Poverty Probability Index (PPI) lookup table for Philippines using new poverty definitions
Source:R/00_philippines.R
ppiPHL2014_a.RdPoverty Probability Index (PPI) lookup table for Philippines using new poverty definitions
Format
A data frame with 11 columns and 101 rows:
scorePPI score
nl100National poverty line (100%)
nl150National poverty line (150%)
nl200National poverty line (200%)
medianPoorest 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)
ppp190Below $1.90 per day purchasing power parity (2011)
ppp310Below $3.10 per day purchasing power parity (2011)
Examples
# Access Philippines PPI table
ppiPHL2014_a
#> score nl100 nl150 nl200 median 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 5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 6 6 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 7 7 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 8 8 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 9 9 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
#> 10 10 91.8 99.1 99.9 74.8 79.1 97.9 99.2 100.0 71.4 96.6
#> 11 11 91.8 99.1 99.9 74.8 79.1 97.9 99.2 100.0 71.4 96.6
#> 12 12 91.8 99.1 99.9 74.8 79.1 97.9 99.2 100.0 71.4 96.6
#> 13 13 91.8 99.1 99.9 74.8 79.1 97.9 99.2 100.0 71.4 96.6
#> 14 14 91.8 99.1 99.9 74.8 79.1 97.9 99.2 100.0 71.4 96.6
#> 15 15 88.6 98.7 99.9 62.3 69.6 97.0 98.9 100.0 56.5 94.5
#> 16 16 88.6 98.7 99.9 62.3 69.6 97.0 98.9 100.0 56.5 94.5
#> 17 17 88.6 98.7 99.9 62.3 69.6 97.0 98.9 100.0 56.5 94.5
#> 18 18 88.6 98.7 99.9 62.3 69.6 97.0 98.9 100.0 56.5 94.5
#> 19 19 88.6 98.7 99.9 62.3 69.6 97.0 98.9 100.0 56.5 94.5
#> 20 20 79.4 97.4 99.4 47.2 53.9 92.3 97.9 100.0 39.0 88.4
#> 21 21 79.4 97.4 99.4 47.2 53.9 92.3 97.9 100.0 39.0 88.4
#> 22 22 79.4 97.4 99.4 47.2 53.9 92.3 97.9 100.0 39.0 88.4
#> 23 23 79.4 97.4 99.4 47.2 53.9 92.3 97.9 100.0 39.0 88.4
#> 24 24 79.4 97.4 99.4 47.2 53.9 92.3 97.9 100.0 39.0 88.4
#> 25 25 64.2 91.5 98.1 28.1 33.8 82.1 92.8 99.9 23.4 75.8
#> 26 26 64.2 91.5 98.1 28.1 33.8 82.1 92.8 99.9 23.4 75.8
#> 27 27 64.2 91.5 98.1 28.1 33.8 82.1 92.8 99.9 23.4 75.8
#> 28 28 64.2 91.5 98.1 28.1 33.8 82.1 92.8 99.9 23.4 75.8
#> 29 29 64.2 91.5 98.1 28.1 33.8 82.1 92.8 99.9 23.4 75.8
#> 30 30 49.9 85.2 95.9 18.8 24.5 72.0 87.3 99.7 15.8 62.9
#> 31 31 49.9 85.2 95.9 18.8 24.5 72.0 87.3 99.7 15.8 62.9
#> 32 32 49.9 85.2 95.9 18.8 24.5 72.0 87.3 99.7 15.8 62.9
#> 33 33 49.9 85.2 95.9 18.8 24.5 72.0 87.3 99.7 15.8 62.9
#> 34 34 49.9 85.2 95.9 18.8 24.5 72.0 87.3 99.7 15.8 62.9
#> 35 35 32.9 75.0 92.6 10.4 13.6 56.2 78.5 99.1 8.2 46.6
#> 36 36 32.9 75.0 92.6 10.4 13.6 56.2 78.5 99.1 8.2 46.6
#> 37 37 32.9 75.0 92.6 10.4 13.6 56.2 78.5 99.1 8.2 46.6
#> 38 38 32.9 75.0 92.6 10.4 13.6 56.2 78.5 99.1 8.2 46.6
#> 39 39 32.9 75.0 92.6 10.4 13.6 56.2 78.5 99.1 8.2 46.6
#> 40 40 18.9 58.3 81.5 5.3 6.3 38.9 62.8 96.4 3.6 29.1
#> 41 41 18.9 58.3 81.5 5.3 6.3 38.9 62.8 96.4 3.6 29.1
#> 42 42 18.9 58.3 81.5 5.3 6.3 38.9 62.8 96.4 3.6 29.1
#> 43 43 18.9 58.3 81.5 5.3 6.3 38.9 62.8 96.4 3.6 29.1
#> 44 44 18.9 58.3 81.5 5.3 6.3 38.9 62.8 96.4 3.6 29.1
#> 45 45 9.4 38.7 65.7 2.5 2.9 21.9 42.6 91.4 1.8 16.0
#> 46 46 9.4 38.7 65.7 2.5 2.9 21.9 42.6 91.4 1.8 16.0
#> 47 47 9.4 38.7 65.7 2.5 2.9 21.9 42.6 91.4 1.8 16.0
#> 48 48 9.4 38.7 65.7 2.5 2.9 21.9 42.6 91.4 1.8 16.0
#> 49 49 9.4 38.7 65.7 2.5 2.9 21.9 42.6 91.4 1.8 16.0
#> 50 50 5.0 24.1 51.2 0.7 1.2 12.1 27.2 83.1 0.6 8.5
#> 51 51 5.0 24.1 51.2 0.7 1.2 12.1 27.2 83.1 0.6 8.5
#> 52 52 5.0 24.1 51.2 0.7 1.2 12.1 27.2 83.1 0.6 8.5
#> 53 53 5.0 24.1 51.2 0.7 1.2 12.1 27.2 83.1 0.6 8.5
#> 54 54 5.0 24.1 51.2 0.7 1.2 12.1 27.2 83.1 0.6 8.5
#> 55 55 1.5 12.3 31.6 0.1 0.2 5.3 14.3 69.2 0.1 3.3
#> 56 56 1.5 12.3 31.6 0.1 0.2 5.3 14.3 69.2 0.1 3.3
#> 57 57 1.5 12.3 31.6 0.1 0.2 5.3 14.3 69.2 0.1 3.3
#> 58 58 1.5 12.3 31.6 0.1 0.2 5.3 14.3 69.2 0.1 3.3
#> 59 59 1.5 12.3 31.6 0.1 0.2 5.3 14.3 69.2 0.1 3.3
#> 60 60 0.8 6.0 18.2 0.0 0.1 2.7 6.4 52.2 0.0 1.8
#> 61 61 0.8 6.0 18.2 0.0 0.1 2.7 6.4 52.2 0.0 1.8
#> 62 62 0.8 6.0 18.2 0.0 0.1 2.7 6.4 52.2 0.0 1.8
#> 63 63 0.8 6.0 18.2 0.0 0.1 2.7 6.4 52.2 0.0 1.8
#> 64 64 0.8 6.0 18.2 0.0 0.1 2.7 6.4 52.2 0.0 1.8
#> 65 65 0.2 2.5 10.1 0.0 0.0 0.7 3.2 37.1 0.0 0.6
#> 66 66 0.2 2.5 10.1 0.0 0.0 0.7 3.2 37.1 0.0 0.6
#> 67 67 0.2 2.5 10.1 0.0 0.0 0.7 3.2 37.1 0.0 0.6
#> 68 68 0.2 2.5 10.1 0.0 0.0 0.7 3.2 37.1 0.0 0.6
#> 69 69 0.2 2.5 10.1 0.0 0.0 0.7 3.2 37.1 0.0 0.6
#> 70 70 0.0 0.8 3.8 0.0 0.0 0.2 1.0 21.3 0.0 0.1
#> 71 71 0.0 0.8 3.8 0.0 0.0 0.2 1.0 21.3 0.0 0.1
#> 72 72 0.0 0.8 3.8 0.0 0.0 0.2 1.0 21.3 0.0 0.1
#> 73 73 0.0 0.8 3.8 0.0 0.0 0.2 1.0 21.3 0.0 0.1
#> 74 74 0.0 0.8 3.8 0.0 0.0 0.2 1.0 21.3 0.0 0.1
#> 75 75 0.0 0.6 1.7 0.0 0.0 0.1 0.7 13.1 0.0 0.1
#> 76 76 0.0 0.6 1.7 0.0 0.0 0.1 0.7 13.1 0.0 0.1
#> 77 77 0.0 0.6 1.7 0.0 0.0 0.1 0.7 13.1 0.0 0.1
#> 78 78 0.0 0.6 1.7 0.0 0.0 0.1 0.7 13.1 0.0 0.1
#> 79 79 0.0 0.6 1.7 0.0 0.0 0.1 0.7 13.1 0.0 0.1
#> 80 80 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.0 0.0 0.0
#> 81 81 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.0 0.0 0.0
#> 82 82 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.0 0.0 0.0
#> 83 83 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.0 0.0 0.0
#> 84 84 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.0 0.0 0.0
#> 85 85 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.3 0.0 0.0
#> 86 86 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.3 0.0 0.0
#> 87 87 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.3 0.0 0.0
#> 88 88 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.3 0.0 0.0
#> 89 89 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.3 0.0 0.0
#> 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
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiPHL2014_a[ppiPHL2014_a$score == ppiScore, ]
#> score nl100 nl150 nl200 median ppp125 ppp200 ppp250 ppp500 ppp190 ppp310
#> 50 50 5 24.1 51.2 0.7 1.2 12.1 27.2 83.1 0.6 8.5
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiPHL2014_a, score == ppiScore)
#> score nl100 nl150 nl200 median ppp125 ppp200 ppp250 ppp500 ppp190 ppp310
#> 50 50 5 24.1 51.2 0.7 1.2 12.1 27.2 83.1 0.6 8.5
# 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
ppiPHL2014_a[ppiPHL2014_a$score == ppiScore, "nl100"]
#> [1] 5