Manufacturing, value added (current USD)

Data - WDI

Author

Info

source	dataset	.html	.RData
wdi	NV.IND.MANF.CD	2024-06-19	2024-06-09

Data on macro

source	dataset	.html	.RData
eurostat	nama_10_a10	2024-06-20	2024-06-08
eurostat	nama_10_a10_e	2024-06-20	2024-06-18
eurostat	nama_10_gdp	2024-06-20	2024-06-18
eurostat	nama_10_lp_ulc	2024-06-20	2024-06-08
eurostat	namq_10_a10	2024-06-20	2024-06-18
eurostat	namq_10_a10_e	2024-06-20	2024-06-08
eurostat	namq_10_gdp	2024-06-20	2024-06-08
eurostat	namq_10_lp_ulc	2024-06-20	2024-06-08
eurostat	namq_10_pc	2024-06-20	2024-06-18
eurostat	nasa_10_nf_tr	2024-06-19	2024-06-08
eurostat	nasq_10_nf_tr	2024-06-19	2024-06-08
fred	gdp	2024-06-18	2024-06-07
oecd	QNA	2024-06-06	2024-06-05
oecd	SNA_TABLE1	2024-06-19	2024-06-01
oecd	SNA_TABLE14A	2024-06-19	2024-04-15
oecd	SNA_TABLE2	2024-06-19	2024-04-11
oecd	SNA_TABLE6A	2024-06-19	2024-04-15
wdi	NE.RSB.GNFS.ZS	2024-06-20	2024-04-14
wdi	NY.GDP.MKTP.CD	2024-06-19	2024-05-06
wdi	NY.GDP.MKTP.PP.CD	2024-06-19	2024-04-14
wdi	NY.GDP.PCAP.CD	2024-06-19	2024-04-22
wdi	NY.GDP.PCAP.KD	2024-06-19	2024-05-06
wdi	NY.GDP.PCAP.PP.CD	2024-06-19	2024-04-22
wdi	NY.GDP.PCAP.PP.KD	2024-06-19	2024-05-06

LAST_COMPILE

LAST_COMPILE
2024-06-20

Last

Code

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

year	Nobs
2022	198

Nobs - Javascript

Code

NV.IND.MANF.CD %>%
  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

NV.IND.MANF.CD %>%
  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

NV.IND.MANF.CD %>%
  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 .}

Netherlands, Belgium, Switzerland, Turkey, Poland, Sweden

Code

NV.IND.MANF.CD %>%
  right_join(iso2c, by = "iso2c") %>%
  filter(iso2c %in% c("1W", "CH", "BE", "NL", "PO", "SE", "TR")) %>%
  year_to_date %>%
  filter(date >= as.Date("1997-01-01")) %>%
  group_by(date) %>%
  mutate(value = value/value[iso2c == "1W"]) %>%
  filter(!(iso2c == "1W")) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  ggplot(.) + theme_minimal() + scale_color_identity() + xlab("") + ylab("% of World Manufacturing value added") +
  geom_line(aes(x = date, y = value, color = color)) + add_5flags +
  scale_x_date(breaks = seq(1950, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 70, 0.2),
                     labels = scales::percent_format(accuracy = .1))

Germany, France, Italy, United Kingdom, Spain

Code

NV.IND.MANF.CD %>%
  right_join(iso2c, by = "iso2c") %>%
  filter(iso2c %in% c("1W", "DE", "FR", "IT", "ES", "GB")) %>%
  year_to_date %>%
  filter(date >= as.Date("1997-01-01")) %>%
  group_by(date) %>%
  mutate(value = value/value[iso2c == "1W"]) %>%
  filter(!(iso2c == "1W")) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "FR", color2, color)) %>%
  ggplot(.) + theme_minimal() + scale_color_identity() + xlab("") +
  xlab("") + ylab("% de la VA manufacturière mondiale") +
  geom_line(aes(x = date, y = value, color = color)) + add_5flags +
  scale_x_date(breaks = seq(1950, 2100, 2) %>% 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))

Brazil, Mexico, Argentina

Code

NV.IND.MANF.CD %>%
  right_join(iso2c, by = "iso2c") %>%
  filter(iso2c %in% c("1W", "BR", "MX", "AR")) %>%
  year_to_date %>%
  filter(date >= as.Date("1997-01-01")) %>%
  group_by(date) %>%
  mutate(value = value/value[iso2c == "1W"]) %>%
  filter(!(iso2c == "1W")) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "MX", color2, color)) %>%
  ggplot(.) + theme_minimal() + scale_color_identity() + xlab("") + ylab("% of World Manufacturing value added") +
  geom_line(aes(x = date, y = value, color = color)) + add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 2) %>% 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))

China, E.U., U.S.

All

Code

data <- NV.IND.MANF.CD %>%
  right_join(iso2c, by = "iso2c") %>%
  filter(iso2c %in% c("1W", "US", "CN", "EU")) %>%
  year_to_date %>%
  filter(date >= as.Date("1997-01-01")) %>%
  group_by(date) %>%
  mutate(value = value/value[iso2c == "1W"]) %>%
  filter(!(iso2c == "1W")) %>%
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  mutate(color = ifelse(iso2c == "US", color2, color)) %>%
  select(iso2c, Iso2c, date, value, color)

data %>%
  ggplot(.) + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = value, color = color)) +
  add_3flags +
  scale_x_date(breaks = seq(1950, 2100, 2) %>% 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("% de la VA manufacturière mondiale")

2005-

Code

NV.IND.MANF.CD %>%
  right_join(iso2c, by = "iso2c") %>%
  filter(iso2c %in% c("1W", "US", "CN", "EU")) %>%
  year_to_date %>%
  filter(date >= as.Date("1997-01-01")) %>%
  group_by(date) %>%
  mutate(value = value/value[iso2c == "1W"]) %>%
  filter(!(iso2c == "1W")) %>%
  mutate(Iso2c = ifelse(iso2c == "EU", "Europe", Iso2c)) %>%
  filter(date >= as.Date("2005-01-01")) %>%
  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_3flags +
  theme(legend.title = element_blank(),
        legend.position = c(0.85, 0.85)) +
  scale_x_date(breaks = seq(1950, 2022, 2) %>% 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)) + 
  xlab("") + ylab("% de la VA manufacturière mondiale")