Unemployment rate by sex and age (%) - UNE_DEAP_SEX_AGE_RT_A

Data - ILO

Author

François Geerolf 

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ref_area

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  filter(sex == "SEX_T",
         classif1 == "AGE_AGGREGATE_YGE15") %>%
  left_join(ref_area, by = "ref_area") %>%
  group_by(ref_area, Ref_area) %>%
  summarise(Nobs = n()) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Ref_area)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

classif1

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  left_join(classif1, by = "classif1") %>%
  group_by(classif1, Classif1) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

source

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  left_join(source, by = "source") %>%
  group_by(source, Source) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

sex

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  left_join(sex, by = "sex") %>%
  group_by(sex, Sex) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

How much data

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  filter(sex == "SEX_T",
         classif1 == "AGE_AGGREGATE_YGE15") %>%
  left_join(ref_area, by = "ref_area") %>%
  mutate(obs_value = round(obs_value, 1)) %>%
  group_by(ref_area, Ref_area) %>%
  arrange(time) %>%
  summarise(Nobs = n(),
            `Year 1` = first(time),
            `Inflation 1` = first(obs_value),
            `Year 2` = last(time),
            `Inflation 2` = last(obs_value)) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Ref_area)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Canada, Japan, United States

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  filter(ref_area %in% c("USA", "JPN", "CAN"),
         sex == "SEX_T",
         classif1 == "AGE_AGGREGATE_YGE15") %>%
  left_join(ref_area, by = "ref_area") %>%
  year_to_enddate() %>%
  mutate(obs_value = obs_value/100) %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  ggplot(.) + geom_line() + theme_minimal() + scale_color_identity() + add_flags +
  aes(x = date, y = obs_value, color = color) + 
  xlab("") + ylab("Unemployment rate") +
  theme(legend.title = element_blank(),
        legend.position = c(0.15, 0.85)) +
  scale_x_date(breaks = seq(1900, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 10000, 2),
                     labels = percent_format(a = 1)) + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "grey")

France, Germany, Spain

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  filter(ref_area %in% c("FRA", "DEU", "ESP"),
         sex == "SEX_T",
         classif1 == "AGE_AGGREGATE_YGE15") %>%
  left_join(ref_area, by = "ref_area") %>%
  year_to_enddate() %>%
  mutate(obs_value = obs_value/100) %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  ggplot(.) + geom_line() + theme_minimal() + scale_color_identity() + add_flags +
  aes(x = date, y = obs_value, color = color) + 
  xlab("") + ylab("Unemployment rate") +
  theme(legend.title = element_blank(),
        legend.position = c(0.15, 0.85)) +
  scale_x_date(breaks = seq(1900, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 10000, 2),
                     labels = percent_format(a = 1)) + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "grey")

Hong Kong, Italy, Korea

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  filter(ref_area %in% c("HKG", "ITA", "KOR"),
         sex == "SEX_T",
         classif1 == "AGE_AGGREGATE_YGE15") %>%
  left_join(ref_area, by = "ref_area") %>%
  year_to_enddate() %>%
  mutate(obs_value = obs_value/100) %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  ggplot(.) + geom_line() + theme_minimal() + scale_color_identity() + add_flags +
  aes(x = date, y = obs_value, color = color) + 
  xlab("") + ylab("Unemployment rate") +
  theme(legend.title = element_blank(),
        legend.position = c(0.15, 0.85)) +
  scale_x_date(breaks = seq(1900, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 10000, 2),
                     labels = percent_format(a = 1)) + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "grey")

Phillips Curves

Hong Kong

All

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  filter(ref_area %in% c("HKG"),
         sex == "SEX_T",
         classif1 == "AGE_AGGREGATE_YGE15") %>%
  mutate(date = paste0(time, "-12-31") %>% as.Date) %>%
  select(date, value = obs_value) %>%
  mutate(variable = "Unemployment Rate") %>%
  bind_rows(NY.GDP.DEFL.KD.ZG %>%
              filter(iso2c %in% c("HK")) %>%
              mutate(date = paste0(year, "-12-31") %>% as.Date) %>%
              select(date, value = value) %>%
              mutate(variable = "Inflation (GDP Deflator)")) %>%
  ggplot(.) + geom_line() + theme_minimal() + 
  aes(x = date, y = value/100, color = variable, linetype = variable) + 
  xlab("") + ylab("Hong Kong's Inflation or Unemployment") +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.85, 0.85)) +
  scale_x_date(breaks = seq(1900, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 10000, 2),
                     labels = percent_format(a = 1)) + 
  geom_vline(xintercept = as.Date("1983-01-01"), linetype = "dashed", color = viridis(4)[3]) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

1976

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  filter(ref_area %in% c("HKG"),
         sex == "SEX_T",
         classif1 == "AGE_AGGREGATE_YGE15") %>%
  mutate(date = paste0(time, "-12-31") %>% as.Date) %>%
  select(date, value = obs_value) %>%
  mutate(variable = "Unemployment Rate") %>%
  bind_rows(NY.GDP.DEFL.KD.ZG %>%
              filter(iso2c %in% c("HK")) %>%
              mutate(date = paste0(year, "-12-31") %>% as.Date) %>%
              select(date, value = value) %>%
              mutate(variable = "Inflation (GDP Deflator)")) %>%
  filter(date >= as.Date("1976-01-01")) %>%
  ggplot(.) + geom_line() + theme_minimal() + 
  aes(x = date, y = value/100, color = variable, linetype = variable) + 
  xlab("") + ylab("Hong Kong's Inflation or Unemployment") +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.85, 0.85)) +
  scale_x_date(breaks = seq(1900, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 10000, 2),
                     labels = percent_format(a = 1)) + 
  geom_vline(xintercept = as.Date("1983-01-01"), linetype = "dashed", color = viridis(4)[3]) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

Benin

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  filter(ref_area %in% c("BEN"),
         sex == "SEX_T",
         classif1 == "AGE_AGGREGATE_YGE15") %>%
  mutate(date = paste0(time, "-12-31") %>% as.Date) %>%
  select(date, value = obs_value) %>%
  mutate(variable = "Unemployment Rate") %>%
  bind_rows(NY.GDP.DEFL.KD.ZG %>%
              filter(iso2c %in% c("BJ")) %>%
              mutate(date = paste0(year, "-12-31") %>% as.Date) %>%
              select(date, value = value) %>%
              mutate(variable = "Inflation (GDP Deflator)")) %>%
  filter(date >= as.Date("1976-01-01")) %>%
  ggplot(.) + geom_line() + theme_minimal() + 
  aes(x = date, y = value/100, color = variable, linetype = variable) + 
  xlab("") + ylab("Hong Kong's Inflation or Unemployment") +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.85, 0.85)) +
  scale_x_date(breaks = seq(1900, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 10000, 2),
                     labels = percent_format(a = 1)) + 
  geom_vline(xintercept = as.Date("1983-01-01"), linetype = "dashed", color = viridis(4)[3]) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "grey")

Togo

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  filter(ref_area %in% c("TGO"),
         sex == "SEX_T",
         classif1 == "AGE_AGGREGATE_YGE15") %>%
  mutate(date = paste0(time, "-12-31") %>% as.Date) %>%
  select(date, value = obs_value) %>%
  mutate(variable = "Unemployment Rate") %>%
  bind_rows(NY.GDP.DEFL.KD.ZG %>%
              filter(iso2c %in% c("TG")) %>%
              mutate(date = paste0(year, "-12-31") %>% as.Date) %>%
              select(date, value = value) %>%
              mutate(variable = "Inflation (GDP Deflator)")) %>%
  filter(date >= as.Date("1976-01-01")) %>%
  ggplot(.) + geom_line() + theme_minimal() + 
  aes(x = date, y = value/100, color = variable, linetype = variable) + 
  xlab("") + ylab("Inflation or Unemployment") +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.85, 0.85)) +
  scale_x_date(breaks = seq(1900, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 10000, 2),
                     labels = percent_format(a = 1)) + 
  geom_vline(xintercept = as.Date("1983-01-01"), linetype = "dashed", color = viridis(4)[3]) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "grey")

Mali

Code 
UNE_DEAP_SEX_AGE_RT_A %>%
  filter(ref_area %in% c("MLI"),
         sex == "SEX_T",
         classif1 == "AGE_AGGREGATE_YGE15") %>%
  mutate(date = paste0(time, "-12-31") %>% as.Date) %>%
  select(date, value = obs_value) %>%
  mutate(variable = "Unemployment Rate") %>%
  bind_rows(NY.GDP.DEFL.KD.ZG %>%
              filter(iso2c %in% c("ML")) %>%
              mutate(date = paste0(year, "-12-31") %>% as.Date) %>%
              select(date, value = value) %>%
              mutate(variable = "Inflation (GDP Deflator)")) %>%
  filter(date >= as.Date("1976-01-01")) %>%
  ggplot(.) + geom_line() + theme_minimal() + 
  aes(x = date, y = value/100, color = variable, linetype = variable) + 
  xlab("") + ylab("Inflation or Unemployment") +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.title = element_blank(),
        legend.position = c(0.85, 0.85)) +
  scale_x_date(breaks = seq(1900, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 10000, 2),
                     labels = percent_format(a = 1)) + 
  geom_vline(xintercept = as.Date("1983-01-01"), linetype = "dashed", color = viridis(4)[3]) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "grey")