Unemployment Rate - UNR

Data - GFD

Author

François Geerolf

Variables

Wide

Code 
unr_info %>%
  select(Ticker, Country) %>%
  right_join(unr %>%
               group_by(Ticker, iso3c) %>%
               summarise(Nobs = n(),
                         start = first(year(date)),
                         end = last(year(date))), by = "Ticker") %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Country)),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Ticker, Name

Code 
unr_info %>%
  select(Ticker, Name) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Metadata

Code 
unr_info %>% 
  select(Ticker, Name, Metadata) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Individual Countries

How much data ?

Code 
unr_info %>%
  select(Ticker, Country) %>%
  right_join(unr %>%
               group_by(Ticker, iso3c) %>%
               summarise(Nobs = n(),
                         start = first(year(date)),
                         end = last(year(date))), by = "Ticker") %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Country)),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Argentina

All

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "ARG") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 5), "-01-01")),
               labels = date_format("%y"))

1985

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "ARG",
         date >= as.Date("1985-01-01")) %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 5), "-01-01")),
               labels = date_format("%y"))

1990

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "ARG",
         date >= as.Date("1990-01-01")) %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 5), "-01-01")),
               labels = date_format("%y"))

Great Britain

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "GBR") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

Belgium

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "BEL") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

Brazil

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "BRA") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

Sweden

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "SWE") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

Canada

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "CAN") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

Netherlands

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "NLD") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

Germany

All

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "DEU") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

1920-

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "DEU",
         date >= as.Date("1920-01-01")) %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

1940-

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "DEU",
         date >= as.Date("1940-01-01")) %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 10), "-01-01")),
               labels = date_format("%y"))

United States

1890-2019

(ref:us-unr-1890-2019) U.S. Unemployment (1890-2019)

Code 
unr %>%
  filter(Ticker == "UNUSAM") %>%
  ggplot(.) +
  geom_line(aes(x = date, y = value / 100)) + 
  ylab("Unemployment Rate") + xlab("") +
  geom_rect(data = nber_recessions, 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) + 
  scale_y_continuous(breaks =  0.01*seq(0, 26, 2),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1890, 2019, 10), "-01-01")),
               labels = date_format("%y"),
               limits = c(as.Date("1890-04-01"), as.Date("2019-06-01"))) + 
  theme_minimal() + 
  geom_vline(xintercept = as.Date("1929-10-29"), linetype = "dashed", color = "red")

(ref:us-unr-1890-2019)

Denmark

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "DNK") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

Norway

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "NOR") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

Switzerland

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "CHE") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

Japan

1880-2019

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "JPN") %>%
  ggplot(.) + theme_minimal() + ylab("Unemployment Rate") + xlab("") +
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1895, 2019, 10), "-01-01")),
               labels = date_format("%y"),
               limits = c(as.Date("1895-04-01"), as.Date("2019-06-01"))) + 
  geom_vline(xintercept = as.Date("1929-10-29"), linetype = "dashed", color = "red")

1985-2019

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "JPN") %>%
  filter(date >= as.Date("1985-01-01")) %>%
  ggplot(.) + theme_minimal() + ylab("Unemployment Rate") + xlab("") +
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1900, 2019, 5), "-01-01")),
               labels = date_format("%y")) + 
  geom_vline(xintercept = as.Date("1929-10-29"), linetype = "dashed", color = "red")

Austria

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "AUT") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

Australia

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "AUS") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

France

1895 - 2019

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "FRA") %>%
  ggplot(.) +
  geom_line(aes(x = date, y = value / 100)) + 
  ylab("Unemployment Rate") + xlab("") +
  scale_y_continuous(breaks =  0.01*seq(0, 26, 2),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1895, 2019, 10), "-01-01")),
               labels = date_format("%y")) + 
  theme_minimal() + 
  geom_vline(xintercept = as.Date("1929-10-29"), linetype = "dashed", color = "red")

1960 - 2019

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "FRA",
         date >= as.Date("1960-01-01")) %>%
  ggplot(.) +
  geom_line(aes(x = date, y = value / 100)) + 
  ylab("Unemployment Rate") + xlab("") +
  scale_y_continuous(breaks =  0.01*seq(0, 26, 2),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1895, 2019, 10), "-01-01")),
               labels = date_format("%y")) + 
  theme_minimal() + 
  geom_vline(xintercept = as.Date("1929-10-29"), linetype = "dashed", color = "red")

Italy

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "ITA") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

Finland

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "FIN") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 20), "-01-01")),
               labels = date_format("%Y"))

Spain

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "ESP") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 5), "-01-01")),
               labels = date_format("%y"))

South Korea

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "KOR") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 5), "-01-01")),
               labels = date_format("%y"))

Iceland

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "ISL") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 5), "-01-01")),
               labels = date_format("%y"))

Portugal

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "PRT") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 80, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2022, 5), "-01-01")),
               labels = date_format("%y"))

Thailand

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "THA") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1890, 2022, 2), "-01-01")),
               labels = date_format("%y"))

Malaysia

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "MYS") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1890, 2022, 2), "-01-01")),
               labels = date_format("%y"))

Hong Kong

Code 
unr %>%
  filter(variable == "UNM",
         iso3c == "HKG") %>%
  ggplot(.) + ylab("Unemployment Rate") + xlab("") + theme_minimal() + 
  geom_line(aes(x = date, y = value / 100)) +
  scale_y_continuous(breaks =  0.01*seq(0, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  scale_x_date(breaks = as.Date(paste0(seq(1890, 2022, 2), "-01-01")),
               labels = date_format("%y"))

3 countries

FRA, DEU, GBR

Code 
unr %>%
  filter(iso3c %in% c("FRA", "DEU", "GBR"),
         date >= as.Date("1925-01-01"),
         date <= as.Date("1970-01-01")) %>%
  group_by(iso3c) %>%
  complete(date = seq.Date(min(date), max(date), by = "month")) %>%
  left_join(iso3c, by = "iso3c") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = value / 100, color = Iso3c, linetype = Iso3c)) + 
  theme_minimal() + xlab("") + ylab("Unemployment Rate (%)") +
  scale_x_date(breaks = seq(1925, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.8, 0.80),
        legend.title = element_blank())

FRA, GBR (1896-1939)

Code 
unr %>%
  filter(iso3c %in% c("FRA", "GBR"),
         date <= as.Date("1939-01-01"),
         date >= as.Date("1896-01-01")) %>%
  left_join(iso3c, by = "iso3c") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = value / 100, color = Iso3c, linetype = Iso3c)) + 
  theme_minimal() + xlab("") + ylab("Unemployment Rate (%)") +
  scale_x_date(breaks = seq(1890, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-90, 90, 2),
                     labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.2, 0.80),
        legend.title = element_blank())

DEU, GBR, SWE (1896-1939)

Code 
unr %>%
  filter(iso3c %in% c("DEU", "GBR", "SWE"),
         date >= as.Date("1895-01-01"),
         date <= as.Date("1945-01-01")) %>%
  group_by(iso3c) %>%
  complete(date = seq.Date(min(date), max(date), by = "year")) %>%
  left_join(iso3c, by = "iso3c") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = value / 100, color = Iso3c, linetype = Iso3c)) + 
  theme_minimal() + xlab("") + ylab("Unemployment Rate (%)") +
  scale_x_date(breaks = seq(1890, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-90, 90, 2),
                     labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.2, 0.80),
        legend.title = element_blank())

USA, DNK, NOR (1896-1939)

Code 
unr %>%
  filter(iso3c %in% c("USA", "DNK", "NOR"),
         date >= as.Date("1895-01-01"),
         date <= as.Date("1945-01-01")) %>%
  group_by(iso3c) %>%
  complete(date = seq.Date(min(date), max(date), by = "year")) %>%
  left_join(iso3c, by = "iso3c") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = value / 100, color = Iso3c, linetype = Iso3c)) + 
  theme_minimal() + xlab("") + ylab("Unemployment Rate (%)") +
  scale_x_date(breaks = seq(1890, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-90, 90, 2),
                     labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.2, 0.80),
        legend.title = element_blank())

CHE, JPN, AUS (1900-1945)

Code 
unr %>%
  filter(iso3c %in% c("CHE", "JPN", "AUS"),
         date >= as.Date("1900-01-01"),
         date <= as.Date("1945-01-01")) %>%
  group_by(iso3c) %>%
  complete(date = seq.Date(min(date), max(date), by = "year")) %>%
  left_join(iso3c, by = "iso3c") %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = value / 100, color = Iso3c, linetype = Iso3c)) + 
  theme_minimal() + xlab("") + ylab("Unemployment Rate (%)") +
  scale_x_date(breaks = seq(1890, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-90, 90, 2),
                     labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.2, 0.80),
        legend.title = element_blank())