Economic Outlook No 110 - December 2021

Data - OECD

~/data/oecd/

Info

LAST_DOWNLOAD

tibble(source = c("oecd", "oecd", "oecd", "oecd", "oecd", "oecd"),
       dataset = c("EO", "EO112_INTERNET", "EO111_INTERNET", "EO110_INTERNET", "EO109_INTERNET", "EO108_INTERNET")) %>%
  mutate(Title = read_lines(paste0("~/Dropbox/website/data/", source, "/",dataset, ".Rmd"), skip = 1, n_max = 1) %>% gsub("title: ", "", .) %>% gsub("\"", "", .)) %>%
  mutate(Download = as.Date(file.info(paste0("~/Dropbox/website/data/", source, "/", dataset, ".RData"))$mtime),
         Compile = as.Date(file.info(paste0("~/Dropbox/website/data/", source, "/", dataset, ".html"))$mtime)) %>%
  mutate(Compile = paste0("[", Compile, "](https://fgeerolf.com/data/", source, "/", dataset, '.html)')) %>%
  print_table_conditional()

source	dataset	Title	Download	Compile
oecd	EO	Economic Outlook	2024-04-15	2024-04-16
oecd	EO112_INTERNET	Economic Outlook No 112 - November 2022	2023-03-18	2024-04-15
oecd	EO111_INTERNET	Economic Outlook No 111 - June 2022	2023-03-18	2024-04-15
oecd	EO110_INTERNET	Economic Outlook No 110 - December 2021	2023-03-18	2024-04-15
oecd	EO109_INTERNET	Economic Outlook No 109 - May 2021	2023-03-18	2024-04-16
oecd	EO108_INTERNET	Economic Outlook No 108 - December 2020	2020-12-05	2024-04-16

LAST_COMPILE

LAST_COMPILE
2024-04-16

Last

obsTime	Nobs
2023-Q4	3841

VARIABLE

EO110_INTERNET %>%
  left_join(EO110_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

EO110_INTERNET %>%
  left_join(EO110_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	750598
A	Annual	376945

Output Gap (% of GDP)

Germany, Spain, Greece, Italy

EO110_INTERNET %>%
  filter(FREQUENCY == "A",
         VARIABLE == "GAP",
         LOCATION %in% c("DEU", "ESP", "GRC", "ITA")) %>%
  left_join(EO110_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, 2025, 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

EO110_INTERNET %>%
  filter(FREQUENCY == "A",
         VARIABLE == "GAP",
         LOCATION %in% c("CHE", "FRA", "DEU", "USA")) %>%
  left_join(EO110_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, 2025, 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

EO110_INTERNET %>%
  filter(FREQUENCY == "Q",
         VARIABLE == "UNR",
         LOCATION %in% c("DEU", "ITA", "FRA", "USA")) %>%
  left_join(EO110_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, 2025, 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-

EO110_INTERNET %>%
  filter(FREQUENCY == "Q",
         VARIABLE == "UNR",
         LOCATION %in% c("DEU", "ITA", "FRA", "USA")) %>%
  left_join(EO110_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, 2025, 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("")