Delmål 1: Afskaf fattigdom
Økonomisk udsatte
FN 1.2.1 Andel af befolkningen, som lever under fattigdomsgrænsen, opdelt på køn og aldersgruppe
# Import
SOXOU01_raw <-
statgl_url("SOXOU01", lang = language) |>
statgl_fetch(
"inventory variable" = px_all("Andel*"),
.col_code = T
) |>
as_tibble()
# Transform
SOXOU01 <-
SOXOU01_raw |>
mutate(year = year |> make_date())
# Plot
SOXOU01 |>
ggplot(aes(
x = year,
y = value,
fill = `inventory variable`
)) +
geom_col(position = "dodge") +
scale_y_continuous(labels = scales::percent_format(
scale = 1,
accuracy = 1,
big.mark = ".",
decimal.mark = ","
)) +
theme_statgl() +
scale_fill_statgl(guide = guide_legend(nrow = 2)) +
labs(
title = sdg1$figs$fig1$title[language],
subtitle = sdg1$figs$fig1$sub[language],
x = " ",
y = " ",
fill = sdg1$figs$fig1$fill[language],
caption = sdg1$figs$fig1$cap[language]
)
# Transform
SOXOU01 <-
SOXOU01_raw |>
filter(year >= year(Sys.time()) - 5) |>
mutate(year = year %>% fct_inorder()) |>
spread(2, 3) |>
mutate(`inventory variable` = `inventory variable` |> str_to_sentence())
# Table
SOXOU01 |>
rename(" " = 1) |>
statgl_table() |>
add_footnote(
sdg1$figs$fig1$sub[language],
notation = "symbol")| 2020 | 2021 | 2022 | 2023 | |
|---|---|---|---|---|
| Andel under 50% | 4,1 | 4,1 | 4,4 | 4,6 |
| Andel under 60% | 7,7 | 7,7 | 8,2 | 8,2 |
|
* Procentvis andel af befolkningen med en indkomst under 50
eller 60% af medianindkomsten i 3 sammenhængende år |
# Import
SOXOU01_raw <-
statgl_url("SOXOU01", lang = language) |>
statgl_fetch(
"inventory variable" = px_all("Andel*"),
"gender" = 1:2,
.col_code = T
) |>
as_tibble()
# Transform
SOXOU01 <-
SOXOU01_raw |>
mutate(
year = year |> make_date(),
gender = gender |> fct_inorder()
)
# Plot
SOXOU01 |>
mutate(`inventory variable` = `inventory variable` |> str_to_sentence()) |>
ggplot(aes(
x = year,
y = value,
fill = gender
)) +
geom_col(position = "dodge") +
scale_y_continuous(labels = scales::percent_format(
scale = 1
)) +
facet_wrap(~ `inventory variable`) +
theme_statgl() +
scale_fill_statgl(reverse = TRUE) +
labs(
title = sdg1$figs$fig2$title[language],
subtitle = sdg1$figs$fig1$sub[language],
x = " ",
y = " ",
fill = " ",
caption = sdg1$figs$fig1$cap[language]
)
# Transform
SOXOU01 <-
SOXOU01_raw |>
filter(year >= year(Sys.time()) - 5) |>
mutate(year = year |> fct_inorder()) |>
spread(3, 4) |>
mutate(`inventory variable` = `inventory variable` |> str_to_sentence())
# Table
SOXOU01 |>
select(-1) |>
rename(" " = 1) |>
statgl_table() |>
pack_rows(index = table(SOXOU01[[1]])) |>
add_footnote(
sdg1$figs$fig1$sub[language],
notation = "symbol")| 2020 | 2021 | 2022 | 2023 | |
|---|---|---|---|---|
| Andel under 50% | ||||
| Kvinder | 3,7 | 3,8 | 4,1 | 4,1 |
| Mænd | 4,5 | 4,3 | 4,8 | 5,0 |
| Andel under 60% | ||||
| Kvinder | 7,3 | 7,4 | 7,7 | 7,8 |
| Mænd | 8,1 | 7,9 | 8,6 | 8,7 |
|
* Procentvis andel af befolkningen med en indkomst under 50
eller 60% af medianindkomsten i 3 sammenhængende år |
||||
# Import
SOXOU04_raw <-
statgl_url("SOXOU04", lang = language) |>
statgl_fetch(
"inventory variable" = px_all("Andel*"),
"age" = 2:6,
.col_code = T
) |>
as_tibble()
# Transform
SOXOU04 <-
SOXOU04_raw |>
mutate(year = year |> make_date())
# Plot
SOXOU04 |>
mutate(`inventory variable` = `inventory variable` |> str_to_sentence()) |>
ggplot(aes(
x = year,
y = value,
color = age
)) +
geom_line(size = 2) +
facet_wrap(~ `inventory variable`, scales = "free_y") +
scale_y_continuous(labels = scales::percent_format(
scale = 1,
big.mark = ".",
decimal.mark = ","
)) +
theme_statgl() +
scale_color_statgl(reverse = TRUE) +
labs(
title = sdg1$figs$fig3$title[language],
subtitle = sdg1$figs$fig3$sub[language],
x = " ",
y = " ",
color = sdg1$figs$fig3$color[language],
caption = sdg1$figs$fig3$cap[language]
)
# Transform
SOXOU04 <-
SOXOU04_raw |>
filter(year >= year(Sys.time()) - 5) |>
mutate(year = year |> fct_inorder()) |>
spread(3, 4) |>
mutate(`inventory variable` = `inventory variable` |> str_to_sentence())
# Table
SOXOU04 |>
select(-1) |>
rename(" " = 1) |>
statgl_table() |>
pack_rows(index = table(SOXOU04[[1]])) |>
add_footnote(
sdg1$figs$fig3$foot[language],
notation = "symbol")| 2020 | 2021 | 2022 | 2023 | |
|---|---|---|---|---|
| Andel under 50% | ||||
| -29 | 10,9 | 10,8 | 12,3 | 13,1 |
| 30-39 | 5,0 | 4,9 | 5,3 | 5,3 |
| 40-49 | 3,1 | 3,1 | 3,0 | 3,1 |
| 50-60 | 2,4 | 2,4 | 2,6 | 2,7 |
| 60+ | 1,5 | 1,5 | 1,6 | 1,7 |
| Andel under 60% | ||||
| -29 | 17,5 | 17,6 | 19,2 | 20,1 |
| 30-39 | 9,0 | 8,6 | 9,3 | 9,3 |
| 40-49 | 5,3 | 5,4 | 5,5 | 5,8 |
| 50-60 | 5,0 | 4,7 | 4,9 | 5,2 |
| 60+ | 3,5 | 3,5 | 3,9 | 3,8 |
|
* Procentvis andel af befolkningen med en indkomst under 50
eller 60% af medianindkomsten i 3 sammenhængende år. Tabellen inkluderer kun personer over 18 år. |
||||
# Tak til podcasten VELKOMMEN TIL INTERNETTET for god lytter!Forklaring
Statistikken over økonomisk udsatte har en bestemt analysepopulation, som ikke dækker hele befolkningen. Eksempelvis er studerende, beboere på sociale institutioner etc. ikke medtaget i analysen. Desuden skal man have en indkomst på 50 eller 60% af medianindkomsten for at tælle som økonomisk udsat.
At-risk-of-poverty rate
FN 1.2.1 Andel af befolkningen, som lever i relativ fattigdom
# Import
INXIU101_raw <-
statgl_url("INXIU101", lang = language) |>
statgl_fetch(
indicator = 2:4,
time = px_all(),
.col_code = T
) |>
as_tibble()
# Transform
INXIU101 <-
INXIU101_raw |>
mutate(
time = time |> make_date(),
indicator = indicator |> as.factor() |> fct_rev()
)
# Plot
INXIU101 |>
ggplot(aes(
x = time,
y = value,
fill = indicator
)) +
geom_area(position = "identity") +
scale_y_continuous(labels = scales::percent_format(
scale = 1,
accuracy = 1.1,
big.mark = ".",
decimal.mark = ","
)) +
theme_statgl() +
scale_fill_statgl(reverse = TRUE, guide = guide_legend(nrow = 3)) +
labs(
title = "At-risk-of-povery rate",
x = " ",
y = " ",
fill = sdg1$figs$fig1$fill[language],
caption = sdg1$figs$fig4$cap[language]
)
Forklaring
Grønland har ingen officiel fattigdomsgrænse, men internationalt benyttes målet at-risk-of-poverty rate (ROP) som en indikator for relativ fattigdom.
Målet beregnes som den andel af befolkningen, der bor i en husstand, hvor den disponible husstandsindkomst ligger under en fastsat procentdel (her 40, 50 og 60 pct.) af medianindkomsten.
Offentlige midler
FN 1.a.2 Andel af de samlede offentlige udgifter afsat til kerneydelser (undervisning, sundhed og social beskyttelse)
# Import
OFXFUNK_raw <-
statgl_url("OFXFUNK", lang = language) |>
statgl_fetch(
"function" = c(0, 33, 44, 50),
sector = c(0, 1, 2),
.col_code = T
) |>
as_tibble()
# Transform
vec <- 4:6
names(vec) <- trimws(unique(OFXFUNK_raw[[2]]) |> str_remove_all("[:digit:]\\.") |> str_remove_all("1 "))[-1]
OFXFUNK <-
OFXFUNK_raw |>
mutate(value = value |> replace_na(0)) |>
spread(2, 4) |>
select(1:2, unique(OFXFUNK_raw[[2]])) |>
rename(
total = 3,
sund = 4,
under = 5,
social = 6
) |>
mutate(other = total - (sund + under + social)) |>
rename(vec) |>
select(-3) |>
gather(key, value, -(1:2)) |>
mutate(
key = key |> str_replace("other", sdg1$figs$fig5$other[language] |> unlist()),
key = key |> fct_inorder(),
sector = sector |> fct_inorder(),
time = time |> make_date()
)
# Plot
OFXFUNK |>
ggplot(aes(
x = time,
y = value,
fill = key
)) +
geom_area(position = "fill") +
facet_wrap(~ sector) +
scale_fill_statgl(palette = "spring", reverse = TRUE) +
theme_statgl() +
scale_y_continuous(labels = scales::percent_format()) +
labs(
title = sdg1$figs$fig5$title[language],
subtitle = sdg1$figs$fig5$sub[language],
x = " ",
y = " ",
caption = sdg1$figs$fig5$cap[language],
fill = sdg1$figs$fig5$fill[language]
)
Længevarende offentlig forsørgelse
FN 1.3 Andel af befolkningen i den arbejdsdygtige alder på længevarende offentlig forsørgelse
# Import
ARXLEDVAR_raw <-
statgl_url("ARXLEDVAR", lang = language) |>
statgl_fetch(
taar_kvar = px_all(),
kvar_led = 1:4,
opg_var = "procent",
.col_code = T
) |>
as_tibble()
# Transform
ARXLEDVAR <-
ARXLEDVAR_raw |>
mutate(kvar_led = fct_inorder(kvar_led)) |>
mutate(taar_kvar = str_replace_all(taar_kvar, "Q", "-")) |>
mutate(taar_kvar = yq(taar_kvar))
# Plot
ARXLEDVAR |>
ggplot(aes(
x = taar_kvar,
y = value,
fill = kvar_led
)) +
geom_area(position = "fill") +
scale_x_date() +
scale_y_continuous(labels = scales::percent_format()) +
scale_fill_statgl(reverse = T, guide = guide_legend(nrow = 2, byrow = T)) +
theme_statgl() +
labs(
title = sdg1$figs$fig6$title[language],
subtitle = sdg1$figs$fig6$sub[language],
x = " ",
y = " ",
fill = sdg1$figs$fig6$fill[language],
caption = sdg1$figs$fig6$cap[language]
)