiScore, ]
#> score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp844 #> 50 50 2.7 11 30.5 56.3 2 21.2 61.5 77.2 95.7 99.9
# Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiRWA2016, score == ppiScore)
#> score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp844 #> 50 50 2.7 11 30.5 56.3 2 21.2 61.5 77.2 95.7 99.9
# Given a specific PPI score (from 0 - 100), get a poverty probability # based on a specific poverty definition. In this example, the national # poverty line definition ppiScore <- 50 ppiRWA2016[ppiRWA2016$score == ppiScore, "nl100"]
#> [1] 11