Poverty Probability Index (PPI) lookup table for Malawi using government poverty definitions
ppiMWI2015_gov
A data frame with 14 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
half100Poorest half below 100% national
ppp125Below $1.25 per day purchasing power parity (2005)
ppp200Below $2.00 per day purchasing power parity (2005)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp500Below $5.00 per day purchasing power parity (2005)
ppp844Below $8.44 per day purchasing power parity (2005)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
ppp1000Below $10.00 per day purchasing power parity (2011)
# Access Malawi PPI table ppiMWI2015_gov#> score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp844 #> 0 0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 #> 1 1 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 #> 2 2 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 #> 3 3 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 #> 4 4 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 #> 5 5 81.3 97.1 99.7 100.0 81.3 99.7 100.0 100.0 100.0 100.0 #> 6 6 81.3 97.1 99.7 100.0 81.3 99.7 100.0 100.0 100.0 100.0 #> 7 7 81.3 97.1 99.7 100.0 81.3 99.7 100.0 100.0 100.0 100.0 #> 8 8 81.3 97.1 99.7 100.0 81.3 99.7 100.0 100.0 100.0 100.0 #> 9 9 81.3 97.1 99.7 100.0 81.3 99.7 100.0 100.0 100.0 100.0 #> 10 10 71.8 95.7 98.6 100.0 73.3 98.6 100.0 100.0 100.0 100.0 #> 11 11 71.8 95.7 98.6 100.0 73.3 98.6 100.0 100.0 100.0 100.0 #> 12 12 71.8 95.7 98.6 100.0 73.3 98.6 100.0 100.0 100.0 100.0 #> 13 13 71.8 95.7 98.6 100.0 73.3 98.6 100.0 100.0 100.0 100.0 #> 14 14 71.8 95.7 98.6 100.0 73.3 98.6 100.0 100.0 100.0 100.0 #> 15 15 70.3 94.4 98.5 100.0 72.3 98.5 100.0 100.0 100.0 100.0 #> 16 16 70.3 94.4 98.5 100.0 72.3 98.5 100.0 100.0 100.0 100.0 #> 17 17 70.3 94.4 98.5 100.0 72.3 98.5 100.0 100.0 100.0 100.0 #> 18 18 70.3 94.4 98.5 100.0 72.3 98.5 100.0 100.0 100.0 100.0 #> 19 19 70.3 94.4 98.5 100.0 72.3 98.5 100.0 100.0 100.0 100.0 #> 20 20 55.7 87.4 96.3 98.6 60.3 95.8 99.3 99.9 100.0 100.0 #> 21 21 55.7 87.4 96.3 98.6 60.3 95.8 99.3 99.9 100.0 100.0 #> 22 22 55.7 87.4 96.3 98.6 60.3 95.8 99.3 99.9 100.0 100.0 #> 23 23 55.7 87.4 96.3 98.6 60.3 95.8 99.3 99.9 100.0 100.0 #> 24 24 55.7 87.4 96.3 98.6 60.3 95.8 99.3 99.9 100.0 100.0 #> 25 25 49.9 80.0 94.7 98.1 51.3 92.9 98.8 99.6 100.0 100.0 #> 26 26 49.9 80.0 94.7 98.1 51.3 92.9 98.8 99.6 100.0 100.0 #> 27 27 49.9 80.0 94.7 98.1 51.3 92.9 98.8 99.6 100.0 100.0 #> 28 28 49.9 80.0 94.7 98.1 51.3 92.9 98.8 99.6 100.0 100.0 #> 29 29 49.9 80.0 94.7 98.1 51.3 92.9 98.8 99.6 100.0 100.0 #> 30 30 36.4 72.0 94.7 97.6 37.4 91.3 98.5 99.6 100.0 100.0 #> 31 31 36.4 72.0 94.7 97.6 37.4 91.3 98.5 99.6 100.0 100.0 #> 32 32 36.4 72.0 94.7 97.6 37.4 91.3 98.5 99.6 100.0 100.0 #> 33 33 36.4 72.0 94.7 97.6 37.4 91.3 98.5 99.6 100.0 100.0 #> 34 34 36.4 72.0 94.7 97.6 37.4 91.3 98.5 99.6 100.0 100.0 #> 35 35 27.6 70.2 90.1 96.4 29.0 88.5 97.5 99.5 100.0 100.0 #> 36 36 27.6 70.2 90.1 96.4 29.0 88.5 97.5 99.5 100.0 100.0 #> 37 37 27.6 70.2 90.1 96.4 29.0 88.5 97.5 99.5 100.0 100.0 #> 38 38 27.6 70.2 90.1 96.4 29.0 88.5 97.5 99.5 100.0 100.0 #> 39 39 27.6 70.2 90.1 96.4 29.0 88.5 97.5 99.5 100.0 100.0 #> 40 40 21.5 57.4 82.7 93.2 23.6 79.8 96.3 98.9 100.0 100.0 #> 41 41 21.5 57.4 82.7 93.2 23.6 79.8 96.3 98.9 100.0 100.0 #> 42 42 21.5 57.4 82.7 93.2 23.6 79.8 96.3 98.9 100.0 100.0 #> 43 43 21.5 57.4 82.7 93.2 23.6 79.8 96.3 98.9 100.0 100.0 #> 44 44 21.5 57.4 82.7 93.2 23.6 79.8 96.3 98.9 100.0 100.0 #> 45 45 16.5 47.9 76.8 90.3 18.0 71.4 93.4 97.0 100.0 100.0 #> 46 46 16.5 47.9 76.8 90.3 18.0 71.4 93.4 97.0 100.0 100.0 #> 47 47 16.5 47.9 76.8 90.3 18.0 71.4 93.4 97.0 100.0 100.0 #> 48 48 16.5 47.9 76.8 90.3 18.0 71.4 93.4 97.0 100.0 100.0 #> 49 49 16.5 47.9 76.8 90.3 18.0 71.4 93.4 97.0 100.0 100.0 #> 50 50 9.4 30.5 57.1 80.5 9.1 52.1 86.2 92.2 99.8 100.0 #> 51 51 9.4 30.5 57.1 80.5 9.1 52.1 86.2 92.2 99.8 100.0 #> 52 52 9.4 30.5 57.1 80.5 9.1 52.1 86.2 92.2 99.8 100.0 #> 53 53 9.4 30.5 57.1 80.5 9.1 52.1 86.2 92.2 99.8 100.0 #> 54 54 9.4 30.5 57.1 80.5 9.1 52.1 86.2 92.2 99.8 100.0 #> 55 55 5.6 24.9 48.9 74.4 6.1 46.2 81.5 88.2 98.7 99.8 #> 56 56 5.6 24.9 48.9 74.4 6.1 46.2 81.5 88.2 98.7 99.8 #> 57 57 5.6 24.9 48.9 74.4 6.1 46.2 81.5 88.2 98.7 99.8 #> 58 58 5.6 24.9 48.9 74.4 6.1 46.2 81.5 88.2 98.7 99.8 #> 59 59 5.6 24.9 48.9 74.4 6.1 46.2 81.5 88.2 98.7 99.8 #> 60 60 4.0 20.0 44.1 67.1 3.7 41.1 72.3 82.4 96.5 98.9 #> 61 61 4.0 20.0 44.1 67.1 3.7 41.1 72.3 82.4 96.5 98.9 #> 62 62 4.0 20.0 44.1 67.1 3.7 41.1 72.3 82.4 96.5 98.9 #> 63 63 4.0 20.0 44.1 67.1 3.7 41.1 72.3 82.4 96.5 98.9 #> 64 64 4.0 20.0 44.1 67.1 3.7 41.1 72.3 82.4 96.5 98.9 #> 65 65 2.2 12.4 34.1 53.0 2.2 30.5 63.3 77.0 95.8 98.4 #> 66 66 2.2 12.4 34.1 53.0 2.2 30.5 63.3 77.0 95.8 98.4 #> 67 67 2.2 12.4 34.1 53.0 2.2 30.5 63.3 77.0 95.8 98.4 #> 68 68 2.2 12.4 34.1 53.0 2.2 30.5 63.3 77.0 95.8 98.4 #> 69 69 2.2 12.4 34.1 53.0 2.2 30.5 63.3 77.0 95.8 98.4 #> 70 70 1.0 6.5 23.3 38.3 0.7 20.8 48.3 62.4 90.6 97.4 #> ppp190 ppp310 ppp1000 #> 0 100.0 100.0 100.0 #> 1 100.0 100.0 100.0 #> 2 100.0 100.0 100.0 #> 3 100.0 100.0 100.0 #> 4 100.0 100.0 100.0 #> 5 100.0 100.0 100.0 #> 6 100.0 100.0 100.0 #> 7 100.0 100.0 100.0 #> 8 100.0 100.0 100.0 #> 9 100.0 100.0 100.0 #> 10 100.0 100.0 100.0 #> 11 100.0 100.0 100.0 #> 12 100.0 100.0 100.0 #> 13 100.0 100.0 100.0 #> 14 100.0 100.0 100.0 #> 15 100.0 100.0 100.0 #> 16 100.0 100.0 100.0 #> 17 100.0 100.0 100.0 #> 18 100.0 100.0 100.0 #> 19 100.0 100.0 100.0 #> 20 97.9 99.9 100.0 #> 21 97.9 99.9 100.0 #> 22 97.9 99.9 100.0 #> 23 97.9 99.9 100.0 #> 24 97.9 99.9 100.0 #> 25 96.4 99.6 100.0 #> 26 96.4 99.6 100.0 #> 27 96.4 99.6 100.0 #> 28 96.4 99.6 100.0 #> 29 96.4 99.6 100.0 #> 30 96.4 99.6 100.0 #> 31 96.4 99.6 100.0 #> 32 96.4 99.6 100.0 #> 33 96.4 99.6 100.0 #> 34 96.4 99.6 100.0 #> 35 94.5 99.6 100.0 #> 36 94.5 99.6 100.0 #> 37 94.5 99.6 100.0 #> 38 94.5 99.6 100.0 #> 39 94.5 99.6 100.0 #> 40 88.7 99.2 100.0 #> 41 88.7 99.2 100.0 #> 42 88.7 99.2 100.0 #> 43 88.7 99.2 100.0 #> 44 88.7 99.2 100.0 #> 45 84.9 97.2 100.0 #> 46 84.9 97.2 100.0 #> 47 84.9 97.2 100.0 #> 48 84.9 97.2 100.0 #> 49 84.9 97.2 100.0 #> 50 69.1 92.2 100.0 #> 51 69.1 92.2 100.0 #> 52 69.1 92.2 100.0 #> 53 69.1 92.2 100.0 #> 54 69.1 92.2 100.0 #> 55 64.3 88.3 99.8 #> 56 64.3 88.3 99.8 #> 57 64.3 88.3 99.8 #> 58 64.3 88.3 99.8 #> 59 64.3 88.3 99.8 #> 60 56.5 82.7 99.1 #> 61 56.5 82.7 99.1 #> 62 56.5 82.7 99.1 #> 63 56.5 82.7 99.1 #> 64 56.5 82.7 99.1 #> 65 43.6 77.3 98.8 #> 66 43.6 77.3 98.8 #> 67 43.6 77.3 98.8 #> 68 43.6 77.3 98.8 #> 69 43.6 77.3 98.8 #> 70 31.1 62.5 97.8 #> [ reached getOption("max.print") -- omitted 30 rows ]# Given a specific PPI score (from 0 - 100), get the row of poverty # probabilities from PPI table it corresponds to ppiScore <- 50 ppiMWI2015_gov[ppiMWI2015_gov$score == ppiScore, ]#> score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp844 #> 50 50 9.4 30.5 57.1 80.5 9.1 52.1 86.2 92.2 99.8 100 #> ppp190 ppp310 ppp1000 #> 50 69.1 92.2 100# Use subset() function to get the row of poverty probabilities corresponding # to specific PPI score ppiScore <- 50 subset(ppiMWI2015_gov, score == ppiScore)#> score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp844 #> 50 50 9.4 30.5 57.1 80.5 9.1 52.1 86.2 92.2 99.8 100 #> ppp190 ppp310 ppp1000 #> 50 69.1 92.2 100# 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 ppiMWI2015_gov[ppiMWI2015_gov$score == ppiScore, "nl100"]#> [1] 30.5