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Poverty Probability Index (PPI) lookup table for Ecuador

Usage

ppiECU2015

Format

A data frame with 11 columns and 101 rows:

score

PPI score

nlFood

Food poverty line

nl100

National poverty line (100%)

nl150

National poverty line (150%)

nl200

National poverty line (200%)

half100

Poorest half below 100% national

ppp125

Below $1.25 per day purchasing power parity (2005)

ppp200

Below $2.00 per day purchasing power parity (2005)

ppp250

Below $2.50 per day purchasing power parity (2005)

ppp500

Below $5.00 per day purchasing power parity (2005)

ppp844

Below $8.44 per day purchasing power parity (2005)

Examples

  # Access Ecuador PPI table
  ppiECU2015
#>     score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp844
#> 0       0   85.6  99.8 100.0 100.0    92.0   34.7   84.7   96.8  100.0  100.0
#> 1       1   85.6  99.8 100.0 100.0    92.0   34.7   84.7   96.8  100.0  100.0
#> 2       2   85.6  99.8 100.0 100.0    92.0   34.7   84.7   96.8  100.0  100.0
#> 3       3   85.6  99.8 100.0 100.0    92.0   34.7   84.7   96.8  100.0  100.0
#> 4       4   85.6  99.8 100.0 100.0    92.0   34.7   84.7   96.8  100.0  100.0
#> 5       5   68.7  98.3 100.0 100.0    80.3   25.9   67.5   81.2  100.0  100.0
#> 6       6   68.7  98.3 100.0 100.0    80.3   25.9   67.5   81.2  100.0  100.0
#> 7       7   68.7  98.3 100.0 100.0    80.3   25.9   67.5   81.2  100.0  100.0
#> 8       8   68.7  98.3 100.0 100.0    80.3   25.9   67.5   81.2  100.0  100.0
#> 9       9   68.7  98.3 100.0 100.0    80.3   25.9   67.5   81.2  100.0  100.0
#> 10     10   59.2  95.1 100.0 100.0    76.8   17.9   57.3   71.5   99.9  100.0
#> 11     11   59.2  95.1 100.0 100.0    76.8   17.9   57.3   71.5   99.9  100.0
#> 12     12   59.2  95.1 100.0 100.0    76.8   17.9   57.3   71.5   99.9  100.0
#> 13     13   59.2  95.1 100.0 100.0    76.8   17.9   57.3   71.5   99.9  100.0
#> 14     14   59.2  95.1 100.0 100.0    76.8   17.9   57.3   71.5   99.9  100.0
#> 15     15   37.8  93.0  99.7 100.0    70.3    9.0   36.6   64.3   99.0  100.0
#> 16     16   37.8  93.0  99.7 100.0    70.3    9.0   36.6   64.3   99.0  100.0
#> 17     17   37.8  93.0  99.7 100.0    70.3    9.0   36.6   64.3   99.0  100.0
#> 18     18   37.8  93.0  99.7 100.0    70.3    9.0   36.6   64.3   99.0  100.0
#> 19     19   37.8  93.0  99.7 100.0    70.3    9.0   36.6   64.3   99.0  100.0
#> 20     20   25.1  84.7  98.2 100.0    58.9    3.7   23.9   51.6   96.3  100.0
#> 21     21   25.1  84.7  98.2 100.0    58.9    3.7   23.9   51.6   96.3  100.0
#> 22     22   25.1  84.7  98.2 100.0    58.9    3.7   23.9   51.6   96.3  100.0
#> 23     23   25.1  84.7  98.2 100.0    58.9    3.7   23.9   51.6   96.3  100.0
#> 24     24   25.1  84.7  98.2 100.0    58.9    3.7   23.9   51.6   96.3  100.0
#> 25     25   16.6  74.2  97.1  99.7    41.7    1.8   16.2   34.3   95.0   99.9
#> 26     26   16.6  74.2  97.1  99.7    41.7    1.8   16.2   34.3   95.0   99.9
#> 27     27   16.6  74.2  97.1  99.7    41.7    1.8   16.2   34.3   95.0   99.9
#> 28     28   16.6  74.2  97.1  99.7    41.7    1.8   16.2   34.3   95.0   99.9
#> 29     29   16.6  74.2  97.1  99.7    41.7    1.8   16.2   34.3   95.0   99.9
#> 30     30    8.8  64.1  93.7  98.9    27.8    0.8    8.0   23.0   89.1   99.5
#> 31     31    8.8  64.1  93.7  98.9    27.8    0.8    8.0   23.0   89.1   99.5
#> 32     32    8.8  64.1  93.7  98.9    27.8    0.8    8.0   23.0   89.1   99.5
#> 33     33    8.8  64.1  93.7  98.9    27.8    0.8    8.0   23.0   89.1   99.5
#> 34     34    8.8  64.1  93.7  98.9    27.8    0.8    8.0   23.0   89.1   99.5
#> 35     35    6.0  50.0  88.9  98.2    20.1    0.4    5.6   15.1   83.5   99.3
#> 36     36    6.0  50.0  88.9  98.2    20.1    0.4    5.6   15.1   83.5   99.3
#> 37     37    6.0  50.0  88.9  98.2    20.1    0.4    5.6   15.1   83.5   99.3
#> 38     38    6.0  50.0  88.9  98.2    20.1    0.4    5.6   15.1   83.5   99.3
#> 39     39    6.0  50.0  88.9  98.2    20.1    0.4    5.6   15.1   83.5   99.3
#> 40     40    4.3  36.6  80.5  95.0    11.5    0.2    3.8   10.3   73.8   98.1
#> 41     41    4.3  36.6  80.5  95.0    11.5    0.2    3.8   10.3   73.8   98.1
#> 42     42    4.3  36.6  80.5  95.0    11.5    0.2    3.8   10.3   73.8   98.1
#> 43     43    4.3  36.6  80.5  95.0    11.5    0.2    3.8   10.3   73.8   98.1
#> 44     44    4.3  36.6  80.5  95.0    11.5    0.2    3.8   10.3   73.8   98.1
#> 45     45    2.1  24.6  65.2  87.8     8.1    0.2    2.0    6.1   57.7   93.7
#> 46     46    2.1  24.6  65.2  87.8     8.1    0.2    2.0    6.1   57.7   93.7
#> 47     47    2.1  24.6  65.2  87.8     8.1    0.2    2.0    6.1   57.7   93.7
#> 48     48    2.1  24.6  65.2  87.8     8.1    0.2    2.0    6.1   57.7   93.7
#> 49     49    2.1  24.6  65.2  87.8     8.1    0.2    2.0    6.1   57.7   93.7
#> 50     50    0.9  12.9  51.9  81.6     3.3    0.0    0.9    2.5   43.2   89.9
#> 51     51    0.9  12.9  51.9  81.6     3.3    0.0    0.9    2.5   43.2   89.9
#> 52     52    0.9  12.9  51.9  81.6     3.3    0.0    0.9    2.5   43.2   89.9
#> 53     53    0.9  12.9  51.9  81.6     3.3    0.0    0.9    2.5   43.2   89.9
#> 54     54    0.9  12.9  51.9  81.6     3.3    0.0    0.9    2.5   43.2   89.9
#> 55     55    0.2   6.5  36.4  67.7     1.2    0.0    0.2    0.9   28.7   81.0
#> 56     56    0.2   6.5  36.4  67.7     1.2    0.0    0.2    0.9   28.7   81.0
#> 57     57    0.2   6.5  36.4  67.7     1.2    0.0    0.2    0.9   28.7   81.0
#> 58     58    0.2   6.5  36.4  67.7     1.2    0.0    0.2    0.9   28.7   81.0
#> 59     59    0.2   6.5  36.4  67.7     1.2    0.0    0.2    0.9   28.7   81.0
#> 60     60    0.0   3.1  24.0  55.1     0.5    0.0    0.0    0.1   17.3   67.9
#> 61     61    0.0   3.1  24.0  55.1     0.5    0.0    0.0    0.1   17.3   67.9
#> 62     62    0.0   3.1  24.0  55.1     0.5    0.0    0.0    0.1   17.3   67.9
#> 63     63    0.0   3.1  24.0  55.1     0.5    0.0    0.0    0.1   17.3   67.9
#> 64     64    0.0   3.1  24.0  55.1     0.5    0.0    0.0    0.1   17.3   67.9
#> 65     65    0.0   1.1  12.1  33.0     0.2    0.0    0.0    0.1   10.3   52.9
#> 66     66    0.0   1.1  12.1  33.0     0.2    0.0    0.0    0.1   10.3   52.9
#> 67     67    0.0   1.1  12.1  33.0     0.2    0.0    0.0    0.1   10.3   52.9
#> 68     68    0.0   1.1  12.1  33.0     0.2    0.0    0.0    0.1   10.3   52.9
#> 69     69    0.0   1.1  12.1  33.0     0.2    0.0    0.0    0.1   10.3   52.9
#> 70     70    0.0   0.9   6.4  21.8     0.2    0.0    0.0    0.1    4.6   38.8
#> 71     71    0.0   0.9   6.4  21.8     0.2    0.0    0.0    0.1    4.6   38.8
#> 72     72    0.0   0.9   6.4  21.8     0.2    0.0    0.0    0.1    4.6   38.8
#> 73     73    0.0   0.9   6.4  21.8     0.2    0.0    0.0    0.1    4.6   38.8
#> 74     74    0.0   0.9   6.4  21.8     0.2    0.0    0.0    0.1    4.6   38.8
#> 75     75    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   26.6
#> 76     76    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   26.6
#> 77     77    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   26.6
#> 78     78    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   26.6
#> 79     79    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   26.6
#> 80     80    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 81     81    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 82     82    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 83     83    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 84     84    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 85     85    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 86     86    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 87     87    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 88     88    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 89     89    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 90     90    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 91     91    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 92     92    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 93     93    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 94     94    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 95     95    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 96     96    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 97     97    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 98     98    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 99     99    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2
#> 100   100    0.0   0.9   6.4  16.4     0.2    0.0    0.0    0.1    4.6   24.2

  # Given a specific PPI score (from 0 - 100), get the row of poverty
  # probabilities from PPI table it corresponds to
  ppiScore <- 50
  ppiECU2015[ppiECU2015$score == ppiScore, ]
#>    score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp844
#> 50    50    0.9  12.9  51.9  81.6     3.3      0    0.9    2.5   43.2   89.9

  # Use subset() function to get the row of poverty probabilities corresponding
  # to specific PPI score
  ppiScore <- 50
  subset(ppiECU2015, score == ppiScore)
#>    score nlFood nl100 nl150 nl200 half100 ppp125 ppp200 ppp250 ppp500 ppp844
#> 50    50    0.9  12.9  51.9  81.6     3.3      0    0.9    2.5   43.2   89.9

  # 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
  ppiECU2015[ppiECU2015$score == ppiScore, "nl100"]
#> [1] 12.9