Gross domestic product (GDP) at market prices - annual data - tipsau10

Data - Eurostat

Author

François Geerolf

Info

DOWNLOAD_TIME

Code 
tibble(DOWNLOAD_TIME = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/tipsau10.RData")$mtime)) %>%
  print_table_conditional()
DOWNLOAD_TIME
2024-10-08

Last

Code 
tipsau10 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2023 87

geo

All

Code 
tipsau10 %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         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 .}

eurozone

Code 
geo <- geo %>%
  mutate(eurozone = ifelse(Geo %in% c("Austria", "Belgium", "Cyprus", "Estonia", "Finland", "France", 
                                      "Germany", "Greece", "Ireland", "Italy", "Latvia", "Lithuania", 
                                      "Luxembourg", "Malta", "Netherlands", "Portugal", "Slovakia",
                                      "Slovenia", "Spain"), T, F),
         non_eurozone = ifelse(Geo %in% c("Bulgaria", "Croatia", "Czechia", "Denmark", 
                                          "Hungary", "Poland", "Romania", "Sweden"), T, F))
tipsau10 %>%
  left_join(geo, by = "geo") %>%
  filter(eurozone) %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         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 .}

unit

Code 
tipsau10 %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
unit Unit Nobs
CP_MNAC Current prices, million units of national currency 841
CLV15_MNAC Chain linked volumes (2015), million units of national currency 836
CLV_PCH_PRE Chain linked volumes, percentage change on previous period 812

time

Code 
tipsau10 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  arrange(desc(time)) %>%
  print_table_conditional()
time Nobs
2023 87
2022 87
2021 87
2020 87
2019 87
2018 87
2017 87
2016 87
2015 87
2014 87
2013 87
2012 87
2011 87
2010 87
2009 87
2008 87
2007 87
2006 87
2005 87
2004 87
2003 87
2002 87
2001 87
2000 86
1999 85
1998 85
1997 85
1996 85
1995 62

France, Germany, Italy, Spain, Netherlands

Code 
tipsau10 %>%
  filter(geo %in% c("DE", "ES", "FR", "IT", "NL"),
         unit == "CLV_PCH_PRE") %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values/100) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 2), "-01-01")),
               labels = date_format("%y")) +
  xlab("") + ylab("GDP growth") +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

France, Germany, Italy, Spain, Portugal

Code 
tipsau10 %>%
  filter(geo %in% c("FR", "DE", "PT", "ES", "IT"),
         unit == "CLV_PCH_PRE") %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values/100) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 2), "-01-01")),
               labels = date_format("%y")) +
  xlab("") + ylab("GDP growth") +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

France, Germany, Portugal

Code 
tipsau10 %>%
  filter(geo %in% c("FR", "DE", "PT"),
         unit == "CLV_PCH_PRE") %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values/100) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
  scale_color_identity() + add_3flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 2), "-01-01")),
               labels = date_format("%y")) +
  xlab("") + ylab("GDP growth") +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Poland, Hungary, Slovenia

Code 
tipsau10 %>%
  filter(geo %in% c("PL", "HU", "SI"),
         unit == "CLV_PCH_PRE") %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values/100) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
  scale_color_identity() + add_3flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 2), "-01-01")),
               labels = date_format("%y")) +
  xlab("") + ylab("GDP growth") +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Mean, Standard Deviation

All

Viridis

Code 
tipsau10 %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  filter(unit == "CLV_PCH_PRE") %>%
  {if (eurozone) filter(., eurozone) else .} %>%
  group_by(date) %>%
  filter(n() == 19) %>%
  summarise(`Moyenne` = mean(values),
            `Ecart Type` = sd(values)) %>%
  transmute(date, `Moyenne`,
            `Moyenne + SD` = `Moyenne` + `Ecart Type`,
            `Moyenne - SD` = `Moyenne` - `Ecart Type`) %>%
  gather(variable, value, -date) %>%
  mutate(value = value/100) %>%
  ggplot + geom_line(aes(x = date, y = value, color = variable, linetype = variable)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_color_manual(values = c(viridis(3)[1], viridis(3)[2], viridis(3)[2])) +
  scale_linetype_manual(values = c("solid", "dashed", "dashed")) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 2), "-01-01")),
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

Colors

Code 
tipsau10 %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  filter(unit == "CLV_PCH_PRE") %>%
  {if (eurozone) filter(., eurozone) else .} %>%
  group_by(date) %>%
  filter(n() == 19) %>%
  summarise(`Moyenne` = mean(values),
            `Ecart Type` = sd(values)) %>%
  transmute(date, `Moyenne`,
            `Moyenne + SD` = `Moyenne` + `Ecart Type`,
            `Moyenne - SD` = `Moyenne` - `Ecart Type`) %>%
  gather(variable, value, -date) %>%
  mutate(value = value/100) %>%
  ggplot + geom_line(aes(x = date, y = value, color = variable, linetype = variable)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_color_manual(values = c("#003399", "#FFCC00", "#FFCC00")) +
  scale_linetype_manual(values = c("solid", "dashed", "dashed")) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2022, 1), "-01-01")),
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

With France

Code 
tipsau10 %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  filter(unit == "CLV_PCH_PRE") %>%
  {if (eurozone) filter(., eurozone) else .} %>%
  group_by(date) %>%
  filter(n() == 19) %>%
  summarise(`Moyenne Europe` = mean(values),
            `Ecart Type` = sd(values),
            `France` = values[geo == "FR"]) %>%
  transmute(date, `Moyenne Europe`,
            `Moyenne Europe + SD` = `Moyenne Europe` + `Ecart Type`,
            `Moyenne Europe - SD` = `Moyenne Europe` - `Ecart Type`,
             `France`) %>%
  gather(variable, value, -date) %>%
  mutate(values = value/100,
         Geo = ifelse(variable == "France", "France", "Europe")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = variable, linetype = variable)) +
  theme_minimal() + xlab("") + ylab("") + add_4flags +
  scale_color_manual(values = c("#ED2939", "#003399", "#FFCC00", "#FFCC00")) +
  scale_linetype_manual(values = c("solid", "solid", "dashed", "dashed")) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 1), "-01-01")),
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.75, 0.2),
        legend.title = element_blank())

With Germany

Code 
tipsau10 %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  filter(unit == "CLV_PCH_PRE") %>%
  {if (eurozone) filter(., eurozone) else .} %>%
  group_by(date) %>%
  filter(n() == 19) %>%
  summarise(`Moyenne Europe` = mean(values),
            `Ecart Type` = sd(values),
            `France` = values[geo == "FR"],
            `Allemagne` = values[geo == "DE"]) %>%
  transmute(date, `Moyenne Europe`,
            `Moyenne Europe + SD` = `Moyenne Europe` + `Ecart Type`,
            `Moyenne Europe - SD` = `Moyenne Europe` - `Ecart Type`,
             `France`,
             `Allemagne`) %>%
  gather(variable, value, -date) %>%
  mutate(values = value/100,
         Geo = ifelse(variable == "France", "France", "Europe"),
         Geo = ifelse(variable == "Allemagne", "Germany", Geo)) %>%
  ggplot + geom_line(aes(x = date, y = values, color = variable, linetype = variable)) +
  theme_minimal() + xlab("") + ylab("") + add_5flags +
  scale_color_manual(values = c("#000000", "#ED2939", "#003399", "#FFCC00", "#FFCC00")) +
  scale_linetype_manual(values = c("solid", "solid", "solid", "dashed", "dashed")) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 1), "-01-01")),
               labels = date_format("%y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.75, 0.2),
        legend.title = element_blank()) +
  geom_hline(yintercept = 0.06, linetype = "dotted") +
  geom_hline(yintercept = -0.04, linetype = "dotted")