GDP per capita, PPP (constant 2011 international D)

Data - WDI

Author

François Geerolf

Info

source dataset Title .html .rData
wdi NY.GDP.PCAP.PP.KD GDP per capita, PPP (constant 2011 international D) 2026-01-15 2026-01-15

Data on macro

source dataset Title .html .rData
wdi NY.GDP.MKTP.CD GDP (current USD) 2026-01-15 2026-01-07
eurostat nama_10_a10 Gross value added and income by A*10 industry breakdowns 2026-01-16 2026-01-16
eurostat nama_10_a10_e Employment by A*10 industry breakdowns 2026-01-16 2026-01-15
eurostat nama_10_gdp GDP and main components (output, expenditure and income) 2026-01-16 2026-01-15
eurostat nama_10_lp_ulc Labour productivity and unit labour costs 2026-01-16 2026-01-16
eurostat namq_10_a10 Gross value added and income A*10 industry breakdowns 2026-01-16 2026-01-15
eurostat namq_10_a10_e Employment A*10 industry breakdowns 2025-05-24 2026-01-16
eurostat namq_10_gdp GDP and main components (output, expenditure and income) 2025-10-27 2026-01-16
eurostat namq_10_lp_ulc Labour productivity and unit labour costs 2026-01-16 2026-01-16
eurostat namq_10_pc Main GDP aggregates per capita 2026-01-16 2026-01-15
eurostat nasa_10_nf_tr Non-financial transactions 2026-01-16 2026-01-16
eurostat nasq_10_nf_tr Non-financial transactions 2026-01-16 2026-01-16
fred gdp Gross Domestic Product 2026-01-16 2026-01-16
oecd QNA Quarterly National Accounts 2024-06-06 2025-05-24
oecd SNA_TABLE1 Gross domestic product (GDP) 2026-01-15 2025-05-24
oecd SNA_TABLE14A Non-financial accounts by sectors 2026-01-15 2024-06-30
oecd SNA_TABLE2 Disposable income and net lending - net borrowing 2024-07-01 2024-04-11
oecd SNA_TABLE6A Value added and its components by activity, ISIC rev4 2024-07-01 2024-06-30
wdi NE.RSB.GNFS.ZS External balance on goods and services (% of GDP) 2026-01-15 2026-01-15
wdi NY.GDP.MKTP.PP.CD GDP, PPP (current international D) 2026-01-15 2026-01-15
wdi NY.GDP.PCAP.CD GDP per capita (current USD) 2026-01-15 2026-01-15
wdi NY.GDP.PCAP.KD GDP per capita (constant 2015 USD) 2026-01-15 2026-01-15
wdi NY.GDP.PCAP.PP.CD GDP per capita, PPP (current international D) 2026-01-15 2026-01-15
wdi NY.GDP.PCAP.PP.KD GDP per capita, PPP (constant 2011 international D) 2026-01-15 2026-01-15

LAST_COMPILE

LAST_COMPILE
2026-01-16

Last

Code 
NY.GDP.PCAP.PP.KD %>%
  group_by(year) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(year)) %>%
  head(1) %>%
  print_table_conditional()
year Nobs
2024 236

Nobs - Javascript

Code 
NY.GDP.PCAP.PP.KD %>%
  left_join(iso2c, by = "iso2c") %>%
  group_by(iso2c, Iso2c) %>%
  
  mutate(value = round(value)) %>%
  summarise(Nobs = n(),
            `Year 1` = first(year),
            `GDP Per Capita 1` = first(value) %>% paste0("$ ", .),
            `Year 2` = last(year),
            `GDP Per Capita 2` = 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 .}

1990, 2019, growth 1990-2019

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(year %in% c(1990, 2019)) %>%
  left_join(iso2c, by = "iso2c") %>%
  spread(year, value) %>%
  mutate(growth = round(100*(`2019`/`1990`-1),1)) %>%
  mutate(`1990` = round(`1990`),
         `2019` = round(`2019`)) %>%
  arrange(-growth) %>%
  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 .}

Euro Area vs. US

Base 100

Code 
NY.GDP.PCAP.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)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "US", color2, color)) %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  add_2flags +
  scale_x_date(breaks = seq(1950, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(70, 200, 5)) + 
  xlab("") + ylab("PIB/habitant en $ (100 = 2008)")

Avec dollars

Code 
NY.GDP.PCAP.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)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "US", color2, color)) %>%
  ungroup %>%
  mutate(dollar = value,
         value = 100*value/value[2]) %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  add_2flags +
  scale_x_date(breaks = seq(1950, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10, 200, 5)) + 
  xlab("") + ylab("PIB/habitant 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), " /hab")))

Germany, France

All

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("DE", "FR")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(seq(10000, 70000, 10000), seq(10000, 60000, 5000)),
                labels = dollar_format(acc = 1))

GDP Per capita - PPP VS current (USD)

Log

Code 
NY.GDP.PCAP.PP.KD %>%
  bind_rows(NY.GDP.PCAP.KD) %>%
  filter(iso2c %in% c("DE", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c2 = gsub("Germany", "Allemagne", Iso2c),
         variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
                               variable == "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
  year_to_date %>%
  filter(date >= as.Date("1990-01-01")) %>%
  ggplot(.) + xlab("") + ylab("PIB Par habitant ($ constants)") + theme_minimal() + add_4flags +
  geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) + 
  scale_color_manual(values = c("#000000", "#ED2939", "#000000", "#ED2939")) +
  scale_linetype_manual(values = c("solid", "solid", "dashed", "dashed")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.85)) +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 200000, 2000),
                     labels = dollar_format(a = 1))

Linear

Code 
NY.GDP.PCAP.PP.KD %>%
  bind_rows(NY.GDP.PCAP.KD) %>%
  filter(iso2c %in% c("DE", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c2 = gsub("Germany", "Allemagne", Iso2c),
         variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
                               variable == "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
  year_to_date %>%
  ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + add_4flags +
  geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) + 
  scale_color_manual(values = c("#000000", "#ED2939", "#000000", "#ED2939")) +
  scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.85)) +
  scale_x_date(breaks = seq(1950, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 200000, 2000),
                     labels = dollar_format(a = 1))

Switzerland, France

All

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("CH", "FR")) %>%
  year_to_date %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(seq(10000, 70000, 10000), seq(10000, 50000, 5000)),
                labels = dollar_format(acc = 1))

GDP Per capita - PPP VS current (USD)

Log

Code 
NY.GDP.PCAP.PP.KD %>%
  bind_rows(NY.GDP.PCAP.KD) %>%
  filter(iso2c %in% c("CH", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c2 = gsub("Switzerland", "Suisse", Iso2c),
         variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
                               variable == "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
  year_to_date %>%
  ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + add_4flags +
  geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) + 
  scale_color_manual(values = c("#002395", "#FF0000", "#002395", "#FF0000")) +
  scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.85)) +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 200000, 5000),
                     labels = dollar_format(a = 1))

Linear

Code 
NY.GDP.PCAP.PP.KD %>%
  bind_rows(NY.GDP.PCAP.KD) %>%
  filter(iso2c %in% c("CH", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c2 = gsub("Switzerland", "Suisse", Iso2c),
         variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
                               variable == "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
  year_to_date %>%
  ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + add_4flags +
  geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) + 
  scale_color_manual(values = c("#002395", "#FF0000", "#002395", "#FF0000")) +
  scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.85)) +
  scale_x_date(breaks = seq(1950, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 200000, 5000),
                     labels = dollar_format(a = 1))

Euro area vs. US

Base 100 = 1999

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("US", "XC")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "XC", color2, color)) %>%
  group_by(iso2c, Iso2c) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP, 100 = 1999") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = c(seq(1999, 2100, 5), seq(2002, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 400, 5))

GDP Per capita - PPP VS current (USD)

All

Code 
NY.GDP.PCAP.PP.KD %>%
  bind_rows(NY.GDP.PCAP.KD) %>%
  filter(iso2c %in% c("US", "XC")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c2 = case_when(iso2c == "US" ~ "Etats-Unis",
                            iso2c == "XC" ~ "Zone euro"),
         variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
                               variable == "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
  year_to_date %>%
  ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + add_4flags +
  geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) + 
  scale_color_manual(values = c("#3C3B6E", "#FFCC00", "#3C3B6E", "#FFCC00")) +
  scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.85)) +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 200000, 5000),
                     labels = dollar_format(a = 1))

1990-

Code 
NY.GDP.PCAP.PP.KD %>%
  bind_rows(NY.GDP.PCAP.KD) %>%
  filter(iso2c %in% c("US", "XC")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c2 = case_when(iso2c == "US" ~ "Etats-Unis",
                            iso2c == "XC" ~ "Zone euro"),
         variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
                               variable == "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
  year_to_date %>%
  filter(date >= as.Date("1990-01-01")) %>%
  ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + add_4flags +
  geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) + 
  scale_color_manual(values = c("#3C3B6E", "#FFCC00", "#3C3B6E", "#FFCC00")) +
  scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.85)) +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 200000, 5000),
                     labels = dollar_format(a = 1))

1999-

Value

Code 
NY.GDP.PCAP.PP.KD %>%
  bind_rows(NY.GDP.PCAP.KD) %>%
  filter(iso2c %in% c("US", "XC")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c2 = case_when(iso2c == "US" ~ "Etats-Unis",
                            iso2c == "XC" ~ "Zone euro"),
         variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
                               variable == "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + add_4flags +
  geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) + 
  scale_color_manual(values = c("#3C3B6E", "#FFCC00", "#3C3B6E", "#FFCC00")) +
  scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.85)) +
  scale_x_date(breaks = c(seq(1999, 2100, 5), seq(2002, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 200000, 5000),
                     labels = dollar_format(a = 1))

Base = 100

Code 
NY.GDP.PCAP.PP.KD %>%
  bind_rows(NY.GDP.PCAP.KD) %>%
  filter(iso2c %in% c("US", "XC")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c2 = case_when(iso2c == "US" ~ "Etats-Unis",
                            iso2c == "XC" ~ "Zone euro"),
         variable2 = case_when(variable == "NY.GDP.PCAP.PP.KD" ~ paste0("PIB/hab en PPA - ", Iso2c2),
                               variable == "NY.GDP.PCAP.KD" ~ paste0("PIB/hab - ", Iso2c2))) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(variable2) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot(.) + xlab("") + ylab("PIB Par habitant") + theme_minimal() + 
  geom_line(aes(x = date, y = value, color = variable2, linetype = variable2)) + 
  scale_color_manual(values = c("#3C3B6E", "#FFCC00", "#3C3B6E", "#FFCC00")) +
  scale_linetype_manual(values = c("dashed", "dashed", "solid", "solid")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.85)) +
  scale_x_date(breaks = c(seq(1999, 2100, 5), seq(2002, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 300, 10))

Euro area vs. US vs. France

Linear

Code 
NY.GDP.PCAP.PP.KD %>%
  # XC: Euro area
  filter(iso2c %in% c("US", "XC", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "XC", color2, color)) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Base 100 = 1990

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("US", "XC", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "XC", color2, color)) %>%
  group_by(iso2c, Iso2c) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP, 100 = 1990") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 400, 10))

Base 100 = 2006

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("US", "XC", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "XC", color2, color)) %>%
  group_by(iso2c, Iso2c) %>%
  arrange(date) %>%
  filter(date >= as.Date("2006-01-01")) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP, 100 = 2006") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10, 400, 2))

Base 100 = 2007

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("US", "XC", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "XC", color2, color)) %>%
  group_by(iso2c, Iso2c) %>%
  arrange(date) %>%
  filter(date >= as.Date("2007-01-01")) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP, 100 = 2007") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10, 400, 2))

Base 100 = 2008

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("US", "XC", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "XC", "Europe", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "XC", color2, color)) %>%
  group_by(iso2c, Iso2c) %>%
  arrange(date) %>%
  filter(date >= as.Date("2008-01-01")) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP, 100 = 2008") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10, 400, 2))

Italy, France, US, Switzerland, Spain, US

Linear

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("US", "ES", "IT", "FR", "CH", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Log

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("US", "ES", "IT", "FR", "CH", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Base 100 = 1990

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("US", "ES", "IT", "FR", "CH", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  group_by(iso2c, Iso2c) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP, 100 = 1990") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 400, 10))

Italy, France, US, UK, Switzerland, Spain - Compare

Linear

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("US", "GB", "ES", "IT", "FR", "CH")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Log

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("US", "GB", "ES", "IT", "FR", "CH")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Poland, Portugal, Spain

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("PL", "HU", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  group_by(iso2c) %>%
  mutate(value = 100*value /value[date == as.Date("1991-01-01")]) %>%
  filter(date >= as.Date("1990-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = Iso2c)) + 
  xlab("") + ylab("GDP per capita (constant 2010 USD)") + theme_minimal() +
  scale_color_manual(values = c("#002395", "#436F4D", "#DC143C")) + add_3flags +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.8)) +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 400, 10))

Japan

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("JP")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  ggplot(.) + geom_line(aes(x = date, y = value)) +
  xlab("") + ylab("GDP per capita") + theme_minimal() +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.2)) +
  scale_x_date(breaks = seq(1950, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 200000, 1000),
                     labels = dollar_format(a = 1))

France, Germany

Linear

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Log

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 80000, 2000),
                labels = dollar_format(acc = 1))

Index = 100

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  group_by(iso2c) %>%
  mutate(value = 100*value/value[year == 1990]) %>%
  year_to_date %>%
  ggplot(.) + xlab("") + ylab("PPP GDP per capita (1990 = 100)") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = Iso2c)) +
  scale_color_manual(values = c("#002395", "#000000")) + add_2flags +
  theme(legend.position = "none") +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 200, 5))

China, France, Germany

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("CN", "FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Italy, Portugal, Spain

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("ES", "IT", "PT")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Spain, United Kingdom, United States

Linear

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("US", "GB", "ES")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Log

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("US", "GB", "ES")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Argentina, Chile, Venezuela

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("AR", "CL", "VE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Greece, Hong Kong, Mexico

Linear

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("GR", "HK", "MX")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "HK", "Hong Kong", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))

Log

Code 
NY.GDP.PCAP.PP.KD %>%
  filter(iso2c %in% c("GR", "HK", "MX")) %>%
  left_join(iso2c, by = "iso2c") %>%
  mutate(Iso2c = ifelse(iso2c == "HK", "Hong Kong", Iso2c)) %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  
  ggplot(.) + xlab("") + ylab("GDP per capita, PPP") +
  geom_line(aes(x = date, y = value, color = color)) + 
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 80000, 5000),
                labels = dollar_format(acc = 1))