Poverty Probability Index (PPI) lookup table for Kyrgyzstan
Format
A data frame with 9 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)
Examples
# Access Kyrgyzstan PPI table
ppiKGZ2015
#> score nl100 nl150 nl200 median ppp125 ppp200 ppp250 ppp500
#> 0 0 100.0 100.0 100.0 91.5 5.8 88.9 100.0 100.0
#> 1 1 100.0 100.0 100.0 91.5 5.8 88.9 100.0 100.0
#> 2 2 100.0 100.0 100.0 91.5 5.8 88.9 100.0 100.0
#> 3 3 100.0 100.0 100.0 91.5 5.8 88.9 100.0 100.0
#> 4 4 100.0 100.0 100.0 91.5 5.8 88.9 100.0 100.0
#> 5 5 98.0 100.0 100.0 88.6 1.6 71.4 92.0 100.0
#> 6 6 98.0 100.0 100.0 88.6 1.6 71.4 92.0 100.0
#> 7 7 98.0 100.0 100.0 88.6 1.6 71.4 92.0 100.0
#> 8 8 98.0 100.0 100.0 88.6 1.6 71.4 92.0 100.0
#> 9 9 98.0 100.0 100.0 88.6 1.6 71.4 92.0 100.0
#> 10 10 96.6 100.0 100.0 59.9 1.4 51.3 78.7 100.0
#> 11 11 96.6 100.0 100.0 59.9 1.4 51.3 78.7 100.0
#> 12 12 96.6 100.0 100.0 59.9 1.4 51.3 78.7 100.0
#> 13 13 96.6 100.0 100.0 59.9 1.4 51.3 78.7 100.0
#> 14 14 96.6 100.0 100.0 59.9 1.4 51.3 78.7 100.0
#> 15 15 89.9 100.0 100.0 55.3 1.4 38.7 74.5 100.0
#> 16 16 89.9 100.0 100.0 55.3 1.4 38.7 74.5 100.0
#> 17 17 89.9 100.0 100.0 55.3 1.4 38.7 74.5 100.0
#> 18 18 89.9 100.0 100.0 55.3 1.4 38.7 74.5 100.0
#> 19 19 89.9 100.0 100.0 55.3 1.4 38.7 74.5 100.0
#> 20 20 77.3 99.8 100.0 39.5 1.4 24.3 58.4 100.0
#> 21 21 77.3 99.8 100.0 39.5 1.4 24.3 58.4 100.0
#> 22 22 77.3 99.8 100.0 39.5 1.4 24.3 58.4 100.0
#> 23 23 77.3 99.8 100.0 39.5 1.4 24.3 58.4 100.0
#> 24 24 77.3 99.8 100.0 39.5 1.4 24.3 58.4 100.0
#> 25 25 68.0 99.1 100.0 30.5 1.1 15.8 45.7 100.0
#> 26 26 68.0 99.1 100.0 30.5 1.1 15.8 45.7 100.0
#> 27 27 68.0 99.1 100.0 30.5 1.1 15.8 45.7 100.0
#> 28 28 68.0 99.1 100.0 30.5 1.1 15.8 45.7 100.0
#> 29 29 68.0 99.1 100.0 30.5 1.1 15.8 45.7 100.0
#> 30 30 46.5 96.1 100.0 20.2 0.9 9.3 27.1 99.7
#> 31 31 46.5 96.1 100.0 20.2 0.9 9.3 27.1 99.7
#> 32 32 46.5 96.1 100.0 20.2 0.9 9.3 27.1 99.7
#> 33 33 46.5 96.1 100.0 20.2 0.9 9.3 27.1 99.7
#> 34 34 46.5 96.1 100.0 20.2 0.9 9.3 27.1 99.7
#> 35 35 40.7 89.4 99.9 12.6 0.3 4.5 19.2 96.0
#> 36 36 40.7 89.4 99.9 12.6 0.3 4.5 19.2 96.0
#> 37 37 40.7 89.4 99.9 12.6 0.3 4.5 19.2 96.0
#> 38 38 40.7 89.4 99.9 12.6 0.3 4.5 19.2 96.0
#> 39 39 40.7 89.4 99.9 12.6 0.3 4.5 19.2 96.0
#> 40 40 15.8 76.6 95.6 6.2 0.1 3.9 10.0 92.1
#> 41 41 15.8 76.6 95.6 6.2 0.1 3.9 10.0 92.1
#> 42 42 15.8 76.6 95.6 6.2 0.1 3.9 10.0 92.1
#> 43 43 15.8 76.6 95.6 6.2 0.1 3.9 10.0 92.1
#> 44 44 15.8 76.6 95.6 6.2 0.1 3.9 10.0 92.1
#> 45 45 11.7 65.2 90.5 5.4 0.1 2.5 7.3 85.2
#> 46 46 11.7 65.2 90.5 5.4 0.1 2.5 7.3 85.2
#> 47 47 11.7 65.2 90.5 5.4 0.1 2.5 7.3 85.2
#> 48 48 11.7 65.2 90.5 5.4 0.1 2.5 7.3 85.2
#> 49 49 11.7 65.2 90.5 5.4 0.1 2.5 7.3 85.2
#> 50 50 4.1 43.9 80.5 1.2 0.0 0.2 3.1 69.5
#> 51 51 4.1 43.9 80.5 1.2 0.0 0.2 3.1 69.5
#> 52 52 4.1 43.9 80.5 1.2 0.0 0.2 3.1 69.5
#> 53 53 4.1 43.9 80.5 1.2 0.0 0.2 3.1 69.5
#> 54 54 4.1 43.9 80.5 1.2 0.0 0.2 3.1 69.5
#> 55 55 3.9 27.3 60.2 0.7 0.0 0.2 2.2 50.3
#> 56 56 3.9 27.3 60.2 0.7 0.0 0.2 2.2 50.3
#> 57 57 3.9 27.3 60.2 0.7 0.0 0.2 2.2 50.3
#> 58 58 3.9 27.3 60.2 0.7 0.0 0.2 2.2 50.3
#> 59 59 3.9 27.3 60.2 0.7 0.0 0.2 2.2 50.3
#> 60 60 2.9 21.4 51.0 0.4 0.0 0.2 1.6 39.8
#> 61 61 2.9 21.4 51.0 0.4 0.0 0.2 1.6 39.8
#> 62 62 2.9 21.4 51.0 0.4 0.0 0.2 1.6 39.8
#> 63 63 2.9 21.4 51.0 0.4 0.0 0.2 1.6 39.8
#> 64 64 2.9 21.4 51.0 0.4 0.0 0.2 1.6 39.8
#> 65 65 1.3 6.9 38.8 0.4 0.0 0.2 0.9 25.0
#> 66 66 1.3 6.9 38.8 0.4 0.0 0.2 0.9 25.0
#> 67 67 1.3 6.9 38.8 0.4 0.0 0.2 0.9 25.0
#> 68 68 1.3 6.9 38.8 0.4 0.0 0.2 0.9 25.0
#> 69 69 1.3 6.9 38.8 0.4 0.0 0.2 0.9 25.0
#> 70 70 1.2 4.5 31.6 0.4 0.0 0.2 0.9 19.6
#> 71 71 1.2 4.5 31.6 0.4 0.0 0.2 0.9 19.6
#> 72 72 1.2 4.5 31.6 0.4 0.0 0.2 0.9 19.6
#> 73 73 1.2 4.5 31.6 0.4 0.0 0.2 0.9 19.6
#> 74 74 1.2 4.5 31.6 0.4 0.0 0.2 0.9 19.6
#> 75 75 1.2 4.5 18.9 0.4 0.0 0.2 0.9 12.1
#> 76 76 1.2 4.5 18.9 0.4 0.0 0.2 0.9 12.1
#> 77 77 1.2 4.5 18.9 0.4 0.0 0.2 0.9 12.1
#> 78 78 1.2 4.5 18.9 0.4 0.0 0.2 0.9 12.1
#> 79 79 1.2 4.5 18.9 0.4 0.0 0.2 0.9 12.1
#> 80 80 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 81 81 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 82 82 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 83 83 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 84 84 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 85 85 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 86 86 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 87 87 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 88 88 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 89 89 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 90 90 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 91 91 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 92 92 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 93 93 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 94 94 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 95 95 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 96 96 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 97 97 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 98 98 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 99 99 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
#> 100 100 1.2 4.5 18.7 0.4 0.0 0.2 0.9 12.1
# Given a specific PPI score (from 0 - 100), get the row of poverty
# probabilities from PPI table it corresponds to
ppiScore <- 50
ppiKGZ2015[ppiKGZ2015$score == ppiScore, ]
#> score nl100 nl150 nl200 median ppp125 ppp200 ppp250 ppp500
#> 50 50 4.1 43.9 80.5 1.2 0 0.2 3.1 69.5
# Use subset() function to get the row of poverty probabilities corresponding
# to specific PPI score
ppiScore <- 50
subset(ppiKGZ2015, score == ppiScore)
#> score nl100 nl150 nl200 median ppp125 ppp200 ppp250 ppp500
#> 50 50 4.1 43.9 80.5 1.2 0 0.2 3.1 69.5
# 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
ppiKGZ2015[ppiKGZ2015$score == ppiScore, "nl100"]
#> [1] 4.1