Poverty Probability Index (PPI) lookup table for Tanzania
Format
A data frame with 19 columns and 101 rows:
scorePPI score
nlFoodFood poverty line
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
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)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
ppp380Below $3.80 per day purchasing power parity (2011)
ppp400Below $4.00 per day purchasing power parity (2011)
half100Poorest half below 100 national
percentile20Below 20th percentile poverty line
percentile40Below 40th percentile poverty line
percentile50Below 50th percentile poverty line
percentile60Below 60th percentile poverty line
percentile80Below 80th percentile poverty line
Examples
# Access Tanzania PPI table
ppiTZA2016
#> score nlFood nl100 nl150 nl200 ppp125 ppp200 ppp250 ppp500 ppp190 ppp310
#> 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 39.5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 6 6 39.5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 7 7 39.5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 8 8 39.5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 9 9 39.5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 10 10 36.6 82.3 93.1 100.0 86.7 100.0 100.0 100.0 89.0 100.0
#> 11 11 36.6 82.3 93.1 100.0 86.7 100.0 100.0 100.0 89.0 100.0
#> 12 12 36.6 82.3 93.1 100.0 86.7 100.0 100.0 100.0 89.0 100.0
#> 13 13 36.6 82.3 93.1 100.0 86.7 100.0 100.0 100.0 89.0 100.0
#> 14 14 36.6 82.3 93.1 100.0 86.7 100.0 100.0 100.0 89.0 100.0
#> 15 15 29.9 62.1 89.2 98.6 77.5 99.9 99.9 100.0 85.0 99.9
#> 16 16 29.9 62.1 89.2 98.6 77.5 99.9 99.9 100.0 85.0 99.9
#> 17 17 29.9 62.1 89.2 98.6 77.5 99.9 99.9 100.0 85.0 99.9
#> 18 18 29.9 62.1 89.2 98.6 77.5 99.9 99.9 100.0 85.0 99.9
#> 19 19 29.9 62.1 89.2 98.6 77.5 99.9 99.9 100.0 85.0 99.9
#> 20 20 21.0 51.2 84.5 93.8 71.9 93.0 97.0 99.7 78.0 96.3
#> 21 21 21.0 51.2 84.5 93.8 71.9 93.0 97.0 99.7 78.0 96.3
#> 22 22 21.0 51.2 84.5 93.8 71.9 93.0 97.0 99.7 78.0 96.3
#> 23 23 21.0 51.2 84.5 93.8 71.9 93.0 97.0 99.7 78.0 96.3
#> 24 24 21.0 51.2 84.5 93.8 71.9 93.0 97.0 99.7 78.0 96.3
#> 25 25 13.3 40.3 77.4 93.8 59.6 92.4 96.7 99.5 70.6 94.5
#> 26 26 13.3 40.3 77.4 93.8 59.6 92.4 96.7 99.5 70.6 94.5
#> 27 27 13.3 40.3 77.4 93.8 59.6 92.4 96.7 99.5 70.6 94.5
#> 28 28 13.3 40.3 77.4 93.8 59.6 92.4 96.7 99.5 70.6 94.5
#> 29 29 13.3 40.3 77.4 93.8 59.6 92.4 96.7 99.5 70.6 94.5
#> 30 30 10.4 32.9 68.0 87.4 48.0 84.3 95.0 99.5 57.7 91.7
#> 31 31 10.4 32.9 68.0 87.4 48.0 84.3 95.0 99.5 57.7 91.7
#> 32 32 10.4 32.9 68.0 87.4 48.0 84.3 95.0 99.5 57.7 91.7
#> 33 33 10.4 32.9 68.0 87.4 48.0 84.3 95.0 99.5 57.7 91.7
#> 34 34 10.4 32.9 68.0 87.4 48.0 84.3 95.0 99.5 57.7 91.7
#> 35 35 4.4 20.2 58.1 79.4 35.2 77.2 89.5 99.5 47.2 84.4
#> 36 36 4.4 20.2 58.1 79.4 35.2 77.2 89.5 99.5 47.2 84.4
#> 37 37 4.4 20.2 58.1 79.4 35.2 77.2 89.5 99.5 47.2 84.4
#> 38 38 4.4 20.2 58.1 79.4 35.2 77.2 89.5 99.5 47.2 84.4
#> 39 39 4.4 20.2 58.1 79.4 35.2 77.2 89.5 99.5 47.2 84.4
#> 40 40 2.8 14.0 42.5 67.9 23.5 64.3 79.6 98.5 31.2 71.8
#> 41 41 2.8 14.0 42.5 67.9 23.5 64.3 79.6 98.5 31.2 71.8
#> 42 42 2.8 14.0 42.5 67.9 23.5 64.3 79.6 98.5 31.2 71.8
#> 43 43 2.8 14.0 42.5 67.9 23.5 64.3 79.6 98.5 31.2 71.8
#> 44 44 2.8 14.0 42.5 67.9 23.5 64.3 79.6 98.5 31.2 71.8
#> 45 45 1.5 10.9 40.2 63.7 20.2 54.3 75.7 97.3 28.5 66.1
#> 46 46 1.5 10.9 40.2 63.7 20.2 54.3 75.7 97.3 28.5 66.1
#> 47 47 1.5 10.9 40.2 63.7 20.2 54.3 75.7 97.3 28.5 66.1
#> 48 48 1.5 10.9 40.2 63.7 20.2 54.3 75.7 97.3 28.5 66.1
#> 49 49 1.5 10.9 40.2 63.7 20.2 54.3 75.7 97.3 28.5 66.1
#> 50 50 1.3 6.6 29.2 51.2 13.8 45.4 61.2 94.2 18.8 54.0
#> 51 51 1.3 6.6 29.2 51.2 13.8 45.4 61.2 94.2 18.8 54.0
#> 52 52 1.3 6.6 29.2 51.2 13.8 45.4 61.2 94.2 18.8 54.0
#> 53 53 1.3 6.6 29.2 51.2 13.8 45.4 61.2 94.2 18.8 54.0
#> 54 54 1.3 6.6 29.2 51.2 13.8 45.4 61.2 94.2 18.8 54.0
#> 55 55 0.6 4.1 24.2 43.8 7.3 38.7 56.9 93.4 11.9 45.5
#> 56 56 0.6 4.1 24.2 43.8 7.3 38.7 56.9 93.4 11.9 45.5
#> 57 57 0.6 4.1 24.2 43.8 7.3 38.7 56.9 93.4 11.9 45.5
#> 58 58 0.6 4.1 24.2 43.8 7.3 38.7 56.9 93.4 11.9 45.5
#> 59 59 0.6 4.1 24.2 43.8 7.3 38.7 56.9 93.4 11.9 45.5
#> 60 60 0.6 2.2 13.5 31.8 4.2 25.1 45.6 86.1 5.8 33.7
#> 61 61 0.6 2.2 13.5 31.8 4.2 25.1 45.6 86.1 5.8 33.7
#> 62 62 0.6 2.2 13.5 31.8 4.2 25.1 45.6 86.1 5.8 33.7
#> 63 63 0.6 2.2 13.5 31.8 4.2 25.1 45.6 86.1 5.8 33.7
#> 64 64 0.6 2.2 13.5 31.8 4.2 25.1 45.6 86.1 5.8 33.7
#> 65 65 0.4 1.3 8.6 28.1 1.7 21.3 36.8 79.9 3.7 28.9
#> 66 66 0.4 1.3 8.6 28.1 1.7 21.3 36.8 79.9 3.7 28.9
#> 67 67 0.4 1.3 8.6 28.1 1.7 21.3 36.8 79.9 3.7 28.9
#> 68 68 0.4 1.3 8.6 28.1 1.7 21.3 36.8 79.9 3.7 28.9
#> 69 69 0.4 1.3 8.6 28.1 1.7 21.3 36.8 79.9 3.7 28.9
#> 70 70 0.0 1.0 5.9 19.5 1.7 13.8 27.1 78.7 3.1 21.2
#> 71 71 0.0 1.0 5.9 19.5 1.7 13.8 27.1 78.7 3.1 21.2
#> 72 72 0.0 1.0 5.9 19.5 1.7 13.8 27.1 78.7 3.1 21.2
#> 73 73 0.0 1.0 5.9 19.5 1.7 13.8 27.1 78.7 3.1 21.2
#> 74 74 0.0 1.0 5.9 19.5 1.7 13.8 27.1 78.7 3.1 21.2
#> 75 75 0.0 1.0 5.9 16.8 1.7 12.8 23.2 71.3 2.9 20.1
#> 76 76 0.0 1.0 5.9 16.8 1.7 12.8 23.2 71.3 2.9 20.1
#> 77 77 0.0 1.0 5.9 16.8 1.7 12.8 23.2 71.3 2.9 20.1
#> 78 78 0.0 1.0 5.9 16.8 1.7 12.8 23.2 71.3 2.9 20.1
#> 79 79 0.0 1.0 5.9 16.8 1.7 12.8 23.2 71.3 2.9 20.1
#> 80 80 0.0 1.0 2.6 7.3 1.3 3.1 8.1 44.2 1.3 6.3
#> 81 81 0.0 1.0 2.6 7.3 1.3 3.1 8.1 44.2 1.3 6.3
#> 82 82 0.0 1.0 2.6 7.3 1.3 3.1 8.1 44.2 1.3 6.3
#> 83 83 0.0 1.0 2.6 7.3 1.3 3.1 8.1 44.2 1.3 6.3
#> 84 84 0.0 1.0 2.6 7.3 1.3 3.1 8.1 44.2 1.3 6.3
#> 85 85 0.0 0.0 2.2 7.3 0.1 2.8 8.1 38.3 1.2 6.3
#> 86 86 0.0 0.0 2.2 7.3 0.1 2.8 8.1 38.3 1.2 6.3
#> 87 87 0.0 0.0 2.2 7.3 0.1 2.8 8.1 38.3 1.2 6.3
#> 88 88 0.0 0.0 2.2 7.3 0.1 2.8 8.1 38.3 1.2 6.3
#> 89 89 0.0 0.0 2.2 7.3 0.1 2.8 8.1 38.3 1.2 6.3
#> 90 90 0.0 0.0 0.0 7.3 0.0 0.0 7.6 30.6 0.0 6.3
#> 91 91 0.0 0.0 0.0 7.3 0.0 0.0 7.6 30.6 0.0 6.3
#> 92 92 0.0 0.0 0.0 7.3 0.0 0.0 7.6 30.6 0.0 6.3
#> 93 93 0.0 0.0 0.0 7.3 0.0 0.0 7.6 30.6 0.0 6.3
#> 94 94 0.0 0.0 0.0 7.3 0.0 0.0 7.6 30.6 0.0 6.3
#> 95 95 0.0 0.0 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 0.0 0.0
#> 97 97 0.0 0.0 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 0.0 0.0
#> 99 99 0.0 0.0 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 0.0 0.0
#> ppp380 ppp400 half100 percentile20 percentile40 percentile50 percentile60
#> 0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 1 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 2 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 3 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 4 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 5 100.0 100.0 80.6 100.0 100.0 100.0 100.0
#> 6 100.0 100.0 80.6 100.0 100.0 100.0 100.0
#> 7 100.0 100.0 80.6 100.0 100.0 100.0 100.0
#> 8 100.0 100.0 80.6 100.0 100.0 100.0 100.0
#> 9 100.0 100.0 80.6 100.0 100.0 100.0 100.0
#> 10 100.0 100.0 49.2 76.6 89.0 90.1 98.6
#> 11 100.0 100.0 49.2 76.6 89.0 90.1 98.6
#> 12 100.0 100.0 49.2 76.6 89.0 90.1 98.6
#> 13 100.0 100.0 49.2 76.6 89.0 90.1 98.6
#> 14 100.0 100.0 49.2 76.6 89.0 90.1 98.6
#> 15 99.9 99.9 42.6 53.2 78.8 88.1 95.0
#> 16 99.9 99.9 42.6 53.2 78.8 88.1 95.0
#> 17 99.9 99.9 42.6 53.2 78.8 88.1 95.0
#> 18 99.9 99.9 42.6 53.2 78.8 88.1 95.0
#> 19 99.9 99.9 42.6 53.2 78.8 88.1 95.0
#> 20 97.4 98.3 25.6 38.3 71.8 80.1 87.6
#> 21 97.4 98.3 25.6 38.3 71.8 80.1 87.6
#> 22 97.4 98.3 25.6 38.3 71.8 80.1 87.6
#> 23 97.4 98.3 25.6 38.3 71.8 80.1 87.6
#> 24 97.4 98.3 25.6 38.3 71.8 80.1 87.6
#> 25 97.4 98.0 20.6 28.0 58.0 73.7 83.9
#> 26 97.4 98.0 20.6 28.0 58.0 73.7 83.9
#> 27 97.4 98.0 20.6 28.0 58.0 73.7 83.9
#> 28 97.4 98.0 20.6 28.0 58.0 73.7 83.9
#> 29 97.4 98.0 20.6 28.0 58.0 73.7 83.9
#> 30 96.7 97.7 16.9 23.2 48.4 60.8 74.2
#> 31 96.7 97.7 16.9 23.2 48.4 60.8 74.2
#> 32 96.7 97.7 16.9 23.2 48.4 60.8 74.2
#> 33 96.7 97.7 16.9 23.2 48.4 60.8 74.2
#> 34 96.7 97.7 16.9 23.2 48.4 60.8 74.2
#> 35 92.5 94.1 8.1 12.5 36.3 48.9 62.4
#> 36 92.5 94.1 8.1 12.5 36.3 48.9 62.4
#> 37 92.5 94.1 8.1 12.5 36.3 48.9 62.4
#> 38 92.5 94.1 8.1 12.5 36.3 48.9 62.4
#> 39 92.5 94.1 8.1 12.5 36.3 48.9 62.4
#> 40 85.4 88.9 5.4 7.9 23.2 33.0 45.4
#> 41 85.4 88.9 5.4 7.9 23.2 33.0 45.4
#> 42 85.4 88.9 5.4 7.9 23.2 33.0 45.4
#> 43 85.4 88.9 5.4 7.9 23.2 33.0 45.4
#> 44 85.4 88.9 5.4 7.9 23.2 33.0 45.4
#> 45 81.8 84.1 3.1 5.4 17.9 27.4 39.4
#> 46 81.8 84.1 3.1 5.4 17.9 27.4 39.4
#> 47 81.8 84.1 3.1 5.4 17.9 27.4 39.4
#> 48 81.8 84.1 3.1 5.4 17.9 27.4 39.4
#> 49 81.8 84.1 3.1 5.4 17.9 27.4 39.4
#> 50 69.7 72.2 1.7 3.4 12.1 17.6 26.8
#> 51 69.7 72.2 1.7 3.4 12.1 17.6 26.8
#> 52 69.7 72.2 1.7 3.4 12.1 17.6 26.8
#> 53 69.7 72.2 1.7 3.4 12.1 17.6 26.8
#> 54 69.7 72.2 1.7 3.4 12.1 17.6 26.8
#> 55 63.1 65.3 0.5 0.6 6.0 8.6 18.8
#> 56 63.1 65.3 0.5 0.6 6.0 8.6 18.8
#> 57 63.1 65.3 0.5 0.6 6.0 8.6 18.8
#> 58 63.1 65.3 0.5 0.6 6.0 8.6 18.8
#> 59 63.1 65.3 0.5 0.6 6.0 8.6 18.8
#> 60 50.2 53.8 0.5 0.6 1.8 4.4 10.3
#> 61 50.2 53.8 0.5 0.6 1.8 4.4 10.3
#> 62 50.2 53.8 0.5 0.6 1.8 4.4 10.3
#> 63 50.2 53.8 0.5 0.6 1.8 4.4 10.3
#> 64 50.2 53.8 0.5 0.6 1.8 4.4 10.3
#> 65 44.7 46.8 0.3 0.4 1.1 1.3 5.5
#> 66 44.7 46.8 0.3 0.4 1.1 1.3 5.5
#> 67 44.7 46.8 0.3 0.4 1.1 1.3 5.5
#> 68 44.7 46.8 0.3 0.4 1.1 1.3 5.5
#> 69 44.7 46.8 0.3 0.4 1.1 1.3 5.5
#> 70 34.4 37.2 0.0 0.0 1.1 1.3 2.6
#> 71 34.4 37.2 0.0 0.0 1.1 1.3 2.6
#> 72 34.4 37.2 0.0 0.0 1.1 1.3 2.6
#> 73 34.4 37.2 0.0 0.0 1.1 1.3 2.6
#> 74 34.4 37.2 0.0 0.0 1.1 1.3 2.6
#> 75 33.0 35.7 0.0 0.0 1.0 1.3 2.6
#> 76 33.0 35.7 0.0 0.0 1.0 1.3 2.6
#> 77 33.0 35.7 0.0 0.0 1.0 1.3 2.6
#> 78 33.0 35.7 0.0 0.0 1.0 1.3 2.6
#> 79 33.0 35.7 0.0 0.0 1.0 1.3 2.6
#> 80 11.4 13.4 0.0 0.0 0.0 1.3 1.4
#> 81 11.4 13.4 0.0 0.0 0.0 1.3 1.4
#> 82 11.4 13.4 0.0 0.0 0.0 1.3 1.4
#> 83 11.4 13.4 0.0 0.0 0.0 1.3 1.4
#> 84 11.4 13.4 0.0 0.0 0.0 1.3 1.4
#> 85 11.4 13.4 0.0 0.0 0.0 0.1 0.1
#> 86 11.4 13.4 0.0 0.0 0.0 0.1 0.1
#> 87 11.4 13.4 0.0 0.0 0.0 0.1 0.1
#> 88 11.4 13.4 0.0 0.0 0.0 0.1 0.1
#> 89 11.4 13.4 0.0 0.0 0.0 0.1 0.1
#> 90 7.6 7.6 0.0 0.0 0.0 0.0 0.0
#> 91 7.6 7.6 0.0 0.0 0.0 0.0 0.0
#> 92 7.6 7.6 0.0 0.0 0.0 0.0 0.0
#> 93 7.6 7.6 0.0 0.0 0.0 0.0 0.0
#> 94 7.6 7.6 0.0 0.0 0.0 0.0 0.0
#> 95 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 96 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 97 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 98 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 99 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 100 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> percentile80
#> 0 100.0
#> 1 100.0
#> 2 100.0
#> 3 100.0
#> 4 100.0
#> 5 100.0
#> 6 100.0
#> 7 100.0
#> 8 100.0
#> 9 100.0
#> 10 100.0
#> 11 100.0
#> 12 100.0
#> 13 100.0
#> 14 100.0
#> 15 99.9
#> 16 99.9
#> 17 99.9
#> 18 99.9
#> 19 99.9
#> 20 97.1
#> 21 97.1
#> 22 97.1
#> 23 97.1
#> 24 97.1
#> 25 96.9
#> 26 96.9
#> 27 96.9
#> 28 96.9
#> 29 96.9
#> 30 95.4
#> 31 95.4
#> 32 95.4
#> 33 95.4
#> 34 95.4
#> 35 88.0
#> 36 88.0
#> 37 88.0
#> 38 88.0
#> 39 88.0
#> 40 80.4
#> 41 80.4
#> 42 80.4
#> 43 80.4
#> 44 80.4
#> 45 72.4
#> 46 72.4
#> 47 72.4
#> 48 72.4
#> 49 72.4
#> 50 54.6
#> 51 54.6
#> 52 54.6
#> 53 54.6
#> 54 54.6
#> 55 46.4
#> 56 46.4
#> 57 46.4
#> 58 46.4
#> 59 46.4
#> 60 33.0
#> 61 33.0
#> 62 33.0
#> 63 33.0
#> 64 33.0
#> 65 22.7
#> 66 22.7
#> 67 22.7
#> 68 22.7
#> 69 22.7
#> 70 13.9
#> 71 13.9
#> 72 13.9
#> 73 13.9
#> 74 13.9
#> 75 12.8
#> 76 12.8
#> 77 12.8
#> 78 12.8
#> 79 12.8
#> 80 5.3
#> 81 5.3
#> 82 5.3
#> 83 5.3
#> 84 5.3
#> 85 5.3
#> 86 5.3
#> 87 5.3
#> 88 5.3
#> 89 5.3
#> 90 0.0
#> 91 0.0
#> 92 0.0
#> 93 0.0
#> 94 0.0
#> 95 0.0
#> 96 0.0
#> 97 0.0
#> 98 0.0
#> 99 0.0
#> 100 0.0
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiTZA2016[ppiTZA2016$score == ppiScore, ]
#> score nlFood nl100 nl150 nl200 ppp125 ppp200 ppp250 ppp500 ppp190 ppp310
#> 50 50 1.3 6.6 29.2 51.2 13.8 45.4 61.2 94.2 18.8 54
#> ppp380 ppp400 half100 percentile20 percentile40 percentile50 percentile60
#> 50 69.7 72.2 1.7 3.4 12.1 17.6 26.8
#> percentile80
#> 50 54.6
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiTZA2016, score == ppiScore)
#> score nlFood nl100 nl150 nl200 ppp125 ppp200 ppp250 ppp500 ppp190 ppp310
#> 50 50 1.3 6.6 29.2 51.2 13.8 45.4 61.2 94.2 18.8 54
#> ppp380 ppp400 half100 percentile20 percentile40 percentile50 percentile60
#> 50 69.7 72.2 1.7 3.4 12.1 17.6 26.8
#> percentile80
#> 50 54.6
# 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
ppiTZA2016[ppiTZA2016$score == ppiScore, "nl100"]
#> [1] 6.6