Poverty Probability Index (PPI) lookup table for Ghana based on legacy definitions
Source:R/04_data.R
ppiGHA2015.RdPoverty Probability Index (PPI) lookup table for Ghana based on legacy definitions
Format
A data frame with 8 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)
ppp250Below $2.50 per day purchasing power parity (2005)
ppp375Below $2.75 per day purchasing power parity (2005)
Examples
# Access Ghana PPI table
ppiGHA2015
#> score nlFood nl100 nl150 nl200 ppp125 ppp250 ppp375
#> 0 0 70.4 89.0 97.9 99.1 83.9 97.9 100.0
#> 1 1 70.4 89.0 97.9 99.1 83.9 97.9 100.0
#> 2 2 70.4 89.0 97.9 99.1 83.9 97.9 100.0
#> 3 3 70.4 89.0 97.9 99.1 83.9 97.9 100.0
#> 4 4 70.4 89.0 97.9 99.1 83.9 97.9 100.0
#> 5 5 70.4 89.0 97.9 99.1 83.9 97.9 100.0
#> 6 6 70.4 89.0 97.9 99.1 83.9 97.9 100.0
#> 7 7 70.4 89.0 97.9 99.1 83.9 97.9 100.0
#> 8 8 70.4 89.0 97.9 99.1 83.9 97.9 100.0
#> 9 9 70.4 89.0 97.9 99.1 83.9 97.9 100.0
#> 10 10 50.7 74.4 88.2 96.3 59.6 93.5 97.9
#> 11 11 50.7 74.4 88.2 96.3 59.6 93.5 97.9
#> 12 12 50.7 74.4 88.2 96.3 59.6 93.5 97.9
#> 13 13 50.7 74.4 88.2 96.3 59.6 93.5 97.9
#> 14 14 50.7 74.4 88.2 96.3 59.6 93.5 97.9
#> 15 15 38.4 62.3 85.5 94.2 47.3 88.2 96.4
#> 16 16 38.4 62.3 85.5 94.2 47.3 88.2 96.4
#> 17 17 38.4 62.3 85.5 94.2 47.3 88.2 96.4
#> 18 18 38.4 62.3 85.5 94.2 47.3 88.2 96.4
#> 19 19 38.4 62.3 85.5 94.2 47.3 88.2 96.4
#> 20 20 31.0 58.7 84.9 91.8 39.4 86.1 96.3
#> 21 21 31.0 58.7 84.9 91.8 39.4 86.1 96.3
#> 22 22 31.0 58.7 84.9 91.8 39.4 86.1 96.3
#> 23 23 31.0 58.7 84.9 91.8 39.4 86.1 96.3
#> 24 24 31.0 58.7 84.9 91.8 39.4 86.1 96.3
#> 25 25 21.5 48.0 75.8 89.1 31.1 79.4 94.4
#> 26 26 21.5 48.0 75.8 89.1 31.1 79.4 94.4
#> 27 27 21.5 48.0 75.8 89.1 31.1 79.4 94.4
#> 28 28 21.5 48.0 75.8 89.1 31.1 79.4 94.4
#> 29 29 21.5 48.0 75.8 89.1 31.1 79.4 94.4
#> 30 30 15.1 33.9 65.5 81.9 20.3 69.4 87.5
#> 31 31 15.1 33.9 65.5 81.9 20.3 69.4 87.5
#> 32 32 15.1 33.9 65.5 81.9 20.3 69.4 87.5
#> 33 33 15.1 33.9 65.5 81.9 20.3 69.4 87.5
#> 34 34 15.1 33.9 65.5 81.9 20.3 69.4 87.5
#> 35 35 8.1 24.2 53.7 73.9 10.6 54.9 79.6
#> 36 36 8.1 24.2 53.7 73.9 10.6 54.9 79.6
#> 37 37 8.1 24.2 53.7 73.9 10.6 54.9 79.6
#> 38 38 8.1 24.2 53.7 73.9 10.6 54.9 79.6
#> 39 39 8.1 24.2 53.7 73.9 10.6 54.9 79.6
#> 40 40 5.4 16.6 39.2 65.2 7.8 42.0 74.5
#> 41 41 5.4 16.6 39.2 65.2 7.8 42.0 74.5
#> 42 42 5.4 16.6 39.2 65.2 7.8 42.0 74.5
#> 43 43 5.4 16.6 39.2 65.2 7.8 42.0 74.5
#> 44 44 5.4 16.6 39.2 65.2 7.8 42.0 74.5
#> 45 45 2.2 10.1 30.9 53.4 3.5 31.3 64.3
#> 46 46 2.2 10.1 30.9 53.4 3.5 31.3 64.3
#> 47 47 2.2 10.1 30.9 53.4 3.5 31.3 64.3
#> 48 48 2.2 10.1 30.9 53.4 3.5 31.3 64.3
#> 49 49 2.2 10.1 30.9 53.4 3.5 31.3 64.3
#> 50 50 1.3 5.0 21.1 40.8 1.5 22.5 49.4
#> 51 51 1.3 5.0 21.1 40.8 1.5 22.5 49.4
#> 52 52 1.3 5.0 21.1 40.8 1.5 22.5 49.4
#> 53 53 1.3 5.0 21.1 40.8 1.5 22.5 49.4
#> 54 54 1.3 5.0 21.1 40.8 1.5 22.5 49.4
#> 55 55 1.2 3.6 14.5 30.4 1.5 15.5 41.7
#> 56 56 1.2 3.6 14.5 30.4 1.5 15.5 41.7
#> 57 57 1.2 3.6 14.5 30.4 1.5 15.5 41.7
#> 58 58 1.2 3.6 14.5 30.4 1.5 15.5 41.7
#> 59 59 1.2 3.6 14.5 30.4 1.5 15.5 41.7
#> 60 60 0.4 1.7 8.5 22.7 0.7 9.0 31.3
#> 61 61 0.4 1.7 8.5 22.7 0.7 9.0 31.3
#> 62 62 0.4 1.7 8.5 22.7 0.7 9.0 31.3
#> 63 63 0.4 1.7 8.5 22.7 0.7 9.0 31.3
#> 64 64 0.4 1.7 8.5 22.7 0.7 9.0 31.3
#> 65 65 0.1 0.7 4.9 15.4 0.1 5.6 22.4
#> 66 66 0.1 0.7 4.9 15.4 0.1 5.6 22.4
#> 67 67 0.1 0.7 4.9 15.4 0.1 5.6 22.4
#> 68 68 0.1 0.7 4.9 15.4 0.1 5.6 22.4
#> 69 69 0.1 0.7 4.9 15.4 0.1 5.6 22.4
#> 70 70 0.1 0.7 3.7 9.7 0.1 3.7 15.5
#> 71 71 0.1 0.7 3.7 9.7 0.1 3.7 15.5
#> 72 72 0.1 0.7 3.7 9.7 0.1 3.7 15.5
#> 73 73 0.1 0.7 3.7 9.7 0.1 3.7 15.5
#> 74 74 0.1 0.7 3.7 9.7 0.1 3.7 15.5
#> 75 75 0.0 0.2 0.9 4.6 0.0 0.8 7.7
#> 76 76 0.0 0.2 0.9 4.6 0.0 0.8 7.7
#> 77 77 0.0 0.2 0.9 4.6 0.0 0.8 7.7
#> 78 78 0.0 0.2 0.9 4.6 0.0 0.8 7.7
#> 79 79 0.0 0.2 0.9 4.6 0.0 0.8 7.7
#> 80 80 0.0 0.0 0.2 1.1 0.0 0.5 2.2
#> 81 81 0.0 0.0 0.2 1.1 0.0 0.5 2.2
#> 82 82 0.0 0.0 0.2 1.1 0.0 0.5 2.2
#> 83 83 0.0 0.0 0.2 1.1 0.0 0.5 2.2
#> 84 84 0.0 0.0 0.2 1.1 0.0 0.5 2.2
#> 85 85 0.0 0.0 0.0 0.4 0.0 0.2 0.7
#> 86 86 0.0 0.0 0.0 0.4 0.0 0.2 0.7
#> 87 87 0.0 0.0 0.0 0.4 0.0 0.2 0.7
#> 88 88 0.0 0.0 0.0 0.4 0.0 0.2 0.7
#> 89 89 0.0 0.0 0.0 0.4 0.0 0.2 0.7
#> 90 90 0.0 0.0 0.0 0.0 0.0 0.0 0.2
#> 91 91 0.0 0.0 0.0 0.0 0.0 0.0 0.2
#> 92 92 0.0 0.0 0.0 0.0 0.0 0.0 0.2
#> 93 93 0.0 0.0 0.0 0.0 0.0 0.0 0.2
#> 94 94 0.0 0.0 0.0 0.0 0.0 0.0 0.2
#> 95 95 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
#> 97 97 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
#> 99 99 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
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiGHA2015[ppiGHA2015$score == ppiScore, ]
#> score nlFood nl100 nl150 nl200 ppp125 ppp250 ppp375
#> 50 50 1.3 5 21.1 40.8 1.5 22.5 49.4
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiGHA2015, score == ppiScore)
#> score nlFood nl100 nl150 nl200 ppp125 ppp250 ppp375
#> 50 50 1.3 5 21.1 40.8 1.5 22.5 49.4
# 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[ppiGHA2015$score == ppiScore, "nl100"]
#> [1] 5