Direction of Trade Statistics - France - DOT_FR

Data - IMF

Author

François Geerolf

Info

DOWNLOAD_TIME

Code 
tibble(DOWNLOAD_TIME = as.Date(file.info("~/iCloud/website/data/imf/DOT_FR.RData")$mtime)) |>
  print_table_conditional()
DOWNLOAD_TIME
NA

Last

Code 
DOT_FR |>
  group_by(TIME_PERIOD) |>
  summarise(Nobs = n()) |>
  arrange(desc(TIME_PERIOD)) |>
  head(1) |>
  print_table_conditional()
TIME_PERIOD Nobs
2024-Q3 672

FREQ

Code 
DOT_FR |>
  left_join(FREQ, by = "FREQ") |>
  group_by(FREQ, Freq) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
FREQ Freq Nobs
M Monthly 435855
Q Quarterly 149819
A Annual 41559

INDICATOR

Code 
DOT_FR |>
  left_join(INDICATOR, by = "INDICATOR") |>
  group_by(INDICATOR, Indicator) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
INDICATOR Indicator Nobs
TBG_USD Goods, Value of Trade Balance, US Dollars 214698
TXG_FOB_USD Goods, Value of Exports, Free on board (FOB), US Dollars 211392
TMG_CIF_USD Goods, Value of Imports, Cost, Insurance, Freight (CIF), US Dollars 201143

COUNTERPART_AREA

Code 
DOT_FR |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  group_by(COUNTERPART_AREA, Counterpart_area) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Counterpart_area))),
         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 .}

France - Germany Surplus

Annual

Code 
DOT_FR |>
  filter(COUNTERPART_AREA == "DE",
         FREQ == "A") |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)) |>
  left_join(INDICATOR, by = "INDICATOR") |>
  select(TIME_PERIOD, Indicator, OBS_VALUE) |>
  spread(Indicator, OBS_VALUE) |>
  arrange(desc(TIME_PERIOD)) |>
  print_table_conditional()

Quarterly

Code 
DOT_FR |>
  filter(COUNTERPART_AREA == "DE",
         FREQ == "Q") |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)) |>
  left_join(INDICATOR, by = "INDICATOR") |>
  select(TIME_PERIOD, Indicator, OBS_VALUE) |>
  spread(Indicator, OBS_VALUE) |>
  arrange(desc(TIME_PERIOD)) |>
  print_table_conditional()

Table - 2019, 2013, 2010, 2007, 2004

All

Code 
DOT_FR |>
  left_join(NGDP_USD |>
              select(FREQ, REF_AREA, TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = c("TIME_PERIOD", "REF_AREA", "FREQ")) |>
  filter(TIME_PERIOD %in% c("2019", "2010", "2000", "1990"),
         INDICATOR == "TBG_USD") |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  select(COUNTERPART_AREA, Counterpart_area, TIME_PERIOD, OBS_VALUE) |>
  spread(TIME_PERIOD, OBS_VALUE) |>
  arrange(-`2019`) %>%
  mutate_at(vars(-1, -2), funs(round(100*., 2))) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Counterpart_area))),
         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 .}

Large Surpluses

Code 
DOT_FR |>
  left_join(NGDP_USD |>
              select(FREQ, REF_AREA, TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = c("TIME_PERIOD", "REF_AREA", "FREQ")) |>
  filter(TIME_PERIOD %in% c("2019", "2010", "2000", "1990"),
         INDICATOR == "TBG_USD") |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  select(COUNTERPART_AREA, Counterpart_area, TIME_PERIOD, OBS_VALUE) |>
  spread(TIME_PERIOD, OBS_VALUE) |>
  arrange(-`2019`) %>%
  mutate_at(vars(-1, -2), funs(round(100*., 2))) |>
  filter(!is.na(`2019`),
         `2019` > 0.04) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Counterpart_area))),
         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 .}

Large Deficits

Code 
DOT_FR |>
  left_join(NGDP_USD |>
              select(FREQ, REF_AREA, TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = c("TIME_PERIOD", "REF_AREA", "FREQ")) |>
  filter(TIME_PERIOD %in% c("2019", "2010", "2000", "1990"),
         INDICATOR == "TBG_USD") |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  select(COUNTERPART_AREA, Counterpart_area, TIME_PERIOD, OBS_VALUE) |>
  spread(TIME_PERIOD, OBS_VALUE) |>
  arrange(`2019`) %>%
  mutate_at(vars(-1, -2), funs(round(100*., 2))) |>
  filter(!is.na(`2019`),
         `2019` < -0.11) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Counterpart_area))),
         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 .}

Large Surpluses in 2020

US, UK, Singapore

Code 
DOT_FR |>
  filter(COUNTERPART_AREA  %in% c("GB", "US", "SG"),
         INDICATOR %in% c("TBG_USD"),
         FREQ == "A") |>
  inner_join(NGDP_USD |>
              filter(REF_AREA == "FR",
                     FREQ == "A") |>
              mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)) |>
              select(TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = "TIME_PERIOD") |>
  year_to_date2() |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  mutate(Counterpart_area = ifelse(COUNTERPART_AREA == "U2", "Europe", Counterpart_area),
         Counterpart_area = ifelse(COUNTERPART_AREA == "W00", "World", Counterpart_area)) |>
  left_join(colors, by = c("Counterpart_area" = "country")) |>
  mutate(color = ifelse(COUNTERPART_AREA == "DE", color2, color)) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme(legend.position = "none") + add_flags +
  scale_x_date(breaks = seq(1950, 2100, 10) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 500, .1),
                     labels = percent_format(accuracy = .1)) + 
  xlab("") + ylab("France Bilateral Trade Surplus (% of GDP)") + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

Qatar, Hong Kong, Egypt

Code 
DOT_FR |>
  filter(COUNTERPART_AREA  %in% c("QA", "HK", "EG"),
         INDICATOR %in% c("TBG_USD"),
         FREQ == "A") |>
  inner_join(NGDP_USD |>
              filter(REF_AREA == "FR",
                     FREQ == "A") |>
              mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)) |>
              select(TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = "TIME_PERIOD") |>
  year_to_date2() |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  mutate(Counterpart_area = ifelse(COUNTERPART_AREA == "HK", "Hong Kong", Counterpart_area),
         Counterpart_area = ifelse(COUNTERPART_AREA == "W00", "World", Counterpart_area)) |>
  left_join(colors, by = c("Counterpart_area" = "country")) |>
  mutate(color = ifelse(COUNTERPART_AREA == "DE", color2, color)) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme(legend.position = "none") + add_flags +
  scale_x_date(breaks = seq(1950, 2100, 10) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 500, .1),
                     labels = percent_format(accuracy = .1)) + 
  xlab("") + ylab("France Bilateral Trade Surplus (% of GDP)") + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

Large Deficits in 2020

Germany, Nertherlands, Belgium

Code 
DOT_FR |>
  filter(COUNTERPART_AREA  %in% c("DE", "NL", "BE"),
         INDICATOR %in% c("TBG_USD"),
         FREQ == "A") |>
  inner_join(NGDP_USD |>
              filter(REF_AREA == "FR",
                     FREQ == "A") |>
              mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)) |>
              select(TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = "TIME_PERIOD") |>
  year_to_date2() |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  mutate(Counterpart_area = ifelse(COUNTERPART_AREA == "U2", "Europe", Counterpart_area),
         Counterpart_area = ifelse(COUNTERPART_AREA == "W00", "World", Counterpart_area)) |>
  left_join(colors, by = c("Counterpart_area" = "country")) |>
  mutate(color = ifelse(COUNTERPART_AREA == "DE", color2, color)) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme(legend.position = "none") + add_flags +
  scale_x_date(breaks = seq(1950, 2100, 10) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 500, .1),
                     labels = percent_format(accuracy = .1)) + 
  xlab("") + ylab("France Bilateral Trade Surplus (% of GDP)") + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

Germany, Nertherlands, Belgium, World

All

Code 
DOT_FR |>
  filter(COUNTERPART_AREA  %in% c("DE", "NL", "BE", "W00"),
         INDICATOR %in% c("TBG_USD"),
         FREQ == "A") |>
  inner_join(NGDP_USD |>
              filter(REF_AREA == "FR",
                     FREQ == "A") |>
              mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)) |>
              select(TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = "TIME_PERIOD") |>
  year_to_date2() |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  mutate(Counterpart_area = ifelse(COUNTERPART_AREA == "U2", "Europe", Counterpart_area),
         Counterpart_area = ifelse(COUNTERPART_AREA == "W00", "World", Counterpart_area)) |>
  left_join(colors, by = c("Counterpart_area" = "country")) |>
  mutate(color = ifelse(COUNTERPART_AREA == "DE", color2, color)) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme(legend.position = "none") + add_flags +
  scale_x_date(breaks = seq(1950, 2100, 10) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 500, .5),
                     labels = percent_format(accuracy = .1)) + 
  xlab("") + ylab("France Bilateral Trade Surplus (% of GDP)") + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

1990-

Code 
DOT_FR |>
  filter(COUNTERPART_AREA  %in% c("DE", "NL", "BE", "W00"),
         INDICATOR %in% c("TBG_USD"),
         FREQ == "A") |>
  inner_join(NGDP_USD |>
              filter(REF_AREA == "FR",
                     FREQ == "A") |>
              mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)) |>
              select(TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = "TIME_PERIOD") |>
  year_to_date2() |>
  filter(date >= as.Date("1990-01-01")) |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  mutate(Counterpart_area = ifelse(COUNTERPART_AREA == "U2", "Europe", Counterpart_area),
         Counterpart_area = ifelse(COUNTERPART_AREA == "W00", "World", Counterpart_area)) |>
  left_join(colors, by = c("Counterpart_area" = "country")) |>
  mutate(color = ifelse(COUNTERPART_AREA == "DE", color2, color)) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme(legend.position = "none") + add_flags +
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 500, .5),
                     labels = percent_format(accuracy = .1)) + 
  xlab("") + ylab("France Bilateral Trade Surplus (% of GDP)") + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

China, Italy, Spain

Code 
DOT_FR |>
  filter(COUNTERPART_AREA  %in% c("CN", "IT", "ES"),
         INDICATOR %in% c("TBG_USD"),
         FREQ == "A") |>
  inner_join(NGDP_USD |>
              filter(REF_AREA == "FR",
                     FREQ == "A") |>
              mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)) |>
              select(TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = "TIME_PERIOD") |>
  year_to_date2() |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  mutate(Counterpart_area = ifelse(COUNTERPART_AREA == "U2", "Europe", Counterpart_area),
         Counterpart_area = ifelse(COUNTERPART_AREA == "W00", "World", Counterpart_area)) |>
  left_join(colors, by = c("Counterpart_area" = "country")) |>
  mutate(color = ifelse(COUNTERPART_AREA == "ES", color2, color)) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme(legend.position = "none") + add_flags +
  scale_x_date(breaks = seq(1950, 2100, 10) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 500, .1),
                     labels = percent_format(accuracy = .1)) + 
  xlab("") + ylab("France Bilateral Trade Surplus (% of GDP)") + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

China, Germany, Europe

All

Code 
DOT_FR |>
  filter(COUNTERPART_AREA  %in% c("CN", "DE", "U2"),
         INDICATOR %in% c("TBG_USD"),
         FREQ == "A") |>
  inner_join(NGDP_USD |>
              filter(REF_AREA == "FR",
                     FREQ == "A") |>
              mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)) |>
              select(TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = "TIME_PERIOD") |>
  year_to_date2() |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  mutate(Counterpart_area = ifelse(COUNTERPART_AREA == "U2", "Europe", Counterpart_area),
         Counterpart_area = ifelse(COUNTERPART_AREA == "W00", "World", Counterpart_area)) |>
  left_join(colors, by = c("Counterpart_area" = "country")) |>
  mutate(color = ifelse(COUNTERPART_AREA == "DE", color2, color)) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme(legend.position = "none") + add_flags +
  scale_x_date(breaks = seq(1950, 2100, 10) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 500, 1),
                     labels = percent_format(accuracy = .1)) + 
  xlab("") + ylab("France Bilateral Trade Surplus (% of GDP)") + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

1980-

Code 
DOT_FR |>
  filter(COUNTERPART_AREA  %in% c("CN", "DE", "U2"),
         INDICATOR %in% c("TBG_USD"),
         FREQ == "A") |>
  inner_join(NGDP_USD |>
              filter(REF_AREA == "FR",
                     FREQ == "A") |>
              mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)) |>
              select(TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = "TIME_PERIOD") |>
  year_to_date2() |>
  filter(date >= as.Date("1980-01-01")) |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  mutate(Counterpart_area = ifelse(COUNTERPART_AREA == "U2", "Europe", Counterpart_area),
         Counterpart_area = ifelse(COUNTERPART_AREA == "W00", "World", Counterpart_area)) |>
  left_join(colors, by = c("Counterpart_area" = "country")) |>
  mutate(color = ifelse(COUNTERPART_AREA == "DE", color2, color)) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme(legend.position = "none") + add_flags +
  scale_x_date(breaks = seq(1950, 2100, 10) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 500, 1),
                     labels = percent_format(accuracy = .1)) + 
  xlab("") + ylab("France Bilateral Trade Surplus (% of GDP)") + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

1990-

Code 
DOT_FR |>
  filter(COUNTERPART_AREA  %in% c("CN", "DE", "U2"),
         INDICATOR %in% c("TBG_USD"),
         FREQ == "A") |>
  inner_join(NGDP_USD |>
              filter(REF_AREA == "FR",
                     FREQ == "A") |>
              mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)) |>
              select(TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = "TIME_PERIOD") |>
  year_to_date2() |>
  filter(date >= as.Date("1990-01-01")) |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  mutate(Counterpart_area = ifelse(COUNTERPART_AREA == "U2", "Europe", Counterpart_area),
         Counterpart_area = ifelse(COUNTERPART_AREA == "W00", "World", Counterpart_area)) |>
  left_join(colors, by = c("Counterpart_area" = "country")) |>
  mutate(color = ifelse(COUNTERPART_AREA == "DE", color2, color)) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme(legend.position = "none") + add_flags +
  scale_x_date(breaks = seq(1950, 2100, 10) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 500, 1),
                     labels = percent_format(accuracy = .1)) + 
  xlab("") + ylab("France Bilateral Trade Surplus (% of GDP)") + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

China, Germany, Europe, Russia

All

Code 
DOT_FR |>
  filter(COUNTERPART_AREA  %in% c("CN", "DE", "U2", "RU"),
         INDICATOR %in% c("TBG_USD"),
         FREQ == "A") |>
  inner_join(NGDP_USD |>
              filter(REF_AREA == "FR",
                     FREQ == "A") |>
              mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)) |>
              select(TIME_PERIOD, NGDP_USD = OBS_VALUE),
            by = "TIME_PERIOD") |>
  year_to_date2() |>
  mutate(OBS_VALUE = OBS_VALUE*10^(UNIT_MULT)/NGDP_USD) |>
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") |>
  mutate(Counterpart_area = ifelse(COUNTERPART_AREA == "U2", "Europe", Counterpart_area),
         Counterpart_area = ifelse(COUNTERPART_AREA == "W00", "World", Counterpart_area),
         Counterpart_area = ifelse(COUNTERPART_AREA == "RU", "Russia", Counterpart_area)) |>
  left_join(colors, by = c("Counterpart_area" = "country")) |>
  mutate(color = ifelse(COUNTERPART_AREA == "DE", color2, color)) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme(legend.position = "none") + add_flags +
  scale_x_date(breaks = seq(1950, 2100, 10) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 500, 1),
                     labels = percent_format(accuracy = .1)) + 
  xlab("") + ylab("France Bilateral Trade Surplus (% of GDP)") + 
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")