| source | dataset | Title | Download | Compile |
|---|---|---|---|---|
| oecd | EO | Economic Outlook | 2026-04-12 | [2026-08-13] |
| oecd | EO112_INTERNET | Economic Outlook No 112 - November 2022 | NA | [2026-08-11] |
| oecd | EO111_INTERNET | Economic Outlook No 111 - June 2022 | NA | [2026-08-11] |
| oecd | EO110_INTERNET | Economic Outlook No 110 - December 2021 | NA | [2026-08-11] |
| oecd | EO109_INTERNET | Economic Outlook No 109 - May 2021 | NA | [2026-08-11] |
| oecd | EO108_INTERNET | Economic Outlook No 108 - December 2020 | NA | [2026-08-11] |
Economic Outlook No 108 - December 2020
Data - OECD
Info
LAST_DOWNLOAD
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2026-08-13 |
Last
| obsTime | Nobs |
|---|---|
| 2020-Q4 | 3879 |
VARIABLE
Code
EO108_INTERNET |>
left_join(EO108_INTERNET_var$VARIABLE, by = "VARIABLE") %>%
mutate(Variable = Variable |> substr(1, 120)) |>
group_by(VARIABLE, Variable) |>
summarise(Nobs = n()) |>
arrange(-Nobs) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}FREQUENCY
Code
EO108_INTERNET |>
left_join(EO108_INTERNET_var$FREQUENCY, by = "FREQUENCY") |>
group_by(FREQUENCY, Frequency) |>
summarise(Nobs = n()) |>
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| FREQUENCY | Frequency | Nobs |
|---|---|---|
| Q | Quarterly | 715318 |
| A | Annual | 357547 |
Output Gap (% of GDP)
Germany, Spain, Greece, Italy
Code
EO108_INTERNET |>
filter(FREQUENCY == "A",
VARIABLE == "GAP",
LOCATION %in% c("DEU", "ESP", "GRC", "ITA")) |>
left_join(EO108_INTERNET_var$LOCATION, by = "LOCATION") |>
year_to_date() |>
select(Location, date, obsValue) |>
arrange(Location, date) |>
mutate(obsValue = obsValue/100) |>
left_join(colors, by = c("Location" = "country")) |>
ggplot() +
geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + scale_color_identity() + add_4flags +
scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 5),
labels = scales::percent_format(accuracy = 1)) +
ylab("Output Gap (% of GDP)") + xlab("")
United States, France, Germany, Switzerland
Code
EO108_INTERNET |>
filter(FREQUENCY == "A",
VARIABLE == "GAP",
LOCATION %in% c("CHE", "FRA", "DEU", "USA")) |>
left_join(EO108_INTERNET_var$LOCATION, by = "LOCATION") |>
year_to_date() |>
select(Location, date, obsValue) |>
arrange(Location, date) |>
mutate(obsValue = obsValue/100) |>
left_join(colors, by = c("Location" = "country")) |>
ggplot() +
geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + scale_color_identity() + add_4flags +
scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 5),
labels = scales::percent_format(accuracy = 1)) +
ylab("Output Gap (% of GDP)") + xlab("")
Unemployment Rate
Germany, Spain, Greece, Italy
All
Code
EO108_INTERNET |>
filter(FREQUENCY == "Q",
VARIABLE == "UNR",
LOCATION %in% c("DEU", "ITA", "FRA", "USA")) |>
left_join(EO108_INTERNET_var$LOCATION, by = "LOCATION") |>
quarter_to_date() |>
select(Location, date, obsValue) |>
arrange(Location, date) |>
mutate(obsValue = obsValue/100) |>
left_join(colors, by = c("Location" = "country")) |>
ggplot() +
geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + scale_color_identity() + add_4flags +
scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
labels = scales::percent_format(accuracy = 1)) +
ylab("Unemployment Rate (%)") + xlab("")
1990-
Code
EO108_INTERNET |>
filter(FREQUENCY == "Q",
VARIABLE == "UNR",
LOCATION %in% c("DEU", "ITA", "FRA", "USA")) |>
left_join(EO108_INTERNET_var$LOCATION, by = "LOCATION") |>
quarter_to_date() |>
filter(date >= as.Date("1990-01-01")) |>
select(Location, date, obsValue) |>
arrange(Location, date) |>
mutate(obsValue = obsValue/100) |>
left_join(colors, by = c("Location" = "country")) |>
ggplot() +
geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + scale_color_identity() + add_4flags +
scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
labels = scales::percent_format(accuracy = 1)) +
ylab("Unemployment Rate (%)") + xlab("")