fgt_poverty | R Documentation |
Calculates the FGT metrics, a family of poverty measures originally proposed
by \insertCitefoster1984class;textualaccessibility that capture the
extent and severity of poverty within an accessibility distribution. The FGT
family is composed of three measures that differ based on the \alpha
parameter used to calculate them (either 0, 1 or 2) and which also changes
their interpretation. Please see the details section for more information on
the interpretation of the measures.
fgt_poverty(
accessibility_data,
sociodemographic_data,
opportunity,
population,
poverty_line,
group_by = character(0)
)
accessibility_data |
A data frame. The accessibility levels whose
poverty levels should be calculated. Must contain the columns |
sociodemographic_data |
A data frame. The distribution of
sociodemographic characteristics of the population in the study area cells.
Must contain the columns |
opportunity |
A string. The name of the column in |
population |
A string. The name of the column in |
poverty_line |
A |
group_by |
A |
A data frame containing the three poverty estimates (FGT0, FGT1 and FGT2) for the study area.
The interpretation of each FGT measure depends on the \alpha
parameter
used to calculate it:
with \alpha = 0
(FGT0) the measure captures the extent of poverty
as a simple headcount - i.e. the proportion of people below the poverty line;
with \alpha = 1
(FGT1) the measure, also know as the "poverty gap
index", captures the severity of poverty as the average percentage distance
between the poverty line and the accessibility of individuals below the
poverty line;
with \alpha = 2
(FGT2) the measure simultaneously captures the
extent and the severity of poverty by calculating the number of people
below the poverty line weighted by the size of the accessibility shortfall
relative to the poverty line.
FGT values range from 0 to 1. A value of 0 indicates that every individual is above the poverty line. When every individual is below the poverty line, however, FGT0 value is 1 and FGT1 and FGT2 values approach 1.
data_dir <- system.file("extdata", package = "accessibility")
travel_matrix <- readRDS(file.path(data_dir, "travel_matrix.rds"))
land_use_data <- readRDS(file.path(data_dir, "land_use_data.rds"))
access <- cumulative_cutoff(
travel_matrix,
land_use_data,
cutoff = 30,
opportunity = "jobs",
travel_cost = "travel_time"
)
poverty <- fgt_poverty(
access,
opportunity = "jobs",
sociodemographic_data = land_use_data,
population = "population",
poverty_line = 95368
)
poverty
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