GDP, PPP (constant 2017 international $) - NY.GDP.MKTP.PP.KD

Name: GDP, PPP (constant 2017 international $)
Creator: François Geerolf
License: https://creativecommons.org/licenses/by/4.0/

Data - WDI

Author

François Geerolf

Last observation: 2025 (N = 232)

First observation: 1990 (N = 232)

Last data update: 04 sept. 2026, 00:27

Last compile: 04 sept. 2026, 00:38

Nobs - Javascript

Code

NY.GDP.MKTP.PP.KD |>
  left_join(iso2c, by = "iso2c") |>
  group_by(iso2c, Iso2c) |>
  
  mutate(value = round(value/(10^9))) %>%
  summarise(Nobs = n(),
            `Year 1` = first(year),
            `GDP 1 (Bn)` = first(value) %>% paste0("$ ", .),
            `Year 2` = last(year),
            `GDP 2 (Bn)` = last(value) %>% paste0("$ ", .)) |>
  arrange(-Nobs) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(Iso2c)),
         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 .}

2018 GDP by Country

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c |>
              filter((region != "Aggregates") & (region != "NA")), 
             by = "iso2c") |>
  group_by(iso2c, Iso2c) |>
  
  mutate(value = round(value/(10^9))) |>
  summarise(`GDP (Bn)` = last(value)) |>
  arrange(-`GDP (Bn)`) %>%
  mutate(`GDP (Bn)` = `GDP (Bn)` %>% paste0("$ ", ., " Bn")) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(Iso2c)),
         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 .}

2018 GDP by Country and Aggregates

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c, by = "iso2c") |>
  group_by(iso2c, Iso2c) |>
  
  mutate(value = round(value/(10^9))) |>
  summarise(`GDP (Bn)` = last(value)) |>
  arrange(-`GDP (Bn)`) %>%
  mutate(`GDP (Bn)` = `GDP (Bn)` %>% paste0("$ ", ., " Bn")) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Euro Area vs. US

Base 100

Code

NY.GDP.MKTP.PP.KD |>
  left_join(iso2c, by = "iso2c") |>
  year_to_date() |>
  filter(iso2c %in% c("XC", "US"),
         date >= as.Date("2008-01-01")) |>
  group_by(iso2c) |>
  arrange(date) |>
  mutate(value = 100*value/value[1]) |>
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  add_flags +
  scale_x_date(breaks = seq(1950, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(70, 300, 5)) + 
  xlab("") + ylab("PIB en $ (100 = 2008)")

Avec dollars

Code

NY.GDP.MKTP.PP.KD |>
  left_join(iso2c, by = "iso2c") |>
  year_to_date() |>
  filter(iso2c %in% c("XC", "US"),
         date >= as.Date("2008-01-01")) |>
  group_by(iso2c) |>
  arrange(date) |>
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ungroup() |>
  mutate(dollar = value/10^9,
         value = 100*value/value[2]) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  add_flags +
  scale_x_date(breaks = seq(1950, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10, 300, 5)) + 
  xlab("") + ylab("PIB en $ (100 = Zone Euro, 2008)") + 
  geom_text_repel(data = . %>% filter(year(date) %in% seq(2008, 2022, 2)),
                                      aes(x = date, y = value, label = paste0("$", round(dollar, digits = -2), " Md")))

China, E.U., U.S.

Linear

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c, by = "iso2c") |>
  filter(iso2c %in% c("1W", "US", "CN", "EU")) |>
  group_by(year) |>
  mutate(value = value/value[iso2c == "1W"]) |>
  year_to_date() |>
  filter(!(iso2c == "1W")) |>
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  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(0, 70, 2),
                     labels = scales::percent_format(accuracy = 1),
                     limits = c(0, 0.23)) + 
  xlab("") + ylab("% du PIB mondial en Parité de Pouvoir d'Achat")

Log

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c, by = "iso2c") |>
  filter(iso2c %in% c("1W", "US", "CN", "EU")) |>
  group_by(year) |>
  mutate(value = value/value[iso2c == "1W"]) |>
  year_to_date() |>
  filter(!(iso2c == "1W")) |>
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  add_flags +
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = 0.01*seq(0, 70, 5),
                     labels = scales::percent_format(accuracy = 1)) + 
  xlab("") + ylab("% du PIB mondial en Parité de Pouvoir d'Achat")

Italy, France, Allemagne, Espagne

Linear

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c, by = "iso2c") |>
  filter(iso2c %in% c("1W", "IT", "FR", "DE", "ES")) |>
  group_by(year) |>
  mutate(value = value/value[iso2c == "1W"]) |>
  year_to_date() |>
  filter(!(iso2c == "1W")) |>
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  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(0, 70, .5),
                     labels = scales::percent_format(accuracy = .1)) + 
  xlab("") + ylab("% du PIB mondial en Parité de Pouvoir d'Achat")

Log

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c, by = "iso2c") |>
  filter(iso2c %in% c("1W", "IT", "FR", "DE", "ES")) |>
  group_by(year) |>
  mutate(value = value/value[iso2c == "1W"]) |>
  year_to_date() |>
  filter(!(iso2c == "1W")) |>
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  add_flags +
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = 0.01*seq(0, 70, .5),
                     labels = scales::percent_format(accuracy = .1)) + 
  xlab("") + ylab("% du PIB mondial en Parité de Pouvoir d'Achat")

South Korea, Russia, Indonesia

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c, by = "iso2c") |>
  filter(iso2c %in% c("1W", "ID", "KR", "RU")) |>
  group_by(year) |>
  mutate(value = value/value[iso2c == "1W"]) |>
  year_to_date() |>
  filter(!(iso2c == "1W")) |>
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) |>
  mutate(Iso2c = ifelse(iso2c == "KR", "Korea", Iso2c)) |>
  mutate(Iso2c = ifelse(iso2c == "RU", "Russia", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  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(0, 70, 0.5),
                     labels = scales::percent_format(accuracy = .1)) + 
  xlab("") + ylab("% du World GDP")

Japan, India, United Kingdom

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c, by = "iso2c") |>
  filter(iso2c %in% c("1W", "IN", "JP", "GB")) |>
  group_by(year) |>
  mutate(value = value/value[iso2c == "1W"]) |>
  year_to_date() |>
  filter(!(iso2c == "1W")) |>
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  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(0, 70, 2),
                     labels = scales::percent_format(accuracy = 1),
                     limits = 0.01*c(0, 10)) + 
  xlab("") + ylab("% of World GDP")

Germany, France, Italy

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c, by = "iso2c") |>
  filter(iso2c %in% c("1W", "DE", "FR", "IT")) |>
  group_by(year) |>
  mutate(value = value/value[iso2c == "1W"]) |>
  year_to_date() |>
  filter(!(iso2c == "1W")) |>
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  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(0, 70, 2),
                     labels = scales::percent_format(accuracy = 1),
                     limits = 0.01*c(0, 6)) + 
  xlab("") + ylab("% of World GDP")

Eurozone, European Union, United States

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c, by = "iso2c") |>
  filter(iso2c %in% c("1W", "XC", "US", "EU")) |>
  group_by(year) |>
  mutate(value = value/value[iso2c == "1W"]) |>
  year_to_date() |>
  filter(!(iso2c == "1W")) |>
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  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(0, 70, 5),
                     labels = scales::percent_format(accuracy = 1),
                     limits = 0.01*c(0, 25)) + 
  xlab("") + ylab("% of World GDP")

Germany, Japan, United Kingdom

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c, by = "iso2c") |>
  filter(iso2c %in% c("1W", "JP", "DE", "GB")) |>
  group_by(year) |>
  mutate(value = value/value[iso2c == "1W"]) |>
  year_to_date() |>
  filter(!(iso2c == "1W")) |>
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  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(0, 70, 2),
                     labels = scales::percent_format(accuracy = 1),
                     limits = 0.01*c(0, 10)) + 
  xlab("") + ylab("% of World GDP")

United Kingdom, France, Italy

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c, by = "iso2c") |>
  filter(iso2c %in% c("1W", "GB", "FR", "IT")) |>
  group_by(year) |>
  mutate(value = value/value[iso2c == "1W"]) |>
  year_to_date() |>
  filter(!(iso2c == "1W")) |>
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  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(0, 70, 0.5),
                     labels = scales::percent_format(accuracy = .1)) + 
  xlab("") + ylab("% of World GDP")

Brazil, Russia, India

Code

NY.GDP.MKTP.PP.KD |>
  right_join(iso2c, by = "iso2c") |>
  filter(iso2c %in% c("1W", "BR", "RU", "IN")) |>
  mutate(Iso2c = ifelse(iso2c == "RU", "Russia", Iso2c)) |>
  group_by(year) |>
  mutate(value = value/value[iso2c == "1W"]) |>
  year_to_date() |>
  filter(!(iso2c == "1W")) |>
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) |>
  add_flag_color("Iso2c") |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  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(0, 70, 1),
                     labels = scales::percent_format(accuracy = 1)) + 
  xlab("") + ylab("% of World GDP")

Related Data

Data on macro

source	dataset	Title	Updated
eurostat	nama_10_a10	Gross value added and income by A*10 industry breakdowns - nama_10_a10	2026-08-31
eurostat	nama_10_a10_e	Employment by A*10 industry breakdowns - nama_10_a10_e	2026-08-31
eurostat	nama_10_gdp	GDP and main components (output, expenditure and income) - nama_10_gdp	2026-08-31
eurostat	nama_10_lp_ulc	Labour productivity and unit labour costs - nama_10_lp_ulc	2026-08-31
eurostat	namq_10_a10	Gross value added and income A*10 industry breakdowns - namq_10_a10	2026-08-31
eurostat	namq_10_a10_e	Employment A*10 industry breakdowns - namq_10_a10_e	2026-08-31
eurostat	namq_10_gdp	GDP and main components (output, expenditure and income) - namq_10_gdp	2026-08-31
eurostat	namq_10_lp_ulc	Labour productivity and unit labour costs - namq_10_lp_ulc	2026-08-31
eurostat	namq_10_pc	Main GDP aggregates per capita - namq_10_pc	2026-08-31
eurostat	nasa_10_nf_tr	Non-financial transactions - nasa_10_nf_tr	2026-08-10
eurostat	nasq_10_nf_tr	Non-financial transactions - nasq_10_nf_tr	2026-08-28
fred	gdp	Gross Domestic Product - gdp	2026-09-01
oecd	QNA	Quarterly National Accounts - QNA	2026-09-01
oecd	SNA_TABLE1	Gross domestic product (GDP) - SNA_TABLE1	2026-08-02
oecd	SNA_TABLE14A	Non-financial accounts by sectors - SNA_TABLE14A	2026-08-02
oecd	SNA_TABLE2	Disposable income and net lending - net borrowing - SNA_TABLE2	2026-08-02
oecd	SNA_TABLE6A	Value added and its components by activity, ISIC rev4 - SNA_TABLE6A	2026-08-02
wdi	NE.RSB.GNFS.ZS	External balance on goods and services (% of GDP) - NE.RSB.GNFS.ZS	2026-09-01
wdi	NY.GDP.MKTP.CD	GDP (current USD) - NY.GDP.MKTP.CD	2026-09-01
wdi	NY.GDP.MKTP.PP.CD	GDP, PPP (current international D) - NY.GDP.MKTP.PP.CD	2026-09-01
wdi	NY.GDP.PCAP.CD	GDP per capita (current USD) - NY.GDP.PCAP.CD	2026-09-01
wdi	NY.GDP.PCAP.KD	GDP per capita (constant 2015 USD) - NY.GDP.PCAP.KD	2026-09-01
wdi	NY.GDP.PCAP.PP.CD	GDP per capita, PPP (current international D) - NY.GDP.PCAP.PP.CD	2026-09-01
wdi	NY.GDP.PCAP.PP.KD	GDP per capita, PPP (constant 2011 international D) - NY.GDP.PCAP.PP.KD	2026-09-01