Poverty Probability Index (PPI) lookup table for Ghana using poverty definitions deflated with Ghana's CPI
Source:R/04_data.R
ppiGHA2015_a.RdPoverty Probability Index (PPI) lookup table for Ghana using poverty definitions deflated with Ghana's CPI
Format
A data frame with 13 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)
ppp375Below $3.75 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)
Examples
# Access Ghana PPI table
ppiGHA2015_a
#> score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp375 ppp500
#> 0 0 70.1 91.4 99.1 100.0 74.5 54.1 85.9 91.5 97.9 100.0
#> 1 1 70.1 91.4 99.1 100.0 74.5 54.1 85.9 91.5 97.9 100.0
#> 2 2 70.1 91.4 99.1 100.0 74.5 54.1 85.9 91.5 97.9 100.0
#> 3 3 70.1 91.4 99.1 100.0 74.5 54.1 85.9 91.5 97.9 100.0
#> 4 4 70.1 91.4 99.1 100.0 74.5 54.1 85.9 91.5 97.9 100.0
#> 5 5 70.1 91.4 99.1 100.0 74.5 54.1 85.9 91.5 97.9 100.0
#> 6 6 70.1 91.4 99.1 100.0 74.5 54.1 85.9 91.5 97.9 100.0
#> 7 7 70.1 91.4 99.1 100.0 74.5 54.1 85.9 91.5 97.9 100.0
#> 8 8 70.1 91.4 99.1 100.0 74.5 54.1 85.9 91.5 97.9 100.0
#> 9 9 70.1 91.4 99.1 100.0 74.5 54.1 85.9 91.5 97.9 100.0
#> 10 10 46.1 75.9 89.3 97.7 53.3 38.2 66.0 78.2 95.1 97.7
#> 11 11 46.1 75.9 89.3 97.7 53.3 38.2 66.0 78.2 95.1 97.7
#> 12 12 46.1 75.9 89.3 97.7 53.3 38.2 66.0 78.2 95.1 97.7
#> 13 13 46.1 75.9 89.3 97.7 53.3 38.2 66.0 78.2 95.1 97.7
#> 14 14 46.1 75.9 89.3 97.7 53.3 38.2 66.0 78.2 95.1 97.7
#> 15 15 34.6 66.8 86.9 96.4 41.3 24.5 55.2 71.5 91.2 95.9
#> 16 16 34.6 66.8 86.9 96.4 41.3 24.5 55.2 71.5 91.2 95.9
#> 17 17 34.6 66.8 86.9 96.4 41.3 24.5 55.2 71.5 91.2 95.9
#> 18 18 34.6 66.8 86.9 96.4 41.3 24.5 55.2 71.5 91.2 95.9
#> 19 19 34.6 66.8 86.9 96.4 41.3 24.5 55.2 71.5 91.2 95.9
#> 20 20 26.2 63.8 86.0 93.7 32.9 19.5 49.1 67.0 86.9 93.8
#> 21 21 26.2 63.8 86.0 93.7 32.9 19.5 49.1 67.0 86.9 93.8
#> 22 22 26.2 63.8 86.0 93.7 32.9 19.5 49.1 67.0 86.9 93.8
#> 23 23 26.2 63.8 86.0 93.7 32.9 19.5 49.1 67.0 86.9 93.8
#> 24 24 26.2 63.8 86.0 93.7 32.9 19.5 49.1 67.0 86.9 93.8
#> 25 25 18.9 53.3 80.1 92.4 28.4 12.1 38.5 57.1 81.7 92.7
#> 26 26 18.9 53.3 80.1 92.4 28.4 12.1 38.5 57.1 81.7 92.7
#> 27 27 18.9 53.3 80.1 92.4 28.4 12.1 38.5 57.1 81.7 92.7
#> 28 28 18.9 53.3 80.1 92.4 28.4 12.1 38.5 57.1 81.7 92.7
#> 29 29 18.9 53.3 80.1 92.4 28.4 12.1 38.5 57.1 81.7 92.7
#> 30 30 13.1 40.2 71.1 84.0 21.3 7.2 27.1 41.3 71.4 84.3
#> 31 31 13.1 40.2 71.1 84.0 21.3 7.2 27.1 41.3 71.4 84.3
#> 32 32 13.1 40.2 71.1 84.0 21.3 7.2 27.1 41.3 71.4 84.3
#> 33 33 13.1 40.2 71.1 84.0 21.3 7.2 27.1 41.3 71.4 84.3
#> 34 34 13.1 40.2 71.1 84.0 21.3 7.2 27.1 41.3 71.4 84.3
#> 35 35 6.9 29.0 58.1 76.4 10.7 3.7 16.2 31.4 58.8 77.4
#> 36 36 6.9 29.0 58.1 76.4 10.7 3.7 16.2 31.4 58.8 77.4
#> 37 37 6.9 29.0 58.1 76.4 10.7 3.7 16.2 31.4 58.8 77.4
#> 38 38 6.9 29.0 58.1 76.4 10.7 3.7 16.2 31.4 58.8 77.4
#> 39 39 6.9 29.0 58.1 76.4 10.7 3.7 16.2 31.4 58.8 77.4
#> 40 40 4.4 19.6 45.3 69.2 7.8 2.5 11.6 20.7 45.9 71.5
#> 41 41 4.4 19.6 45.3 69.2 7.8 2.5 11.6 20.7 45.9 71.5
#> 42 42 4.4 19.6 45.3 69.2 7.8 2.5 11.6 20.7 45.9 71.5
#> 43 43 4.4 19.6 45.3 69.2 7.8 2.5 11.6 20.7 45.9 71.5
#> 44 44 4.4 19.6 45.3 69.2 7.8 2.5 11.6 20.7 45.9 71.5
#> 45 45 1.4 11.7 35.2 58.8 4.0 0.6 5.3 12.8 36.4 59.6
#> 46 46 1.4 11.7 35.2 58.8 4.0 0.6 5.3 12.8 36.4 59.6
#> 47 47 1.4 11.7 35.2 58.8 4.0 0.6 5.3 12.8 36.4 59.6
#> 48 48 1.4 11.7 35.2 58.8 4.0 0.6 5.3 12.8 36.4 59.6
#> 49 49 1.4 11.7 35.2 58.8 4.0 0.6 5.3 12.8 36.4 59.6
#> 50 50 0.9 7.2 25.6 47.3 2.0 0.4 2.5 6.8 25.2 45.1
#> 51 51 0.9 7.2 25.6 47.3 2.0 0.4 2.5 6.8 25.2 45.1
#> 52 52 0.9 7.2 25.6 47.3 2.0 0.4 2.5 6.8 25.2 45.1
#> 53 53 0.9 7.2 25.6 47.3 2.0 0.4 2.5 6.8 25.2 45.1
#> 54 54 0.9 7.2 25.6 47.3 2.0 0.4 2.5 6.8 25.2 45.1
#> 55 55 0.9 4.3 17.7 35.7 1.7 0.3 2.2 5.1 17.6 36.7
#> 56 56 0.9 4.3 17.7 35.7 1.7 0.3 2.2 5.1 17.6 36.7
#> 57 57 0.9 4.3 17.7 35.7 1.7 0.3 2.2 5.1 17.6 36.7
#> 58 58 0.9 4.3 17.7 35.7 1.7 0.3 2.2 5.1 17.6 36.7
#> 59 59 0.9 4.3 17.7 35.7 1.7 0.3 2.2 5.1 17.6 36.7
#> 60 60 0.2 2.2 10.6 26.5 0.7 0.0 1.0 2.1 10.9 25.9
#> 61 61 0.2 2.2 10.6 26.5 0.7 0.0 1.0 2.1 10.9 25.9
#> 62 62 0.2 2.2 10.6 26.5 0.7 0.0 1.0 2.1 10.9 25.9
#> 63 63 0.2 2.2 10.6 26.5 0.7 0.0 1.0 2.1 10.9 25.9
#> 64 64 0.2 2.2 10.6 26.5 0.7 0.0 1.0 2.1 10.9 25.9
#> 65 65 0.0 1.1 7.4 21.2 0.2 0.0 0.2 0.7 6.5 17.9
#> 66 66 0.0 1.1 7.4 21.2 0.2 0.0 0.2 0.7 6.5 17.9
#> 67 67 0.0 1.1 7.4 21.2 0.2 0.0 0.2 0.7 6.5 17.9
#> 68 68 0.0 1.1 7.4 21.2 0.2 0.0 0.2 0.7 6.5 17.9
#> 69 69 0.0 1.1 7.4 21.2 0.2 0.0 0.2 0.7 6.5 17.9
#> 70 70 0.0 0.8 4.6 13.3 0.1 0.0 0.1 0.6 4.3 11.7
#> 71 71 0.0 0.8 4.6 13.3 0.1 0.0 0.1 0.6 4.3 11.7
#> 72 72 0.0 0.8 4.6 13.3 0.1 0.0 0.1 0.6 4.3 11.7
#> 73 73 0.0 0.8 4.6 13.3 0.1 0.0 0.1 0.6 4.3 11.7
#> 74 74 0.0 0.8 4.6 13.3 0.1 0.0 0.1 0.6 4.3 11.7
#> 75 75 0.0 0.3 1.4 6.5 0.0 0.0 0.0 0.0 1.6 6.2
#> 76 76 0.0 0.3 1.4 6.5 0.0 0.0 0.0 0.0 1.6 6.2
#> 77 77 0.0 0.3 1.4 6.5 0.0 0.0 0.0 0.0 1.6 6.2
#> 78 78 0.0 0.3 1.4 6.5 0.0 0.0 0.0 0.0 1.6 6.2
#> 79 79 0.0 0.3 1.4 6.5 0.0 0.0 0.0 0.0 1.6 6.2
#> 80 80 0.0 0.0 0.6 1.1 0.0 0.0 0.0 0.0 0.7 1.3
#> 81 81 0.0 0.0 0.6 1.1 0.0 0.0 0.0 0.0 0.7 1.3
#> 82 82 0.0 0.0 0.6 1.1 0.0 0.0 0.0 0.0 0.7 1.3
#> 83 83 0.0 0.0 0.6 1.1 0.0 0.0 0.0 0.0 0.7 1.3
#> 84 84 0.0 0.0 0.6 1.1 0.0 0.0 0.0 0.0 0.7 1.3
#> 85 85 0.0 0.0 0.2 0.4 0.0 0.0 0.0 0.0 0.2 0.4
#> 86 86 0.0 0.0 0.2 0.4 0.0 0.0 0.0 0.0 0.2 0.4
#> 87 87 0.0 0.0 0.2 0.4 0.0 0.0 0.0 0.0 0.2 0.4
#> 88 88 0.0 0.0 0.2 0.4 0.0 0.0 0.0 0.0 0.2 0.4
#> 89 89 0.0 0.0 0.2 0.4 0.0 0.0 0.0 0.0 0.2 0.4
#> 90 90 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 91 91 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 92 92 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 93 93 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 94 94 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
#> 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
#> ppp190 ppp310
#> 0 74.5 96.7
#> 1 74.5 96.7
#> 2 74.5 96.7
#> 3 74.5 96.7
#> 4 74.5 96.7
#> 5 74.5 96.7
#> 6 74.5 96.7
#> 7 74.5 96.7
#> 8 74.5 96.7
#> 9 74.5 96.7
#> 10 50.7 81.7
#> 11 50.7 81.7
#> 12 50.7 81.7
#> 13 50.7 81.7
#> 14 50.7 81.7
#> 15 39.9 74.7
#> 16 39.9 74.7
#> 17 39.9 74.7
#> 18 39.9 74.7
#> 19 39.9 74.7
#> 20 32.6 70.6
#> 21 32.6 70.6
#> 22 32.6 70.6
#> 23 32.6 70.6
#> 24 32.6 70.6
#> 25 25.1 62.1
#> 26 25.1 62.1
#> 27 25.1 62.1
#> 28 25.1 62.1
#> 29 25.1 62.1
#> 30 16.5 45.4
#> 31 16.5 45.4
#> 32 16.5 45.4
#> 33 16.5 45.4
#> 34 16.5 45.4
#> 35 7.9 35.4
#> 36 7.9 35.4
#> 37 7.9 35.4
#> 38 7.9 35.4
#> 39 7.9 35.4
#> 40 5.1 24.0
#> 41 5.1 24.0
#> 42 5.1 24.0
#> 43 5.1 24.0
#> 44 5.1 24.0
#> 45 2.4 16.1
#> 46 2.4 16.1
#> 47 2.4 16.1
#> 48 2.4 16.1
#> 49 2.4 16.1
#> 50 1.0 9.5
#> 51 1.0 9.5
#> 52 1.0 9.5
#> 53 1.0 9.5
#> 54 1.0 9.5
#> 55 0.9 5.8
#> 56 0.9 5.8
#> 57 0.9 5.8
#> 58 0.9 5.8
#> 59 0.9 5.8
#> 60 0.4 2.9
#> 61 0.4 2.9
#> 62 0.4 2.9
#> 63 0.4 2.9
#> 64 0.4 2.9
#> 65 0.1 1.3
#> 66 0.1 1.3
#> 67 0.1 1.3
#> 68 0.1 1.3
#> 69 0.1 1.3
#> 70 0.1 0.8
#> 71 0.1 0.8
#> 72 0.1 0.8
#> 73 0.1 0.8
#> 74 0.1 0.8
#> 75 0.0 0.1
#> 76 0.0 0.1
#> 77 0.0 0.1
#> 78 0.0 0.1
#> 79 0.0 0.1
#> 80 0.0 0.0
#> 81 0.0 0.0
#> 82 0.0 0.0
#> 83 0.0 0.0
#> 84 0.0 0.0
#> 85 0.0 0.0
#> 86 0.0 0.0
#> 87 0.0 0.0
#> 88 0.0 0.0
#> 89 0.0 0.0
#> 90 0.0 0.0
#> 91 0.0 0.0
#> 92 0.0 0.0
#> 93 0.0 0.0
#> 94 0.0 0.0
#> 95 0.0 0.0
#> 96 0.0 0.0
#> 97 0.0 0.0
#> 98 0.0 0.0
#> 99 0.0 0.0
#> 100 0.0 0.0
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiGHA2015_a[ppiGHA2015_a$score == ppiScore, ]
#> score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp375 ppp500
#> 50 50 0.9 7.2 25.6 47.3 2 0.4 2.5 6.8 25.2 45.1
#> ppp190 ppp310
#> 50 1 9.5
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiGHA2015_a, score == ppiScore)
#> score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp375 ppp500
#> 50 50 0.9 7.2 25.6 47.3 2 0.4 2.5 6.8 25.2 45.1
#> ppp190 ppp310
#> 50 1 9.5
# 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
ppiGHA2015_a[ppiGHA2015_a$score == ppiScore, "nl100"]
#> [1] 7.2