~/data/wdi/

Info

source	dataset	.html	.RData	.Rmd
wdi	NV.IND.MANF.ZS	2023-12-24	2023-09-20	2023-09-20

Data on industry

source	dataset	Title	Download	Compile
wdi	NV.IND.MANF.ZS	Manufacturing, value added (% of GDP)	2023-09-20	2023-12-24
ec	INDUSTRY	Industry (sector data)	2023-10-01	2023-10-01
eurostat	ei_isin_m	Industry - monthly data - index (2015 = 100) (NACE Rev. 2) - ei_isin_m	2023-12-24	2023-12-31
eurostat	htec_trd_group4	High-tech trade by high-tech group of products in million euro (from 2007, SITC Rev. 4)	2023-12-24	2023-12-31
eurostat	nama_10_a64	National accounts aggregates by industry (up to NACE A*64)	2023-12-24	2023-12-31
eurostat	nama_10_a64_e	National accounts employment data by industry (up to NACE A*64)	2023-12-31	2023-12-24
eurostat	namq_10_a10_e	Employment A*10 industry breakdowns	2023-12-31	2023-12-27
eurostat	road_eqr_carmot	New registrations of passenger cars by type of motor energy and engine size - road_eqr_carmot	2023-12-24	2023-12-31
eurostat	sts_inpp_m	Producer prices in industry, total - monthly data	2023-12-24	2024-01-02
eurostat	sts_inppd_m	Producer prices in industry, domestic market - monthly data	2023-12-31	2023-12-24
eurostat	sts_inpr_m	Production in industry - monthly data	2023-12-24	2023-12-31
eurostat	sts_intvnd_m	Turnover in industry, non domestic market - monthly data - sts_intvnd_m	2023-12-24	2023-12-31
fred	industry	Manufacturing, Industry	2024-01-06	2024-01-06
oecd	ALFS_EMP	Employment by activities and status (ALFS)	2023-10-30	2024-01-05
oecd	BERD_MA_SOF	Business enterprise R&D expenditure by main activity (focussed) and source of funds	2023-09-09	2024-01-05
oecd	GBARD_NABS2007	Government budget allocations for R and D	2023-11-22	2024-01-05
oecd	MEI_REAL	Production and Sales (MEI)	2023-12-27	2024-01-05
oecd	MSTI_PUB	Main Science and Technology Indicators	2023-10-04	2024-01-05
oecd	SNA_TABLE4	PPPs and exchange rates	2024-01-06	2024-01-06
wdi	NV.IND.EMPL.KD	Industry, value added per worker (constant 2010 USD)	2023-06-18	2024-01-06
wdi	NV.IND.MANF.CD	Manufacturing, value added (current USD)	2023-12-17	2024-01-06
wdi	NV.IND.TOTL.KD	Industry (including construction), value added (constant 2015 USD) - NV.IND.TOTL.KD	2022-09-27	2023-12-24
wdi	NV.IND.TOTL.ZS	Industry, value added (including construction) (% of GDP)	2023-09-20	2023-12-24
wdi	SL.IND.EMPL.ZS	Employment in industry (% of total employment)	2023-07-22	2023-12-24
wdi	TX.VAL.MRCH.CD.WT	Merchandise exports (current USD)	2023-04-12	2023-12-24

LAST_COMPILE

LAST_COMPILE
2024-01-06

Last

NV.IND.MANF.ZS %>%
  group_by(year) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(year)) %>%
  head(1) %>%
  print_table_conditional()

year	Nobs
2022	166

Nobs - Javascript

Nobs - Max - Min

NV.IND.MANF.ZS %>%
  left_join(iso2c, by = "iso2c") %>%
  group_by(iso2c, Iso2c) %>%
  rename(value = `NV.IND.MANF.ZS`) %>%
  mutate(value = round(value, 1)) %>%
  summarise(Nobs = n(),
            `Year 1` = first(year),
            `Manufacturing Share 1 (%)` = first(value),
            `Year 2` = last(year),
            `Manufacturing Share 2 (%)` = last(value)) %>%
  arrange(-`Manufacturing Share 2 (%)`) %>%
  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 .}

Nobs

NV.IND.MANF.ZS %>%
  left_join(iso2c, by = "iso2c") %>%
  group_by(iso2c, Iso2c) %>%
  summarise(Period = paste0(first(year), "-", last(year)),
            Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Afghanistan

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("AF")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  ggplot(.) + xlab("") + ylab("Manufacturing, value added (% of GDP)") + 
  geom_line(aes(x = date, y = NV.IND.MANF.ZS/100)) + theme_minimal() +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.2)) +
  scale_x_date(breaks = seq(1950, 2020, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

Argentina

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("AR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  ggplot(.) + xlab("") + ylab("Manufacturing, value added (% of GDP)") + 
  geom_line(aes(x = date, y = NV.IND.MANF.ZS/100)) + theme_minimal() +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.2)) +
  scale_x_date(breaks = seq(1950, 2020, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

Uruguay

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("UY")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  ggplot(.) + xlab("") + ylab("Manufacturing, value added (% of GDP)") + 
  geom_line(aes(x = date, y = NV.IND.MANF.ZS/100)) + theme_minimal() +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.2)) +
  scale_x_date(breaks = seq(1950, 2020, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

Hungary

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("HU")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  ggplot(.) + xlab("") + ylab("Manufacturing, value added (% of GDP)") + 
  geom_line(aes(x = date, y = NV.IND.MANF.ZS/100)) + theme_minimal() +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.2)) +
  scale_x_date(breaks = seq(1950, 2020, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 0.5),
                     labels = scales::percent_format(accuracy = 0.1))

OECD, World, Advanced

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("OE", "1W", "EU")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

Sweden, OECD, World, Advanced

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("OE", "1W", "EU", "SE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_4flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

OECD, Advanced, France, Germany

All

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("OE", "FR", "DE", "US", "GB")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

1995-

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("OE", "FR", "DE", "US", "GB")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1950, 2020, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

OECD, World, Advanced, France

All

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("OE", "1W", "FR", "DE", "US", "GB")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "DE", color2, color)) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

1995-

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("OE", "1W", "FR", "DE", "US", "GB")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "DE", color2, color)) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1950, 2020, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

1995-2021

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("OE", "1W", "FR", "DE", "US", "GB")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01"),
         date <= as.Date("2021-01-01")) %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "DE", color2, color)) %>%
  mutate(color= ifelse(iso2c == "GB", "#012169", color)) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1950, 2030, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

United Kingdom, United States, France, World, OECD

1995-2021

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("OE", "1W", "FR", "US", "GB")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01"),
         date <= as.Date("2021-01-01")) %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "DE", color2, color)) %>%
  mutate(color= ifelse(iso2c == "GB", "#012169", color)) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1950, 2030, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

China

1995-

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("OE", "1W", "FR", "DE", "US", "GB", "CN")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "DE", color2, color)) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_7flags +
  scale_x_date(breaks = seq(1950, 2020, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

OECD, World, Advanced, France

All

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("OE", "1W", "FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "DE", color2, color)) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_4flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

1997-

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("OE", "1W", "FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  filter(date >= as.Date("1997-01-01")) %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "DE", color2, color)) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_4flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

France, Germany, OECD

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("OE", "FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

China, France, Germany

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("CN", "FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

Sweden, France, Germany

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("SE", "FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

China, India, France, Germany, Japan, US, UK

All

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("CN", "FR", "DE", "IN", "GB", "US", "JP")) %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  year_to_date %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_7flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

1990-

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("CN", "FR", "DE", "IN", "GB", "US", "JP")) %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  year_to_date %>%
  filter(date >= as.Date("1990-01-01")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_7flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

Italy, Portugal, Spain

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("IT", "PT", "ES")) %>%
  left_join(iso2c, by = "iso2c") %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  year_to_date %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

Germany, Switzerland, Netherlands

All

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("DE", "CH", "KR", "JP")) %>%
  left_join(tibble(iso2c = c("DE", "CH", "KR", "JP"),
                   Iso2c = c("Germany", "Switzerland", "South Korea", "Japan")),
            by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_4flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

1995-

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("DE", "CH", "KR", "JP")) %>%
  left_join(tibble(iso2c = c("DE", "CH", "KR", "JP"),
                   Iso2c = c("Germany", "Switzerland", "South Korea", "Japan")),
            by = "iso2c") %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_4flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

Italy, Portugal, Spain, Greece, France

All

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("IT", "PT", "ES", "GR", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = NV.IND.MANF.ZS/100, color = Iso2c)) + 
  theme_minimal() +
  scale_color_manual(values = c("#002395", "#0D5EAF", "#009246", "#FF0000", "#FFC400")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.2)) +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  geom_image(data = . %>%
               filter(date == as.Date("2007-01-01")) %>%
               mutate(image = paste0("../../icon/flag/", str_to_lower(gsub(" ", "-", Iso2c)), ".png")),
             aes(x = date, y = NV.IND.MANF.ZS/100, image = image), asp = 1.5) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)")

1995-

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("IT", "PT", "ES", "GR", "FR")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  ggplot(.) + 
  geom_line(aes(x = date, y = NV.IND.MANF.ZS/100, color = Iso2c)) + 
  theme_minimal() +
  scale_color_manual(values = c("#002395", "#0D5EAF", "#009246", "#FF0000", "#FFC400")) +
  theme(legend.position = "none") + 
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  geom_image(data = . %>%
               filter(date == as.Date("2016-01-01")) %>%
               mutate(image = paste0("../../icon/flag/", str_to_lower(gsub(" ", "-", Iso2c)), ".png")),
             aes(x = date, y = NV.IND.MANF.ZS/100, image = image), asp = 1.5) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)")

Spain, United Kingdom, United States

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("US", "GB")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_2flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1))

Argentina, Chile, Venezuela

NV.IND.MANF.ZS %>%
  filter(iso2c %in% c("AR", "CL", "VE")) %>%
  left_join(tibble(iso2c = c("AR", "CL", "VE"),
                   Iso2c = c("Argentina", "Chile", "Venezuela")),
            by = "iso2c") %>%
  year_to_date %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

Greece, Hong Kong, Mexico

NV.IND.MANF.ZS %>%
  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")) %>%
  mutate(value = NV.IND.MANF.ZS/100) %>%
  ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
  xlab("") + ylab("Manufacturing, value added (% of GDP)") +
  theme_minimal() + scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1950, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

Manufacturing, value added (% of GDP)

Data - WDI

François Geerolf

Info

Data on industry

LAST_COMPILE

Last

Nobs - Javascript

Nobs - Max - Min

Nobs

Afghanistan

Argentina

Uruguay

Hungary

OECD, World, Advanced

Sweden, OECD, World, Advanced

OECD, Advanced, France, Germany

All

1995-

OECD, World, Advanced, France

All

1995-

1995-2021

United Kingdom, United States, France, World, OECD

1995-2021

China

1995-

OECD, World, Advanced, France

All

1997-

France, Germany, OECD

China, France, Germany

Sweden, France, Germany

China, India, France, Germany, Japan, US, UK

All

1990-

Italy, Portugal, Spain

Germany, Switzerland, Netherlands

All

1995-

Italy, Portugal, Spain, Greece, France

All

1995-

Spain, United Kingdom, United States

Argentina, Chile, Venezuela

Greece, Hong Kong, Mexico